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  • Reinforcement Learning   RL算法tricks和搭环境遇到的问题. [slides] 宁鲲鹏 黄振 何花

    • TCHALLA APP

  • 2024-09-02   AETTA: Label-Free Accuracy Estimation for Test-Time Adaptation [slides] 郑腾鑫陵
  • 2024-09-02   Adversarial Graph Augmentation to Improve Graph Contrastive Learning [slides] 吴子涵
  • 2024-09-02   Prompt-aligned Gradient for Prompt Tuning [slides] 葛泽庆
  • 2024-09-09   Exploiting Conjugate Label Information for Multi-Instance Partial-Label Learning [slides] 周傅毅楠
  • 2024-09-09   EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level Latencies [slides] 颜劭铭
  • 2024-09-09   DGE: Direct Gaussian 3D Editing by Consistent Multi-view Editing [slides] 吴盛杰

    • SAGITTARIUS APP

  • 2024-03-18   Query-Policy Misalignmenr in Preference-Based Reinforcement Learning [slides] 罗钦文
  • 2024-03-18   Beyond Uniform Sampling: Offline Reinforcement Learning with Imbalanced Datasets [slides] 周立戎
  • 2024-03-18   Parameter-free Online Test-time Adaptation [slides] 赵世佶
  • 2024-04-22   Exploiting Label Skews in Federated Learning with Model Concatenation [slides] 葛泽庆
  • 2024-04-22   How Re-sampling Helps for Long-Tail Learning? [slides] 郑金鹏
  • 2024-04-22   CodeLLM Report [slides] 吕伟杰
  • 2024-04-29   GaussianEditor: Editing 3D Gaussians Delicately with Text Instructions [slides] 吴盛杰
  • 2024-04-29   Partial Label Learning with Dissimilarity Propagation guided Candidate Label Shrinkage [slides] 周傅毅楠
  • 2024-04-29   Review-Enhanced Hierarchical Contrastive Learning for Recommendation [slides] 牛荣兵
  • 2024-05-06   CHMATCH: Contrastive Hierarchical Matching and Robust Adaptive Threshold Boosted Semi-Supervised Learning [slides] 牛纪龙
  • 2024-05-06   Unbiased scene graph generation from biased training [gateio] 彭沛
  • 2024-05-13   No Fear of Classifier Biases: Neural Collapse Inspired Federated Learning with Synthetic and Fixed Classifier [slides] 周子健
  • 2024-05-13   Exploring Structured Semantic Prior for Multi Label Recognition with Incomplete Labels [slides] 熊淑贤
  • 2024-05-13   LTGC: Long-tail Recognition via Leveraging LLMs-driven Generated Content [slides] 王迁仟
  • 2024-05-20   YolOOD: Utilizing Object Detection Concepts for Multi-Label Out-of-Distribution Detection [slides] 刘昊哲
  • 2024-05-20   Brighten-and-Colorize: A Decoupled Network for Customized Low-Light Image Enhancement [slides] 高远航
  • 2024-05-20   Variational Graph Generative-Contrastive Learning for Recommendation [slides] 张李军
  • 2024-05-27   Subclass-balancing Contrastive Learning for Long-tailed Recognition [slides] 陈夕程
  • 2024-05-27   Adaptive Early-Learning Correction for Segmentation from Noisy Annotations [slides] 孙悦
  • 2024-05-27   Inconsistency-Based Data-Centric Active Open-Set Annotation [slides] 宗辰辰
  • 2024-06-03   FineRec: Exploring Fine-grained Sequential Recommendation [slides] 朱梓源
  • 2024-06-03   Balanced Classification: A Unified Framework for Long-Tailed Object Detection [slides] 魏晓蕾
  • 2024-06-03   DUAL RL: UNIFICATION AND NEW METHODS FOR REINFORCEMENT AND IMITATION LEARNING [slides] 周立戎
  • 2024-06-17   Reparameterized Policy Learning for Multimodal Trajectory Optimization [slides] 罗钦文
  • 2024-06-17   Unifying Top-down and Bottom-up Scanpath Prediction Using Transformers [slides] 赖彦涛
  • 2024-06-24   Mamba: Linear-Time Sequence Modeling with Selective State Spaces Series [slides] 欣子豪
  • 2024-06-24   Mitigating Backdoor Attacks in Federated Learning [slides] 丁宾宾
  • 2024-07-01   Zero-Reference Low-Light Enhancement via Physical Quadruple Priors [slides] 徐峥岩
  • 2024-07-01   Multi-modal Models: Multi-modal Large language Models [slides] 范恒博
  • 2024-07-01   LLM Tokenizer and Agents [slides] 王烨文
  • 2024-07-08   SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution [slides] 李雅超
  • 2024-07-08   Semi-Supervised Domain Generalization with Known and Unknown Classes [slides] 肖家豪
  • 2024-07-08   Switching Temporary Teachers for Semi-Supervised Semantic Segmentation [slides] 陈傲
  • 2024-03-04   InstanceDiffusion: Instance-level Control for Image Generation [slides] 李雅超
  • 2024-03-04   On the Pitfall of Mixup for Uncertainty Calibration [slides] 宗辰辰
  • 2024-03-11   MarginMatch: Improving Semi-Supervised Learning with Pseudo-Margins [slides] 牛纪龙
  • 2024-03-11   Global and Local Mixture Consistency Cumulative Learning for Long-tailed Visual Recognitions [slides] 魏晓蕾
  • 2024-03-11   Current Status and Development Trend of Semi-supervised Objective Detection Research [slides] 欣子豪
  • 2024-03-25   Channel-spatial knowledge distillation for efficient semantic segmentation [slides] 孙悦
  • 2024-03-25   Partial Multi-Label Learning with ProbabilisticGraphical Disambiguation [slides] 肖家豪
  • 2024-03-25   General Debiasing for Graph-based Collaborative Filtering viaAdversarial Graph Dropout [slides] 朱梓源
  • 2024-04-08   Null-text Inversion for Editing Real Images using Guided Diffusion Models [slides] 温铭浩
  • 2024-04-08   Defending against Backdoors in Federated Learningwith Robust Learning Rate [slides] 丁宾宾
  • 2024-04-08   UniAR: Unifying Human Attention and Response Prediction on Visual Content [slides] 赖彦涛
  • 2024-04-15   Flare7K++: Mixing Synthetic and Real Datasets for Nighttime Flare Removal and Beyond [slides] 刘睿璇
  • 2024-04-15   QuAVF: Quality-aware Audio-Visual Fusion for Ego4D Talking to Me Challenge [slides] 朱新佳
  • 2024-07-08   SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution [slides] 李雅超
  • 2024-07-08   Semi-Supervised Domain Generalization with Known and Unknown Classes [slides] 肖家豪
  • 2024-07-08   Switching Temporary Teachers for Semi-Supervised Semantic Segmentation [slides] 陈傲
  • 2024-07-15   HMD-Poser: On-Device Real-time Human Motion Tracking from Scalable Sparse Observations [slides] 张世杰
  • 2024-07-15   Learning Transferable Negative Prompts for Out-of-Distribution Detection [slides] 李其飞
  • 2024-07-15   Multimodal Prompting with Missing Modalities for Visual Recognition [slides] 朱新佳
  • 2024-07-22   OpenFWI [slides] 郭泽凯
  • 2024-07-22   View-Consistent 3D Editing with Gaussian Splatting [slides] 温铭浩
  • 2024-07-22   Flare7K: A Phenomenological Nighttime Flare Removal Dataset [slides] 刘睿璇

