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 the Existence of The Adversarial Bayes Classifier NeurIPS 2021 On-the-fly Rectification for Robust Large-Vocabulary Topic Inference ICML 2021 On the Generalization Properties of Adversarial Training AISTATS 2021 On the Generation of Medical Dialogs for COVID-19 ACL 2021 On the Hardness of Robust Classification JMLR 2021 On the Hidden Negative Transfer in Sequential Transfer Learning for Domain Adaptation from News to Tweets EACL 2021 On the Importance of Distractors for Few-Shot Classification ICCV 2021 On the Importance of Gradients for Detecting Distributional Shifts in the Wild NeurIPS 2021 On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning AISTATS 2021 On the Importance of Word Order Information in Cross-lingual Sequence Labeling AAAI 2021 On the Inductive Bias of Masked Language Modeling: From Statistical to Syntactic Dependencies NAACL 2021 On the Inherent Regularization Effects of Noise Injection During Training ICML 2021 On the Learning Dynamics of Semi-Supervised Training for ASR Interspeech 2021 On the Linear Convergence of Policy Gradient Methods for Finite MDPs AISTATS 2021 On the logistical difficulties and findings of Jopara Sentiment Analysis NAACL 2021 On the Model-Based Stochastic Value Gradient for Continuous Reinforcement Learning L4DC 2021 On the Power of Localized Perceptron for Label-Optimal Learning of Halfspaces with Adversarial Noise ICML 2021 On the Rate of Convergence of Regularized Learning in Games: From Bandits and Uncertainty to Optimism and Beyond NeurIPS 2021 On the Relation between Syntactic Divergence and Zero-Shot Performance EMNLP 2021 On the Relationship between Zipf’s Law of Abbreviation and Interfering Noise in Emergent Languages ACL 2021 On the Robustness of Intent Classification and Slot Labeling in Goal-oriented Dialog Systems to Real-world Noise EMNLP 2021 On the Robustness of Vision Transformers to Adversarial Examples ICCV 2021 On the Role of Corpus Ordering in Language Modeling EMNLP 2021 On the Stability of Random Matrix Product with Markovian Noise: Application to Linear Stochastic Approximation and TD Learning COLT 2021 On the Stability of System Rankings at WMT EMNLP 2021