Skip to content
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)

Papers per year

1
20
220
477
4,652
9,258
2000
'5
'10
'15
'20
'25

Papers (including subtopics)

On Nonlinear Spatial Filtering in Multichannel Speech Enhancement Interspeech 2019 On Open-Universe Causal Reasoning UAI 2019 On-Policy Robot Imitation Learning from a Converging Supervisor CoRL 2019 On Relating Explanations and Adversarial Examples NeurIPS 2019 On Robustness of Principal Component Regression NeurIPS 2019 On Robustness of Unsupervised Domain Adaptation for Speaker Recognition Interspeech 2019 On Robustness to Adversarial Examples and Polynomial Optimization NeurIPS 2019 On Sample Complexity Upper and Lower Bounds for Exact Ranking from Noisy Comparisons NeurIPS 2019 On Self Modulation for Generative Adversarial Networks ICLR 2019 On Stabilizing Generative Adversarial Training With Noise CVPR 2019 On Strength Adjustment for MCTS-Based Programs AAAI 2019 On Target Shift in Adversarial Domain Adaptation AISTATS 2019 On Testing of Uniform Samplers AAAI 2019 On the Connection Between Adversarial Robustness and Saliency Map Interpretability ICML 2019 On the Convergence and Robustness of Adversarial Training ICML 2019 On the Correctness and Sample Complexity of Inverse Reinforcement Learning NeurIPS 2019 On the Design of Black-Box Adversarial Examples by Leveraging Gradient-Free Optimization and Operator Splitting Method ICCV 2019 On the Design of Estimators for Bandit Off-Policy Evaluation ICML 2019 On the Dynamics of Gradient Descent for Autoencoders AISTATS 2019 On the Effectiveness of Low Frequency Perturbations IJCAI 2019 On the End-to-End Solution to Mandarin-English Code-Switching Speech Recognition Interspeech 2019 On the Estimation of Treatment Effect with Text Covariates IJCAI 2019 On the Global Optima of Kernelized Adversarial Representation Learning ICCV 2019 On the Hardness of Robust Classification NeurIPS 2019 On the Limits of Learning to Actively Learn Semantic Representations CoNLL 2019