    • AMLT LOGIN

  • 2023-09-15   Talisman -Targeted Active Learning for Object Detection with Rare Classes and Slices Using Submodular Mutual Information [slides] 熊淑贤
  • 2023-09-15   AnomalyGPT: Detecting Industrial Anomalies using Large Vision-Language Models [slides] 吕伟杰
  • 2023-09-15   Learning Semantic-Aware Knowledge Guidance for Low-Light Image Enhancement [slides] 徐峥岩
  • 2023-09-07   Mosaic Representation Learning for Self-supervised Visual Pre-training [slides] 周傅毅楠
  • 2023-09-07   FEDERATED SEMI-SUPERVISED LEARNING WITH INTER-CLIENT CONSISTENCY & DISJOINT LEARNING [slides] 葛泽庆
  • 2023-09-07   Fast Counterfactual Inference for History-Based Reinforcement Learning [slides] 周立戎
  • 2023-09-22   Large Selective Kernel Network for Remote Sensing Object Detection [slides] 张婧炜
  • 2023-09-22   Iterative Prompt Learning for Unsupervised Backlit Image Enhancement [slides] 高远航
  • 2023-09-22   An intriguing failing of convolutional neural networks and the CoordConv solution [slides] 仇梦雨
  • 2023-10-13   Boosting Offline Reinforcement Learning with Action Preference Query [slides] 罗钦文
  • 2023-10-13   DOES ZERO-SHOT REINFORCEMENT LEARNING EXIST? [slides] 王烨文
  • 2023-10-13   Deep leakage from Gradients [slides] 丁宾宾
  • 2023-10-20   Efficient Teacher: Semi-Supervised Object Detection for YOLOv5 [slides] 欣子豪
  • 2023-10-20   Long-tailed classification by keeping the good and removing the bad momentum causal effect [slides] 彭沛
  • 2023-10-20   A Brief Introduction to LLM [slides] 郭洪涛
  • 2023-10-27   Bridging the Gap between Model Explanations in Partially Annotated Multi-label Classification [slides] 陈傲
  • 2023-10-27   Boosting Semi-Supervised Learning by Exploiting All Unlabeled Data [slides] 牛纪龙
  • 2023-11-03   Graph Contrastive Learning with Generative Adversarial Network [slides] 张李军
  • 2023-11-03   Label Matching Semi-Supervised Object Detection [slides] 胡刚
  • 2023-11-03   FCC: Feature Clusters Compression for Long-Tailed Visual Recognition [slides] 陈夕程
  • 2023-11-10   Learning in Imperfect Environmen：Multi-Label Classificationwith Long-Tailed Distribution and Partial Labels [slides] 陈佳瑶
  • 2023-11-10   IOMatch: Simplifying Open-Set Semi-Supervised Learning with Joint Inliers and Outliers Utilization [slides] 刘昊哲
  • 2023-11-10   Rethinking Gradient Projection Continual Learning: Stability / Plasticity Feature Space Decoupling [gate.io] 郑宇祥
  • 2023-11-17   PMAL: Open Set Recognition via Robust Prototype Mining [slides] 赵世佶
  • 2023-11-17   RankMatch: Fostering Confidence and Consistency in Learning with Noisy Labels [slides] 宗辰辰
  • 2023-11-17   How Re-sampling Helps for Long-Tail Learning? [slides] 王蕾
  • 2023-11-24   Person Image Synthesis via Denoising Diffusion Model [slides] 李雅超
  • 2023-11-24   Multimodal Models-1. Contrastive Language-Image Pre-training [slides] 范恒博
  • 2023-12-01   Smoothed Adaptive Weighting for Imbalanced Semi-Supervised Learning [slides] 肖家豪
  • 2023-12-01   Semi-Supervised Semantic Segmentation under Label Noise via Diverse Learning Groups [slides] 孙悦
  • 2023-12-01   COMPETITIVE PHYSICS INFORMED NETWORKS [slides] 单彬
  • 2023-12-08   Natural Language-conditioned Reinforcement Learning with Task-related Language Development and Translation [slides] 王烨文
  • 2023-12-08   Multimodal Models-2. Diffusion Model [slides] 范恒博
  • 2023-12-08   Local Color Distributions Prior for Image Enhancement [slides] 徐峥岩
  • 2023-12-15   Spatial Consistency Loss for Training Multi-Label Classifiers from Single-Label Annotations [slides] 陈傲
  • 2023-12-15   LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation [slides] 牛荣兵
  • 2023-12-15   VILA: Learning Image Aesthetics from User Comments with Vision-Language Pretraining [slides] 高远航
  • 2023-12-22   Partial Label Learning with a Partner [slides] 周傅毅楠
  • 2023-12-22   FedBR: Improving Federated Learning on Heterogeneous Data via Local Learning Bias Reduction [slides] 葛泽庆
  • 2023-12-22   NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis [slides] 吴盛杰

    • NFTBS EXCHANGES

  • 2023-02-17   Debiased Self-Training for Semi-Supervised Learning. [slides] 孙峰
  • 2023-02-17   Decoupled Contrastive Learning. [slides] 杨鹏辉
  • 2023-02-24   Label Inference Attacks Against Vertical Federated Learning. [slides] 丁宾宾
  • 2023-02-24   Causality-driven Hierarchical Structure Discovery for Reinforcement Learning. [slides] 周立戎
  • 2023-03-03   DIRICHLET-BASED UNCERTAINTY CALIBRATION FOR ACTIVE DOMAIN ADAPTATION. [slides] 宗辰辰
  • 2023-03-03   DMIS: Dynamic Mesh-based Importance Sampling for Training Physics-Informed Neural Networks. [slides] 单彬
  • 2023-03-03   Invariant Feature Learning for Generalized Long-Tailed Classification. [slides] 王蕾
  • 2023-03-09   Domain Adaptation Object Detection [slides] 胡刚
  • 2023-03-09   CAUSALITY COMPENSATED ATTENTION FOR CONTEXTUAL BIASED VISUAL RECOGNITION [slides] 陈佳瑶
  • 2023-03-09   Self-Sustaining Representation Expansion for Non-Exemplar Class-Incremental Learning [slides] 郑宇祥
  • 2023-03-17   Detecting Corrupted Labels Without Training a Model to Predict. [slides] 杨铭
  • 2023-03-17   Sparse Mixture-of-Experts are Domain Generalizable Learners. [slides] 杨鹏辉
  • 2023-03-24   How to Reweight Examples in SSL Using Meta-Learning? [slides] 范恒博
  • 2023-03-24   Understanding Deep Learning Requires Rethinking Generalization [slides] 万文海
  • 2023-03-31   Offline-to-Online in reinforcement learning [slides] 罗钦文
  • 2023-03-31   FreeMatch: Self-adaptive Thresholding for Semi-supervised Learning [slides] 肖家豪
  • 2023-04-28   Augmentation and Generalization in Contrastive Self-Supervised Learning [slides] 赵世佶
  • 2023-04-28   Image as Set of Points [slides] 胡刚
  • 2023-04-28   Residual Skill Policies [slides] 王烨文
  • 2023-05-05   Security algorithms under Vertical Federated learning in the FATE framework [slides] 丁宾宾
  • 2023-05-05   How to Exploit Hyperspherical Embeddings for Out-of-Distribution Detection? [slides] 郑宇祥
  • 2023-05-11   Generating High Fidelity Data From Low-density Regions using Diffusion Models? [slides] 王烨文
  • 2023-05-19   Rethinking Image Aesthetics Assessment: Models, Datasets and Benchmarks [slides] 高远航
  • 2023-05-19   Contrastive Learning for Compact Single Image Dehazing [slides] 徐峥岩
  • 2023-05-19   Generative Diffusion Prior for Unified Image Restoration and Enhancement [slides] 李雅超
  • 2023-05-11   Dual Student Networks for Data-Free Model Stealing [slides] 万文海
  • 2023-05-26   Consistency-based Active Learning for Object Detection [slides] 张婧炜
  • 2023-05-26   TC3KD: Knowledge distillation via teacher-student cooperative curriculum customization [slides] 孙悦
  • 2023-05-26   Visual Attention Network [slides] 仇梦雨
  • 2023-06-02   MarginMatch: Improving Semi-Supervised Learning with Pseudo-Margins [slides] 范恒博
  • 2023-06-02   Causal Imitation Learning Via Inverse Reinforcement Learning [slides] 周立戎
  • 2023-06-02   Offline RL with No OOD Actions: In-Sample Learning via Implicit Value Regularization [slides] 罗钦文
  • 2023-06-16   ABC: Auxiliary Balanced Classifier for Class-imbalanced Semi-supervised Learning [slides] 牛纪龙
  • 2023-06-16   Exploring Structured Semantic Prior for Multi Label Recognition with Incomplete Labels [slides] 陈佳瑶
  • 2023-06-16   InPL: Pseudo-labeling the Inliers First for Imbalanced Semi-supervised Learning [slides] 周傅毅楠
  • 2023-06-30   On Multi-Domain Long-Tailed Recognition, Imbalanced Domain Generalization and Beyond [slides] 王蕾
  • 2023-06-30   Long-tailed Visual Recognition via Gaussian Clouded Logit Adjustment [slides] 陈汐程
  • 2023-07-14   Transfer NAS with Meta-learned Bayesian Surrogates [slides] 刘昊哲
  • 2023-07-14   Towards Addressing Label Skews In One-shot Federated Learning [slides] 葛泽庆
  • 2023-07-21   No One Left Behind: Improving the Worst Categories in Long-Tailed Learning [slides] 陈傲
  • 2023-07-21   Active Finetuning: Exploiting Annotation Budget in the Pretraining-Finetuning Paradigm [slides] 熊淑贤
  • 2023-07-21   Bootstrapping the Relationship Between Images and Their Clean and Noisy Labels [slides] 肖家豪

