conftrace_

Learning Types

56,253 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Self-Supervised Learning (8,965) Adversarial Learning (5,204) Unsupervised Learning (4,874) Transfer Learning (4,808) Weakly Supervised Learning (3,938) Contrastive Learning (3,748) Zero-Shot Learning (3,130) Semi-Supervised Learning (3,128) Reinforcement Learning (3,118) Multi-Task Learning (2,556) Evaluation (2,164) Continual Learning (2,107) Active Learning (1,983) Few-Shot Learning (1,840) Deep Learning (1,404) Online Learning (1,360) Multi-Armed Bandits (1,327) Multimodal Learning (1,289) Supervised Learning (986) Multi-Agent Systems (813) Uncertainty Quantification (805) Causal Inference (636) Robustness (576) Retrieval-Augmented Generation (565) Fine-Tuning (490) Ensemble Learning (482) In-Context Learning (439) Multi-Label Classification (430) Imitation Learning (387) Prompt Engineering (270) Multi-Lingual Learning (269) Distribution Shift (264) Reinforcement Learning from Human Feedback (209) Regularization (207) Exploration-Exploitation (203) Generative Models (200) Multi-Objective Optimization (185) Out-of-Distribution Detection (176) Sparse Learning (165) Sampling (150) Preference Learning (136) Offline Reinforcement Learning (130) Multi-Label Learning (128) Markov Decision Process (127) Neural Architecture Search (122) Multi-Instance Learning (121) Multi-View Learning (117) Robust Learning (110) Generative Model (110) Time Series (108) Large Language Models (104) Exploration (103) Hyperparameter Optimization (99) Machine Unlearning (95) Imbalanced Learning (93) Machine Translation (93) Multi-Class Classification (85) Differential Privacy (82) Time Series Analysis (71) Reasoning (70) Calibration (67) Structure Learning (66) Physics-Informed Learning (62) Class Imbalance (58) Model-Based RL (55) Interactive Learning (55) Multi-Domain Learning (47) Inverse Reinforcement Learning (46) Crowdsourcing (40) Off-Policy Learning (38) Label Noise (38) Noisy Label Learning (35) Offline RL (32) Attention (32) Evolutionary Algorithm (32) Decision Making (31) Policy Learning (30) Personalization (28) Low-Resource Learning (26) Collaborative Filtering (25) Self-Training (24) Sequential Modeling (24) Parameter Estimation (23) Survival Analysis (21) Machine Learning (20) Parameter-Efficient Fine-Tuning (20) Synthetic Data Generation (20) Annotation (18) Symbolic Regression (18) AutoML (16) Security (15) Multi-Source Learning (13) Distant Supervision (13) Text Generation (11) Distributional Reinforcement Learning (9) Sentiment Analysis (9) Multi-Hop Reasoning (9) Language Modeling (9) Code Generation (8) Multi-Object Tracking (8) Natural Language Inference (7) Chain-of-Thought (6) Question Answering (5)

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Papers (including subtopics)

Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training EMNLP 2020 Axioms for Learning from Pairwise Comparisons NeurIPS 2020 Background Data Resampling for Outlier-Aware Classification CVPR 2020 Background Matting: The World Is Your Green Screen CVPR 2020 Background Suppression Network for Weakly-Supervised Temporal Action Localization AAAI 2020 Backpropagating Linearly Improves Transferability of Adversarial Examples NeurIPS 2020 Back to the Future: Unsupervised Backprop-based Decoding for Counterfactual and Abductive Commonsense Reasoning EMNLP 2020 BAE: BERT-based Adversarial Examples for Text Classification EMNLP 2020 Balanced Joint Adversarial Training for Robust Intent Detection and Slot Filling COLING 2020 Balanced Off-Policy Evaluation in General Action Spaces AISTATS 2020 Balancing Learning Speed and Stability in Policy Gradient via Adaptive Exploration AISTATS 2020 Balancing Objectives in Counseling Conversations: Advancing Forwards or Looking Backwards ACL 2020 Bandit Linear Control NeurIPS 2020 Bandit Samplers for Training Graph Neural Networks NeurIPS 2020 Batch Decorrelation for Active Metric Learning IJCAI 2020 Batched Coarse Ranking in Multi-Armed Bandits NeurIPS 2020 BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning ICLR 2020 Batch Reinforcement Learning with Hyperparameter Gradients ICML 2020 Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation UAI 2020 Bayes-enhanced Lifelong Attention Networks for Sentiment Classification COLING 2020 Bayesian Adversarial Attack on Graph Neural Networks (Student Abstract) AAAI 2020 Bayesian Decision Process for Budget-efficient Crowdsourced Clustering IJCAI 2020 Bayesian Graph Neural Networks with Adaptive Connection Sampling ICML 2020 Bayesian joint state and parameter tracking in autoregressive models L4DC 2020 Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels NeurIPS 2020