    • GAME 2 LOGIN

  • 2022-09-16   Open-Sampling: Exploring Out-of-Distribution Data for Re-balancing Long-Tailed Datasets. [slides] 宗辰辰
  • 2022-09-16   Understanding and Improving Early Stopping for Learning with Noisy Labels. [slides] 邹博士
  • 2022-09-23   Large Loss Matters in Weakly Supervised Multi-Label Classification. [slides] 陈佳瑶
  • 2022-09-23   Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network. [slides] 郭洪涛
  • 2022-09-23   Regret Minimization Experience Replay in Off-Policy Reinforcement Learning. [slides] 魏晓晨
  • 2022-09-30   Motion-aware Contrastive Video Representation Learning via Foreground-background Merging. [slides] 胡刚
  • 2022-09-30   Uncertainty-aware Learning Against Label Noise on Imbalanced Datasets. [slides] 王蕾
  • 2022-09-30   A Brief Introduction to Machine Unlearning. [slides] 杨鹏辉
  • 2022-10-07   CoMatch: Semi-supervised Learning with Contrastive Graph Regularization. [slides] 曹正涛
  • 2022-10-07   Improving Out-of-Distribution Robustness via Selective Augmentation. [slides] 万文海
  • 2022-10-07   Boosting Multi-Label Image Classification with Complementary Parallel Self-Distillation. [slides] 肖家豪
  • 2022-10-13   L1 Regression with Lewis Weights Subsampling. [slides] 唐英鹏
  • 2022-10-13   Parrot: Data-Driven Behavioral Priors for Reinforcement Learning. [slides] 罗钦文
  • 2022-10-13   Two ways to improve FixMatch Performance From Pseudo-Labels Balancing to Dynamic Threshold. [slides] 范恒博
  • 2022-10-21   Class-Imbalanced Semi-Supervised Learning with Adaptive Thresholding. [slides] 谢明昆
  • 2022-10-21   Representational Continuity for Unsupervised Continual Learning. [slides] 郑宇祥
  • 2022-10-21   Option Discovery Using Deep Skill Chaining. [slides] 王烨文
  • 2022-10-28   Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning. [slides] 周立戎
  • 2022-10-28   On Learning Contrastive Representations for Learning with Noisy Labels. [slides] 赵世佶
  • 2022-11-04   A Brief Introduction to Data Poisoning and Backdoor Attack. [slides] 杨鹏辉
  • 2022-11-04   Adversarial Graph Contrastive Learning with Information Regularization. [slides] 李鑫杰
  • 2022-11-04   SCAFFOLD: Stochastic Controlled Averaging for Federated Learning. [gate.io app] 丁宾宾
  • 2022-11-11   Discovering and forecasting extreme events via active learning in neural operators. [slides] 庞懿闻
  • 2022-11-11   A Policy-Guided Imitation Approach for Offline Reinforcement Learning. [slides] 罗钦文
  • 2022-11-18   A Unified Hard-Constraint Framework for Solving Geometrically Complex PDEs. [slides] 单彬
  • 2022-11-25   RvS: What is Essential for Offline RL via Supervised Learning? [slides] 魏晓晨
  • 2022-11-25   Active Exploration For Inverse Reinforcement Learning [slides] 王烨文
  • 2022-12-02   Offline RL Policies Should be Trained to be Adaptive. [slides] 罗钦文
  • 2022-12-02   Adversarial Masking for Self-Supervised Learning. [slides] 肖家豪
  • 2022-12-02   Can multi-label classification networks know what they don’t know? [slides] 陈傲
  • 2022-12-09   Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning [slides] 宗辰辰
  • 2022-12-09   Active Learning by Feature Mixing [slides] 胡刚
  • 2022-12-09   Label Structure Preserving Contrastive Embedding for Multi-Label Learning with Missing Labels [slides] 范恒博
  • 2022-12-30   VL-LTR: Learning Class-wise Visual-Linguistic Representation for Long-Tailed Visual Recognition [slides] 陈佳瑶
  • 2022-12-30   Beyond neural scaling laws: beating power law scaling via data pruning [slides] 万文海

    • UNIGOLDCOIN EXCHANGES

  • 2022-02-28   Agreement-Discrepancy-Selection: Active Learning with Progressive Distribution Alignment. [slides] 宗辰辰
  • 2022-02-28   Self-paced Contrastive Learning with Hybrid Memory for Domain Adaptive Object Re-ID [slides] 郭洪涛
  • 2022-02-28   Offline Reinforcement Learning With In-Sample Q-Learning. [slides] 邹博士
  • 2022-03-07   SimGRACE: A Simple Framework for Graph Contrastive Learning without Data Augmentation. [slides] 李鑫杰
  • 2022-03-07   Multi-Objective Interpolation Training for Robustness to Label Noise. [slides] 万文海
  • 2022-03-07   Swin Transformer: Hierarchical Vision Transformer using Shifted Windows. [slides] 胡刚
  • 2022-03-14   Transferable Attention for Domain Adaptation. [slides] 曹正涛
  • 2022-03-14   PlayVirtual: Augmenting Cycle-Consistent Virtual Trajectories for Reinforcement Learning. [slides] 何花
  • 2022-03-21   Prioritized Experience Replay. [slides] 魏晓晨
  • 2022-03-21   Focal and Global Knowledge Distillation for Detectors. [slides] 王蕾
  • 2022-03-21   Adaptive Fourier Neural Operators: Efficient Token Mixers for Transformers. [slides] 庞懿闻
  • 2022-03-28   Exploring Balanced Feature Spaces for Representation Learning. [slides] 章青衡
  • 2022-03-28   Multi-Label Learning from Single Positive Labels. [slides] 陈佳瑶
  • 2022-03-28   Undistillable: Making A Nasty Teacher that CANNOT Teach Students. [slides] 杨鹏辉
  • 2022-03-28   Flooding-X: Improving BERT’s Resistance to Adversarial Attacks via Loss-Restricted Fine-Tuning. [slides] 杨鹏辉
  • 2022-04-11   Visual Attention Consistency under Image Transforms for Multi-Label Image Classification. [slides] 谢明昆
  • 2022-04-11   TrustAL: Trustworthy Active Learning using Knowledge Distillation. [slides] 唐英鹏
  • 2022-04-18   Off-Policy Deep Reinforcement Learning without Exploration. [slides] 王烨文
  • 2022-04-18   Experience Replay with Likelihood-free Improve Weights. [gate.io app] 魏晓晨
  • 2022-04-18   General Multi-Label Image Classification . [slides] 肖家豪
  • 2022-04-25   Exploiting Class Activation Value For Partial-Label Learning. [slides] 陈傲
  • 2022-04-25   Boosting Active Learning via Improving Test Performance. [slides] 郭洪涛
  • 2022-04-25   HyperDQN: A Randomized Exploration Method for Deep Reinforcement Learning. [slides] 罗钦文
  • 2022-05-09   SimMatch: Semi-supervised Learning with Similarity Matching. [slides] 范恒博
  • 2022-05-09   Event Transformer. [slides] 胡刚
  • 2022-05-09   Are Graph Augmentations Necessary? Simple Contrastive Learning for Recommendation. [slides] 李鑫杰
  • 2022-05-23   Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. [slides] 杨鹏辉
  • 2022-05-23   Decoupled Knowledge Distillation. [slides] 杨鹏辉
  • 2022-05-23   Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation. [slides] 曹正涛
  • 2022-05-23   UNICON Combating Label Noise Through Uniform Selection and Contrastive Learning. [slides] 陈佳瑶
  • 2022-05-30   Deep Neural Networks Motivated by Partial Differential Equations. [slides] 庞懿闻
  • 2022-05-30   Solving Inefficiency of Self-supervised Representation Learning. [slides] 王蕾
  • 2022-06-06   Revisiting Consistency Regularization for Deep Partial Label Learning. [slides] 邹博士
  • 2022-06-06   Learning to Simulate Self-Driven Particles System with Coordinated Policy Optimization. [slides] 何花
  • 2022-06-06   Contrastively Enforcing Distinctiveness for Multi-Label Classification. [slides] 万文海
  • 2022-06-13   Self Supervision to Distillation for Long-Tailed Visual Recognition. [slides] 章青衡
  • 2022-06-13   Physics-Coupled Spatio-Temporal Active Learning for Dynamical Systems. [slides] 单彬
  • 2022-06-13   Conditional DETR for Fast Training Convergence. [slides] 张诗凡
  • 2022-06-20   Open Set Learning with Counterfactual Images. [slides] 谢明昆
  • 2022-06-20   Pure Noise to the Rescue of Insufficient Data: Improving Imbalanced Classification by Training on Random Noise Images. [slides] 唐英鹏
  • 2022-06-20   Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks. [slides] 黄振
  • 2022-06-27   Learning Transferable Visual Models From Natural Language Supervision. [slides] 孙峰
  • 2022-06-27   Mosaicking to Distill: Knowledge Distillation from Out-of-Domain Data. [slides] 宗辰辰
  • 2022-06-27   Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstruction. [slides] 施皓晨
  • 2022-07-04   Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group Discrimination. [slides] 李鑫杰
  • 2022-07-04   Class2Simi: A Noise Reduction Perspective on Learning with Noisy Labels. [slides] 郭洪涛
  • 2022-07-04   Multi-label Iterated Learning for Image Classification with Label Ambiguity. [slides] 陈佳瑶
  • 2022-07-18   Continual Learning Through Synaptic Intelligence. [slides] 吴宇凡
  • 2022-07-18   DisCor: Corrective Feedback in Reinforcement Learning via Distribution Correction. [slides] 魏晓晨
  • 2022-07-18   E-CIR: Event-Enhanced Continuous Intensity Recovery. [slides] 胡刚

    • SHIBA WATCH 交易所

  • 2021-08-13   Decoupling Representation and Classifier for Long-Tailed Recognition. [slides] 刘耀
  • 2021-08-13   Humble Teachers Teach Better Students for Semi-Supervised Object Detection. [slides] 罗世发
  • 2021-08-21   Self-Tuning for Data-Efficient Deep Learning. [slides] 侍野
  • 2021-08-21   Relation-aware Graph Attention Model With Adaptive Self-adversarial Training. [slides] 韦梦龙
  • 2021-08-29   Towards Understanding the Behaviors of Optimal Deep Active Learning Algorithms. [slides] 唐英鹏
  • 2021-08-29   What Makes for Good View for Contrastive Learning? [slides] 宗辰辰
  • 2021-09-03   Invariant Information Clustering for Unsupervised Image Classification and Segmentation. [slides] 谢明昆
  • 2021-09-03   Two Articles about Label Smoothing and Knowledge Distillation. [slides] 杨鹏辉
  • 2021-09-12   Implementation Matters in Deep Policy Gradients: A Case Study on PPO and TRPO. [slides] 邹博士
  • 2021-09-12   A brief introduction to imitation learning. [slides] 魏晓晨
  • 2021-09-17   Adversarial Imitation Learning with Trajectorial Augmentation and Correction. [slides] 何花
  • 2021-09-17   FixBi: Bridging Domain Spaces for Unsupervised Domain Adaptation. [slides] 曹正涛
  • 2021-09-17   Go-Explore: a New Approach for Hard-Exploration Problems. [slides] 黄振
  • 2021-09-24   GCC: Graph Contrastive Learning for Graph Neural Network Pre-Training. [slides] 孙峰
  • 2021-09-24   Active Learning for Noisy Data Streams Using Weak and Strong Labelers. [slides] 吴宇凡
  • 2021-09-24   Learning nonlinear operators via DeepONet based on the universal approximation theorem of operators. [slides] 庞懿闻
  • 2021-10-05   Contrastive Coding for Active Learning under Class Distribution Mismatch. [slides] 宁鲲鹏
  • 2021-10-05   Be Your Own Teacher：Improve the Performance of Convolutional Neural Networks via Self Distillation. [slides] 罗世发
  • 2021-10-05   Decoupling Representation and Classifier for Long-Tailed Recognition. [slides] 刘耀
  • 2021-10-11   Active Image Synthesis for Efficient Labeling. [slides] 唐英鹏
  • 2021-10-11   Multi-view Feature Augmentation with Adaptive Class Activation Mapping. [slides] 韦梦龙
  • 2021-10-11   Robust and Generalizable Visual Representation Learning via Random Convolutions. [slides] 侍野
  • 2021-10-18   A Baseline for Detecting Misclassified and Out-of-Distribution Examples In Neural Networks. [slides] 周慧
  • 2021-10-18   SOTA of Two Technical Routes in Model Calibration: Gaussian Process Calibration & I-Max Binning. [slides] 杨鹏辉
  • 2021-10-18   Learning When and Where to Zoom with Deep Reinforcement Learning. [slides] 施皓晨
  • 2021-10-25   Rethinking data efficiency in reinforcement learning. [slides] 魏晓晨
  • 2021-10-25   Long-Tailed Visual Recognition. [slides] 魏晓晨
  • 2021-11-01   Tackling the long-tailed problem from the perspective of knowledge distillation. [slides] 郭洪涛
  • 2021-11-01   HOTR: End-to-End Human-Object Interaction Detection with Transformers. [slides] 张诗凡
  • 2021-11-01   Two Articles about Knowledge Distillation and Active Learning. [slides] 宗辰辰
  • 2021-11-08   An Introduction of Batch Reinforcement Learning . [slides] 邹博士
  • 2021-11-08   All Labels Are Not Created Equal: Enhancing Semi-supervision via Label Grouping and Co-training. [slides] 侍野
  • 2021-11-19   Decision Transformer: Reinforcement Learning via Sequence Modeling. [slides] 黄振
  • 2021-11-19   Recall Traces: Backtracking Models for Efficient Reinforcement Learning. [slides] 何花
  • 2021-11-19   BatchBALD: Efficient and Diverse Batch Acquisition for Deep Bayesian Active Learning. [slides] 李鑫杰
  • 2021-11-25   Query2Label: A Simple Transformer Way to Multi-Label Classification. [slides] 陈佳瑶
  • 2021-11-25   Deep Feature Interpolation. [slides] 宁鲲鹏
  • 2021-11-25   Neural operator Learning maps between function spaces. [slides] 庞懿闻
  • 2021-12-03   Data-Uncertainty Guided Multi-Phase Learning for Semi-Supervised Object Detection. [slides] 王蕾
  • 2021-12-03   Learning without Forgetting. [slides] 吴宇凡
  • 2021-12-03   Contrastive Label Disambiguation for Partial Label Learning. [slides] 谢明昆
  • 2021-12-10   Distilling Holistic Knowledge with Graph Neural Networks. [slides] 杨鹏辉
  • 2021-12-10   Search to Distill: Pearls are Everywhere but not the Eyes. [slides] 刘耀
  • 2021-12-10   Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal Effect. [slides] 章青衡
  • 2021-12-17   Prototypical Cross-domain Self-supervised Learning for Few-shot Unsupervised Domain Adaptation. [slides] 曹正涛
  • 2021-12-17   NRGNN: Learning a Label Noise-Resistant Graph Neural Network on Sparsely and Noisily Labeled Graphs. [slides] 韦梦龙
  • 2021-12-17   Improving Calibration for Long-Tailed Recognition. [gate io] 万文海
  • 2021-12-31   When do Curricula Work? [slides] 唐英鹏
  • 2021-12-31   Two Articles about Loss function for long-tail distribution. [slides] 胡刚
  • 2022-01-07   Towards General and Efficient Active Learning. [slides] 郭洪涛
  • 2021-12-31   Model-Contrastive Federated Learning. [slides] 宗辰辰
  • 2021-12-31   MetaFormer is Actually What You Need for Vision. [slides] 施皓晨
  • 2021-12-31   Mining the Benefits of Two-stage and One-stage HOI Detection. [slides] 张诗凡
  • 2021-12-31   Offline RL: Benchmark and a new algorithm. [slides] 魏晓晨

    • SIMPSON FINANCE

  • 2021-03-17   Few-Shot Adversarial Domain Adaptation. [slides] 曹正涛
  • 2021-03-17   FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence. [slides] 何花
  • 2021-03-17   Mastering Complex Control in MOBA Games with Deep Reinforcement Learning. [slides] 黄振
  • 2021-03-24   Class-Balanced Loss Based on Effective Number of Samples. [slides] 孙峰
  • 2021-03-24   Learning Parameters and Constitutive Relationships with Physics Informed Deep Neural Networks. [slides] 庞懿闻
  • 2021-03-24   NLNL: Negative Learning for Noisy Labels. [slides] 吴宇凡
  • 2021-03-31   Model-Free Episodic Control. & Episodic Memory Deep Q-Networks. & Episodic Reinforcement Learning with Associative Memory. [slides] 宁鲲鹏
  • 2021-03-31   VaB-AL：Incorporating Class Imbalance and Difficulty with Variational Bayes for Active Learning. [slides] 罗世发
  • 2021-04-07   Multi-class classification without Multi-class Labels. [slides] 周慧
  • 2021-04-07   Learning from Crowds by Modeling Common Confusions. [slides] 侍野
  • 2021-04-07   Fair Generative Modeling via Weak Supervision. [slides] 韦梦龙
  • 2021-04-14   A Brief Introduction of Model Reuse. [slides] 唐英鹏
  • 2021-04-14   Unsupervised Domain Adaptation Via Structured Prediction Based Selective Pseudo-Labeling. [slides] 曹正涛
  • 2021-04-14   Multiple Instance Active Learning for Object Detection. [slides] 施皓晨
  • 2021-04-21   Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variables. [slides] 何花
  • 2021-04-21   Datasets Condensation with gradient Matching. [slides] 宁鲲鹏
  • 2021-04-29   Rethinking the Value of Labels for Improving Class-Imbalanced Learning. [slides] 吴宇凡
  • 2021-04-29   Sequence Level Training with Recurrent Neural Networks. [slides] 黄振
  • 2021-05-12   Adaptive activation functions accelerate convergence in deep and physics-informed neural networks. [slides] 庞懿闻
  • 2021-05-12   Learning Representations for Time Series Clustering. [slides] 罗世发
  • 2021-05-19   Friendly Adversarial Training: Attacks Which Do Not Kill Training Make Adversarial Learning Stronger. [slides] 刘耀
  • 2021-05-19   Graph Random Neural Networks for Semi-Supervised Learning on Graphs. [slides] 韦梦龙
  • 2021-05-19   Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise. [slides] 侍野
  • 2021-05-26   Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning. [slides] 周慧
  • 2021-06-02   Federated Machine Learning: Concept and Applications. [slides] 唐英鹏
  • 2021-06-02   Learning Imbalanced Datasets with Label-Distribution-Aware Margin Loss. [slides] 谢明昆
  • 2021-06-02   SMAPGAN: Generative Adversarial Network-Based Semi-Supervised Styled Map Tile Generation Method. [slides] 施皓晨
  • 2021-06-09   Diversity is all you need :Learning skills without a reward function. [slides] 何花
  • 2021-06-09   Hierarchical Reinforcement Learning with Advantage-Based Auxiliary Rewards. [slides] 黄振
  • 2021-06-09   Implicit Semantic Data Augmentation for Deep Networks. [slides] 曹正涛
  • 2021-06-16   Contrastive Learning with Stronger Augmentations. [slides] 孙峰
  • 2021-06-16   Noise-resistant Deep Metric Learning with Ranking-based Instance Selection. [slides] 吴宇凡
  • 2021-06-16   A High-Efficient Hybrid Physics-Informed Neural Networks Based on Convolutional Neural Network. [slides] 庞懿闻
  • 2021-06-23   Active Learning for Video Classification. [slides] 宁鲲鹏
  • 2021-06-23   Beyond Synthetic Noise: Deep Learning on Controlled Noisy Labels. [slides] 刘耀
  • 2021-06-23   Putting An End to End-to-End: Gradient-Isolated Learning of Representations. [slides] 罗世发
  • 2021-06-30   Normalized Loss Functions for Deep Learning with Noisy Labels. [slides] 侍野
  • 2021-06-30   UAG: Uncertainty-aware Attention Graph Neural Network for Defending Adversarial Attacks. [slides] 韦梦龙
  • 2021-06-30   Barlow twins: self-supervised learning via redundancy reduction. [slides] 周慧
  • 2021-06-30   Barlow twins: self-supervised learning via redundancy reduction. [slides] 周慧
  • 2021-07-07   Asymmetric Tri-training for Unsupervised Domain Adaptation. [slides] 曹正涛
  • 2021-07-07   Active Testing: Sample–Efficient Model Evaluation. [slides] 唐英鹏
  • 2021-07-07   SemiCDNet: A Semisupervised Convolutional Neural Network for Change Detection in High Resolution Remote-Sensing Images. [slides] 施皓晨
  • 2021-07-14   An Unbiased Risk Estimator for Learning with Augmented Class. [slides] 谢明昆
  • 2021-07-14   SMIRL: Surprise Minimizing Reinforcement Learning In Unstable Environments. [slides] 黄振
  • 2021-07-14   High-dimensional continuous control using generalized advantage estimation. [slides] 何花
  • 2021-07-20   Understanding the Behaviour of Contrastive Loss. [slides] 吴宇凡
  • 2021-07-20   MentorNet: Learning Data-Driven Curriculum for Very Deep Neural Networks on Corrupted Labels. [slides] 孙峰
  • 2021-07-20   B-PINNs: Bayesian physics-informed neural networks for forward and inverse PDE problems with noisy data. [slides] 庞懿闻

    • BAZOOKATOKEN 交易所

  • 2020-09-02   State-Relabeling Adversarial Active Learning. [slides] 刘耀
  • 2020-09-02   Semi-Supervised Learning from Crowds Using Deep Generative Model. [slides] 侍野
  • 2020-09-10   Active Generative Adversarial Network for Image Classification. [slides] 周慧
  • 2020-09-10   Hierarchical Multi-Label Classification Networks. [slides] 韦梦龙
  • 2020-09-17   Hierarchical Imitation and Reinforcement Learning. [slides] 黄文宇
  • 2020-09-17   Learning Loss for Active Learning. [slides] 罗世发
  • 2020-09-24   A Two-Step Computation of the Exact GAN Wasserstein Distance. [slides] 唐英鹏
  • 2020-09-24   Learning to Reweight Examples for Robust Deep Learning. [slides] 谢明昆
  • 2020-10-15   Bootstrap Your Own Latent A New Approach to Self-Supervised Learning. [slides] 潘杰
  • 2020-10-15   Learning How to Active Learn by Dreaming. [slides] 何花
  • 2020-10-22   Deep Discriminative CNN with Temporal Ensembling for Ambiguously-Labeled Image Classification. [slides] 孙峰
  • 2020-10-22   Are Labels Required for Improving Adversarial Robustness? [slides] 宗辰辰
  • 2020-10-30   O2U-Net: A Simple Noisy Label Detection Approach for Deep Neural Networks. [slides] 刘耀
  • 2020-10-30   A Cost-sensitive Active Learning for Imbalance Data with Uncertainty and Diversity Combination. [slides] 罗世发
  • 2020-11-06   AUGMIX:A Simple Data Processing Method to Improve Robustness And Uncertainty. [slides] 周慧
  • 2020-11-06   Learning Discrete Structures for Graph Neural Networks. [slides] 韦梦龙
  • 2020-11-13   Maximum-Entropy Adversarial Data Augmentation for Improved Generalization and Robustness. [slides] 李国翔
  • 2020-11-13   Asking the Right Questions to the RightUsers: Active Learning with Imperfect Oracles. [slides] 黄文宇
  • 2020-11-20   Provably Consistent Partial-Label Learning. [slides] 谢明昆
  • 2020-11-20   Deep Self-Learning From Noisy Labels. [slides] 侍野
  • 2020-11-27   Self-Paced Robust Learning for Leveraging Clean Labels in Noisy Data. [slides] 何花
  • 2020-11-27   An empirical study of example forgetting during deep neural network learning. [slides] 宁鲲鹏
  • 2020-11-27   On Calibration of Modern Neural Networks. [slides] 孙峰
  • 2020-12-04   Data Valuation Using Reinforcement Learning. [slides] 唐英鹏
  • 2020-12-04   Instance Credibility Inference for Few-Shot Learning. [slides] 吴宇凡
  • 2020-12-04   Practical No-box Adversarial Attacks against DNNs. [slides] 宗辰辰
  • 2020-12-11   Knowledge Distillation with Adversarial Samples Supporting Decision Boundary. [slides] 宁鲲鹏
  • 2020-12-18   Regularizing Discriminative Capability of CGANs for Semi-Supervised Generative Learning. [slides] 韦梦龙
  • 2020-12-18   Unsupervised Representation Learning by Invariance Propagation. [slides] 侍野
  • 2020-12-18   Supervised Contrastive Learning. [slides] 罗世发
  • 2020-12-25   Learning from noisy labels & Reinforcement Learning. [slides] 宁鲲鹏
  • 2020-12-25   Triple Generative Adversarial Nets. [slides] 曹正涛
  • 2020-12-25   Conditional Neural Processes & Neural Processes. [slides] 李国翔
  • 2021-01-07   Data Cleansing for Models Trained with SGD. [slides] 潘杰
  • 2021-01-07   Learning Representations in Model-Free Hierarchical Reinforcement Learning. [slides] 黄振

    • METAHERO UNIVERSE 交易所

  • 2020-05-20   Using Active Relocation to Aid Reinforcement Learning. [slides] 宁鲲鹏
  • 2020-05-20   Consensus-Driven Propagation in Massive Unlabeled Data for Face Recognition. [slides] 刘耀
  • 2020-05-27   Deep Learning from Crowds [slides] 侍野
  • 2020-05-27   CNN-RNN: A Unified Framework for Multi-label Image Classification. [slides] 韦梦龙
  • 2020-05-27   SoQal: Selective Oracle Questioning in Active Learning. [slides] 周慧
  • 2020-06-03   Learning with Class-Conditional Random Label Noise. [slides] 谢明昆
  • 2020-06-03   Human-Interactive Subgoal Supervision for Efficient Inverse Reinforcement Learning. [slides] 黄文宇
  • 2020-06-10   Active Imitation Learning with Noisy Guidance. [slides] 李国翔
  • 2020-06-10   Data Shapley: Equitable Valuation of Data for Machine Learning. [slides] 潘杰
  • 2020-06-17   Deep Active Learning with a Neural Architecture Search. [slides] 唐英鹏
  • 2020-06-17   Universal Domain Adaptation. [slides] 孙峰
  • 2020-06-24   Self-Supervised Exploration via Disagreement. [slides] 宁鲲鹏
  • 2020-06-24   Confident Learning: Estimating Uncertainty in Dataset Labels. [slides] 刘耀
  • 2020-07-01   MEGAN: A Generative Adversarial Network for Multi-View Network Embedding. [slides] 韦梦龙
  • 2020-07-01   DIVIDEMIX: Learning with Noisy Labels as Semi-supervised Learning. [slides] 侍野
  • 2020-07-08   Practical applications of metric space magnitude and weighting vectors. [slides] 潘杰
  • 2020-07-08   Adversarial Imitation Learning from State-only Demonstrations. [slides] 黄文宇
  • 2020-07-08   Generate To Adapt: Aligning Domains using Generative Adversarial Networks. [slides] 罗世发
  • 2020-07-15   Adaptive Region-Based Active Learning. [slides] 李国翔
  • 2020-07-15   Bounding Uncertainty for Active Batch Selection. [slides] 周慧
  • 2020-07-22   On Reinforcement Learning for Full-Length Game of StarCraft. [slides] 宁鲲鹏
  • 2020-07-22   Pick-and-Learn: Automatic Quality Evaluation for Noisy-Labeled Image Segmentation. [slides] 刘耀
  • 2020-07-22   Empirical Studies of Active Learning. [slides] 唐英鹏
  • 2020-07-29   Learning from Complementary Labels. [slides] 谢明昆
  • 2020-07-29   Fine-tuning Convolutional Neural Networks for Biomedical Image Analysis: Actively and Incrementally. [slides] 孙峰
  • 2020-08-05   Unsupervised Data Augmentation For Consistency Training. [slides] 侍野
  • 2020-08-05   Maximum Classifier Discrepancy for Unsupervised Domain Adaptation. [slides] 韦梦龙
  • 2020-08-05   Consistency-based Semi-supervised ActiveLearning: Towards Minimizing Labeling Cost. [slides] 周慧
  • 2020-08-14   Understanding Goal-Oriented Active Learning via Influence Functions. [slides] 李国翔
  • 2020-08-14   On Deep Unsupervised Active Learning. [slides] 罗世发
  • 2020-08-19   Learning with Biased Complementary Labels. [slides] 谢明昆
  • 2020-08-19   Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting. [slides] 潘杰
  • 2020-08-26   Continuously Indexd Domain Adaptation. [slides] 孙峰
  • 2020-08-26   Adversarial Active Learning for Deep Networks:a Margin Based Approach. [slides] 宗辰辰

    • YEARN FINANCE 3 EXCHANGE

  • 2019-09-11   Active Learning from Peers [slides] 李国翔
  • 2019-09-11   Teacher Student Curriculum Learning [slides] 黄文宇
  • 2019-09-18   AlphaGo & AlphaGo Zero [slides] 宁鲲鹏
  • 2019-09-18   Characterizing and Avoiding Negative Transfer [slides] 潘杰
  • 2019-09-25   LaSO: Label-Set Operations networks for multi-label few-shot learning [slides] 谢明昆
  • 2019-09-25   Partial Adversarial Domain Adaptation [slides] 唐英鹏
  • 2019-10-09   Learning What and Where to Transfer [slides] 蔡佳佳
  • 2019-10-09   Mixed Membership Stochastic Blockmodels [slides] 刘朝阳
  • 2019-10-16   Learning To Teach [slides] 黄文宇
  • 2019-10-16   Learning to Sample: an Active Learning Framework [slides] 李国翔
  • 2019-10-23   Reinforcement Learning for Imperfect Demonstration [slides] 宁鲲鹏
  • 2019-10-23   Model-Based Active Exploration [slides] 潘杰
  • 2019-10-23   CornerNet: Detecting Objects as Paired Key points [slides] 刘耀
  • 2019-10-30   Active Domain Adaptation for Object Detection [slides] 唐英鹏
  • 2019-10-30   Deep Visual Domain Adaptation：A Survey [slides] 罗世发
  • 2019-11-06   Domain Adaptation for Semantic Segmentation with Maximum Squares Loss [slides] 蔡佳佳
  • 2019-11-06   Noise2Void -Learning Denoising from Single Noisy Images [slides] 侍野
  • 2019-11-06   Graph-based Semi-Supervised & Active Learning for Edge Flows [slides] 刘朝阳
  • 2019-11-13   MixMatch: A Holistic Approach to Semi-Supervised Learning [slides] 李国翔
  • 2019-11-13   Generative Adversarial Imitation Learning [slides] 黄文宇
  • 2019-11-20   Reinforcement Learning from Demonstration through Shaping [slides] 宁鲲鹏
  • 2019-11-20   When can unlabeled data improve the learning rate? [slides] 潘杰
  • 2019-11-20   Cross-stitchNetworksforMulti-taskLearning [slides] 周慧
  • 2019-11-27   Domain Intersection and Domain Difference [slides] 谢明昆
  • 2019-11-27   Open Set Domain Adaptation [slides] 孙峰
  • 2019-11-27   The Graph Neural Network Model [slides] 韦梦龙
  • 2019-12-04   Deep Active Learning: Unified and Principled Method for Query and Training [slides] 刘朝阳
  • 2019-12-04   CenterNet: Keypoint Triplets for Object Detection [slides] 刘耀
  • 2019-12-11   Discriminative Batch Mode Active Learning [slides] 宁鲲鹏
  • 2019-12-11   Learning Confidence for Out-of-Distribution Detection in Neural Networks [slides] 黄文宇
  • 2019-12-11   Bayesian Generative Active Deep Learning [slides] 罗世发
  • 2019-12-18   Reward Shaping via Meta-Learning [slides] 李国翔
  • 2019-12-18   A Simple yet Effective Baseline for Robust Deep Learning with Noisy Labels [slides] 侍野
  • 2019-12-25   Semi-supervised Partial Multi-Label Learning [slides] 谢明昆
  • 2019-12-25   Dual Attention Network for Scene Segmentation [slides] 韦梦龙
  • 2020-01-03   What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? [slides] 蔡佳佳
  • 2020-01-03   Active learning by Greedy Split and Label Exploration [slides] 周慧
  • 2020-01-08   Hierarchically Structured Meta-learning [slides] 李国翔
  • 2020-01-08   Hierarchically Deep Reinforcement Learning [slides] 黄文宇

    • TESE 交易所

  • 2019-07-15   Localization Aware Active Learning for Object Detection [slides] 宁鲲鹏
  • 2019-07-15   Training Region based Object Detectors with Online Hard Example Mining [slides] 李国翔
  • 2019-07-15   Learning and Data Selection in Big Datasets [slides] 黄文宇
  • 2019-07-18   Deep Active Learning [slides] 谢明昆
  • 2019-07-18   Model-Free Subset Selection - Part 1 [slides] 蔡佳佳
  • 2019-07-22   Model-Free Subset Selection - Part 2 [slides] 蔡佳佳
  • 2019-07-22   Active Search | Multi-Class Active Learning by Uncertainty Sampling with Diversity Maximizationy [slides] 潘杰
  • 2019-07-24   Submodularity in Data Subset Selection and Active Learning [slides] 潘杰
  • 2019-07-24   Model-Based Subset Selection in Reinforcement Learning [slides] 黄文宇
  • 2019-07-26   Representer Point Selection for Explaining Deep Neural Networks | Example selection for dictionary learning [slides] 黄文宇
  • 2019-07-26   Data Selection in Deep Learning [slides] 唐英鹏
  • 2019-07-29   Active Decision Boundary Annotation with Deep Generative Models [slides] 谢明昆
  • 2019-07-29   Uncertainty in Deep Learning - Part 1 [slides] 刘朝阳
  • 2019-07-31   Uncertainty in Deep Learning - Part 2 [slides] 刘朝阳
  • 2019-07-31   Active Learning in Semantic Segmentation [slides] 李国翔

    • PSTAKE STAKED BNB

  • 2019-03-21   Self PU Learning [slides] 蔡佳佳
  • 2019-03-21   Introduction to Graph Convolutional Networks [slides] 刘朝阳
  • 2019-03-28   Transferable Curriculum for Weakly-Supervised Domain Adaptation [slides] 唐英鹏
  • 2019-03-28   Reinforcement Learning with Human Teachers [slides] 黄文宇
  • 2019-04-04   Joint Transfer and Batch-mode Active Learning [slides] 潘杰
  • 2019-04-04   ASCENT: Active Supervision for Semi-supervised Learning [slides] 李国翔
  • 2019-04-18   Learning Deep Latent Spaces for Multi-Label Classification [slides] 谢明昆
  • 2019-04-18   Apprenticeship Learning via Inverse Reinforcement Learning [slides] 宁鲲鹏
  • 2019-04-25   OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations [slides] 蔡佳佳
  • 2019-04-25   Active Semi-Supervised Learning Using Sampling Theory for Graph Signals [slides] 刘朝阳
  • 2019-04-25   基于主动学习的标注云平台 [slides] 唐英鹏
  • 2019-05-09   Bayesian Inverse Reinforcement Learning [slides] 黄文宇
  • 2019-05-09   Uncertainty-Based Active Learning via Sparse Modeling for Image Classification [slides] 唐英鹏
  • 2019-05-16   Importance Weighted Transfer of Samples in Reinforcement Learning [slides] 潘杰
  • 2019-05-16   Learning Feature Engineering for Classification [slides] 李国翔
  • 2019-05-23   Multi Label Image Recognition with Graph Convolutional Networks [slides] 谢明昆
  • 2019-05-23   Active Learning for Reward Estimation in Inverse Reinforcement Learning [slides] 宁鲲鹏
  • 2019-05-30   Joint Selection and Classification for Active Query [slides] 蔡佳佳
  • 2019-05-30   Bayesian graph convolutional neural networks for semi supervised classification [slides] 刘朝阳
  • 2019-06-06   ActiveLink: Deep Active Learning for Link Prediction in Knowledge Graphs [slides] 唐英鹏
  • 2019-06-06   Interactively Shaping Agents via Human Reinforcement [slides] 黄文宇
  • 2019-06-13   On Discriminative Learning of Prediction Uncertainty [slides] 潘杰
  • 2019-06-13   Active Learning for DNNs [slides] 李国翔
  • 2019-06-20   Variational Adversarial Active Learning [slides] 谢明昆
  • 2019-06-20   Rapid Performance Gain through Active Model Reuse [slides] 蔡佳佳
  • 2019-07-04   Deep Reinforcement Learning from Human Preferences [slides] 宁鲲鹏
  • 2019-07-04   Semi-supervised Learning with Graph Gaussian Processes [slides] 刘朝阳
  • 2019-07-15   Localization-Aware Active Learning for Object Detection [slides] 宁鲲鹏
  • 2019-07-15   Training Region-based Object Detectors with Online Hard Example Mining [slides] 李国翔
  • 2019-07-15   Learning and Data Selection in Big Datasets [slides] 黄文宇

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  • 2018-09-10   Semi-Supervised AUC Optimization without Guessing Labels of Unlabeled Data [slides] 蔡佳佳
  • 2018-09-10   Feature-Induced Labeling Information Enrichment for Multi-Label Learning [slides] 吴志凡
  • 2018-09-17   Matrix Factorization for Recommendations [slides] 刘朝阳
  • 2018-09-17   Learning Active Learning from Data [slides] 唐英鹏
  • 2018-09-28   Human Guided Linear Regression with FeatureLevel Constraints [slides] 黄文宇
  • 2018-09-28   Deep Active Learning [slides] 谢明昆
  • 2018-10-08   Efficient PAC Learning from the Crowd [slides] 潘杰
  • 2018-10-15   Discovering General-purpose Active Learning Strategies [slides] 蔡佳佳
  • 2018-10-22   Social Recommendation [slides] 刘朝阳
  • 2018-10-22   Meta-Learning Transferable Active Learning Policies by Deep Reinforcement Learning [slides] 李国翔
  • 2018-10-29   NGUARD: A Game Bot Detection Framework for NetEase MMORPGs [slides] 唐英鹏
  • 2018-10-29   A Low-Cost Ethics Shaping Approach for Designing Reinforcement Learning Agents [slides] 黄文宇
  • 2018-10-29   signSGD with Majority Vote is Communication Efficient and Byzantine Fault Tolerant [slides] 赵嘉玮
  • 2018-11-05   Multi-target Unsupervised Domain Adaptation without Exactly Shared Categories [slides] 潘杰
  • 2018-11-05   Meta-Learning for Batch Mode Active Learning [slides] 谢明昆
  • 2018-11-12   Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks [slides] 李国翔
  • 2018-11-12   Meta-Learning for Batch Mode Active Learning [slides] 谢明昆
  • 2018-11-22   Deep Neural Network for Youtube Recommendations [slides] 蔡佳佳
  • 2018-11-22   Active Learning with Partial Feedback [slides] 吴志凡
  • 2018-11-26   Matching Networks for One Shot Learning [slides] 刘朝阳
  • 2018-11-26   ∆-encoder: an effective sample synthesis method for few-shot object recognition [slides] 唐英鹏
  • 2018-12-03   Transfer Learning via Learning to Transfer [slides] 潘杰
  • 2018-12-03   Label Noise Robust Generative Adversarial Networks [slides] 谢明昆
  • 2018-12-10   ACEPY: ACtive lEarning toolbox for PYthon [slides] 唐英鹏
  • 2018-12-10   Learning to learn by gradient descent by gradient descent [slides] 李国翔
  • 2018-12-20   Auto-WEKA: Combined Selection and Hyperparameter Optimization of Classification Algorithms [slides] 吴志凡
  • 2018-12-20   Active Learning by Learning [slides] 黄文宇
  • 2018-12-24   Beyond Filters: Compact Feature Map for Portable Deep Model [slides] 刘朝阳

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  • 2018-03-15   Cost-Effective Active Learning for Hierarchical Multi-Label Classification [slides] 颜逸凡
  • 2018-03-15   A new optimization method for ASPL [slides] 唐英鹏
  • 2018-03-15   The Application Of Active PU Learning In Content Based Image Retrieval [slides] 蔡佳佳
  • 2018-03-15   Open Set Recognition [slides] 刘朝阳
  • 2018-03-22   Cost-Effective Active Learning for Hierarchical Multi-Label Classification [slides] 颜逸凡
  • 2018-03-22   Semi-Supervised Classification Based on Classification from Positive and Unlabeled Data [slides] 蔡佳佳
  • 2018-03-22   EVT sparse representation binary SVM Nearest Neighbors Isolation Fores [slides] 刘朝阳
  • 2018-03-29   SPAL: 换用新的优化算法跑的实验 [slides] 唐英鹏
  • 2018-03-29   Learning Positive and Unlabeled Data [slides] 蔡佳佳
  • 2018-03-29   Label propagation manifold regularization & TED [slides] 刘朝阳
  • 2018-04-04   Deep Bayesian Active Learning [slides] 谢明昆
  • 2018-04-04   LP&EVT [slides] 刘朝阳
  • 2018-04-12   CCDM蝴蝶种类识别 [slides] 唐英鹏
  • 2018-04-19   Gaussian Process Active Learning [slides] 蔡佳佳
  • 2018-04-19   manifold regularization adaptive graph transductive experimental design active learning [slides] 刘朝阳
  • 2018-04-19   Transfer Learning with Active Queries from Source Domain [slides] 吴志凡
  • 2018-04-26   Outlier [slides] 刘朝阳
  • 2018-05-10   PU Learning for Matrix Completion [slides] 蔡佳佳
  • 2018-05-17   实验 [slides] 颜逸凡
  • 2018-05-17   Formulation for ERM [slides] 蔡佳佳
  • 2018-05-17   Low-Rank Representation Learning [slides] 刘朝阳
  • 2018-05-24   Label Propagation [slides] 蔡佳佳
  • 2018-05-24   Low-Rank-Based Feature Learning with Active Learning for Open-Category Classification [slides] 刘朝阳
  • 2018-05-31   Cost‐Effective Active Learning for Hierarchical Multi‐Label Classification [slides] 颜逸凡
  • 2018-05-31   Co-training实验 [slides] 唐英鹏
  • 2018-05-31   Active Positive Unlabeled Learning with Changeless U [slides] 蔡佳佳
  • 2018-05-31   验证利用LRR所得矩阵Z进行已知数据分类和新数据检测的可行性 [slides] 刘朝阳
  • 2018-05-31   Transfer Learning with Active Queries from Source Domain: Optimizing Without Relaxation [slides] 吴志凡
  • 2018-06-07   Cost‐Effective Active Learning for Hierarchical Multi‐Label Classification [slides] 颜逸凡
  • 2018-06-07   Co-training实验 [slides] 唐英鹏
  • 2018-06-07   实验验证数据分布影响 [slides] 蔡佳佳
  • 2018-06-07   MNIST实验 [slides] 刘朝阳
  • 2018-06-21   Cost‐Effective Active Learning for Hierarchical Multi‐Label Classification [slides] 颜逸凡
  • 2018-06-21   Co-training实验 [slides] 唐英鹏
  • 2018-06-21   Active PU Learning 实验 [slides] 蔡佳佳
  • 2018-06-21   Early Active Learning via Robust Representation and Structured Sparsity [slides] 刘朝阳
  • 2018-06-28   Cost‐Effective Active Learning for Hierarchical Multi‐Label Classification [slides] 颜逸凡
  • 2018-06-28   Active PU Learning 实验 [slides] 蔡佳佳
  • 2018-06-28   Early Active Learning via Robust Representation and Structured Sparsity [slides] 刘朝阳
  • 2018-07-05   Cost‐Effective Active Learning for Hierarchical Multi‐Label Classification 实验 [slides] 颜逸凡
  • 2018-07-05   GANs [slides] 谢明昆
  • 2018-07-05   SPAL实验 [slides] 唐英鹏
  • 2018-07-05   Active Learning via Robust Representation and Structured Sparsity 实验 [slides] 刘朝阳
  • 2018-07-26   Cost‐Effective Active Learning for Hierarchical Multi‐Label Classification [slides] 颜逸凡
  • 2018-07-26   Python 代码加密 & Self-Paced Active Learning 实验 [slides] 唐英鹏

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    BKRW EXCHANGES

    • Hierarchical active learning [slides] By:颜逸凡   2017-11-30
      Experiments on three datasets show that the performance may be improved when we discard some labels which have few relevant instances. And we take different costs of query into account. The results are not consistent in three datasets.

    • BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification [slides] [paper] By:颜逸凡
      In many applications, the set of class labels are organized in a hierarchical tree structure, with the leaf nodes as outputs and the internal nodes as clusters of outputs. This paper proposed a novel batch active selection criterion based on the label structure.

    GENIE AI EXCHANGES

    • Active self-pased learning: experiment [slides] By:唐英鹏   2017-11-20

    • Active self-pased learning: experiment [slides] By:唐英鹏   2017-11-13

    • 公式推导 [slides] By:唐英鹏   2017-10-20
      A trial to find some common points between SPL abd AL by formula derivation

    • 公式合并 [slides] By:唐英鹏   2017-10-13
      Combined the formulation of SPL and Querying Discriminative and Representative Samples for Batch Mode Active Learning.

    • Querying Discriminative and Representative Samples for Batch Mode Active Learning [slides] [paper] By:唐英鹏   2017-09-29
      This paper derive a novel form of upper bound for the true risk in the active learning setting; by minimizing this upper bound, they develop a practical batch mode active learning method. This method is shown to query the most informative samples while preserving the source distribution as much as possible. Finally I propose an ideal to combined this method to SPL.

    • Some ideas of combining Self-Paced learning and Active leanring [slides] By:唐英鹏   2017-09-23
      Summarize the work in the summer holiday

    • A theoretical understanding of self-paced learning [slides] [paper] By:唐英鹏
      A report of the first part of this paper which gives some theoretical understanding of self-paced learning, contribution including: find the "latent SPL object function" which demonstrate the Alternative optimization strategy (AOS) to optimize the SPL is equal to using the majorization minimization(MM) algorithm to optimize another function(called latent SPL object function).

    • SPLBoost: An Improved Robust Boosting Algorithm Based on Self-paced Learning [slides] [paper] By:唐英鹏
      A method to combine the self-paced learning and AdaBoost algorithm. They use self-paced learning regime to alleviate the effection of the noise data in the AdaBoost, more specifically, they set the weight of those samples which have a high loss(noise) to zero in order to suppressing their distractions.

    • Active Self-Paced Learning for Cost-Effective and Progressive Face Identification [slides] [paper] By:唐英鹏
      A paper combines the active learning and self-paced learning. This is the first work of these two methods. In their work, they use active learning to query those most uncertain samples and use self-paced learning to give the high-confidence samples pseudo labels. Several experiments demonstrate the effectiveness of their method.

    • Self-Paced Learning for Latent Variable Models [slides] [paper] By:唐英鹏
      This paper is the first time that the self-paced learning was proposed, report including the basic methods of the self-paced and several experiment results.

    GENEBANK TOKEN EXCHANGES

    • Active PU learning using MMD: Experiment [slides] By:蔡佳佳   2017-11-13
      手工构造二位高斯分布数据集上的实验

    • Active PU learning using MMD [slides] By:蔡佳佳   2017-10-30
      Construct selector using MMD and modify the cost function of original PU learning.

    • Formulation for PU Active Learning [slides] By:蔡佳佳   2017-10-20
      Formulate a selector using MMD for PU active learning.

    • Learning Classifiers from Only Positive and Unlabeled Data [slides] [paper] By:蔡佳佳   2017-09-29
      This paper found that a classifier trained on positive and unlabeled examples predicts probabilities that differ by only a constant factor from the true conditional probabilities of being positive.

    • Multi-label Ranking from Positive and Unlabeled Data [slides] [paper] By:蔡佳佳
      This paper examines the training of a multi-label classifier from data with incompletely assigned labels. They treat this problem as a multi-label PU ranking.

    • Active Learning from Positive and Unlabeled Data [slides] [paper] By:蔡佳佳
      This paper uses Bayes’ rule and density estimation to avoid the need to have a model of all classes for computing the uncertainty measure.

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    COOL20 LOGIN

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      ​ ​
    • ​ Large Scale Active learning: experiment ​ [slides] ​ By:刘朝阳   2017-12-18 ​
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      • ​
    • Large Scale Active Learning: Experiment [slides] By:刘朝阳   2017-12-04

    • linear scan与generative model 对比分析 [slides] By:刘朝阳   2017-11-20

    • 负Uncertainty的loss中引入中MMD生成模型的表现 [slides] By:刘朝阳   2017-11-13

    • 试验和问题 [slides] By:刘朝阳   2017-11-30
      验证在二分类模型训练完毕后，依据当前分类模型的Uncertainty是否能够指导生成模型生成的数据位于分类边界附近。

    • Large Scale Active Learning with Generative Model about Uncertainty Data [slides] By:刘朝阳   2017-10-20
      依据当前代的分类模型的Uncertainty知道训练生成模型，使得生成模型生成的数据分布在当前的分类界面附近。

    • A summary about Large-Scale Active Learning [slides] By:刘朝阳   2017-10-13
      寻找AL中的模型，模型满足这样的条件：在优化过程中核心步骤为最大内积和最小内积的形式，从而可以利用各种形式的位置敏感哈希的方法。

    • Discussion About Large Scale Active Learning [slides] By:刘朝阳   2017-09-29

    • A Review about Large-Scale Learning [slides] By:刘朝阳   2017-07-09

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    JCW 交易所

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    • ​ Word Embedding & CNN in NLP ​ [slides] ​ [paper] ​ By:赵嘉玮   2017-09-29 ​
      主要讲述词向量中的Word Embedding的概念，以及CNN网络在nlp领域中的应用,最后说明了最近的工作内容。 ​

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    • Hierarchical Attention Networks for Document Classification [slides] [paper] By:赵嘉玮   2017-09-29
      主要讲述文档级别的自然语言信息的提取任务，讲述关于该领域最新的一篇论文 Hierarchical Attention Networks for Document Classification

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    • Active Learning with Transfer Learning in Deep Neural Networks [slides] By:赵嘉玮   2017-12-04
      讲述了最近的工作进展，以及Active Learning 与 Deep Learning结合的发展方向

    • Fine-grained Image Retrieval [slides] [paper] By:赵嘉玮   2017-10-13
      介绍了细粒度图像识别问题，并对细粒度图像检索问题及解决方法做了介绍

    LAVASWAP EXCHANGE

    • Evolutionary Strategy to perform Batch-Mode Active Learning on Multi-Label Data [slides] By:颜逸凡
      This report instruduces a novel method that treat the active learning problem as a multi-objective problem, and it is solved by means of an evolutionary algorithm. The three objectives are informativeness,representativeness and diversity.

    POOCOIN EXCHANGES

    • Wasserstein GAN [slides] [paper1] [paper2] [paper3] By:刘朝阳

    • Generative Adversarial Text to Image Synthesis [slides] [paper] By:唐英鹏
      The first work can generate pictures according the text description by GAN. They combine the Condition-GAN and DCGAN and also give some improvements to complete this task. The second work stack two GANs to improve the performance of the fist work, they can generative more specific and high resolution pictures.

    • Unpaired Image-to-Image Translation using Cycle-Consistent Adversarial Networks [slides] [paper] By:蔡佳佳
      Style transformation using cycleGAN for unpaired images.

    • DCGAN [slides] [paper] By:谢明昆
      Introduce a set of GAN with generators and discriminators implemented by CNN.

    • Conditional Generative Adversarial Nets [slides] [paper] By:颜逸凡
      This report introduces the conditional version of GAN(generative adversarial nets). The extra information y is added on both the generator and discriminator. This model can work well when the extra information is class labels or data from different modality.

    • Learning to Generate Chairs, Tables and Cars with Convolutional Networks [slides] [paper] By:谢明昆
      Train a convolutional neural network to generate accurate images of objects from a high-level description: style, orientation, color and brightness, etc.

    • Generative Adversarial Nets [slides] [paper] By:刘朝阳

    • Variational Autoencoder [slides] [paper] By:蔡佳佳
      Introduction of an popular generative model, variational autoencoder(VAE).

    • Generative model and Discriminative model [slides] By:唐英鹏
      An introduction of the Generative model and Discriminative model, the Generative model modeling the joint probability of the data which the Discriminative model modeling the conditional distribution directly.

    • Neural Style Transfer [slides] [paper] By:谢明昆
      The Neural-Transfer, is an algorithm that takes as input a content-image, a style-image and return the content of the content-image as if it was ‘painted’ using the artistic style of the style-image

    • Convolutional Neural Networks [slides] [paper1] [paper2] By:谢明昆
      Introduce the basic layers of CNN, including convolutional layers and pooling layers and their operations. Visualize convolutional networks to insight how convolutional layers work.

    • Recurrent Neural Networks [slides] By:赵嘉玮
      First, the powerpoint introduces the basic knowledge of RNN, Recurrent Neural Networks, which contains the method of traning and examples of RNN in NLP. Second, it presents the LSTM Networks, which is improved from basic RNN model. In addition, it explains the framework and connection of LSTM.

    • Deep Belief Networks [slides] By:颜逸凡
      DBN(Deep Belief Nets) is a neural network composed of multiple layers of RBM.This report beliefly introduces the DBN.

    • 径向基函数神经网络模型与学习算法 [slides] By:刘朝阳   2017-07-05

    • Simple Introduction of Back Propagation Neuron Network [slides] By:唐英鹏
      Introduction of the famous Back-Propagation algorithm.

    • Multi-layer Perceptron [slides] By:蔡佳佳
      The simplest neural network, multi-layer perceptron(MLP).

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