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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

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20
220
477
4,652
9,258
2000
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Papers (including subtopics)

Budgeted Training: Rethinking Deep Neural Network Training Under Resource Constraints ICLR 2020 Building Calibrated Deep Models via Uncertainty Matching with Auxiliary Interval Predictors AAAI 2020 Bursting the Filter Bubble: Fairness-Aware Network Link Prediction AAAI 2020 Cable Manipulation with a Tactile-Reactive Gripper RSS 2020 CAG: A Real-Time Low-Cost Enhanced-Robustness High-Transferability Content-Aware Adversarial Attack Generator AAAI 2020 Cakewalk Sampling AAAI 2020 Calibrated Domain-Invariant Learning for Highly Generalizable Large Scale Re-Identification WACV 2020 Calibrated Prediction with Covariate Shift via Unsupervised Domain Adaptation AISTATS 2020 Calibrated Reliable Regression using Maximum Mean Discrepancy NeurIPS 2020 Calibrated Surrogate Losses for Adversarially Robust Classification COLT 2020 Calibrating CNNs for Lifelong Learning NeurIPS 2020 Calibrating Structured Output Predictors for Natural Language Processing ACL 2020 Calibration of Pre-trained Transformers EMNLP 2020 Camera On-Boarding for Person Re-Identification Using Hypothesis Transfer Learning CVPR 2020 Camouflaged Chinese Spam Content Detection with Semi-supervised Generative Active Learning ACL 2020 CancerEmo: A Dataset for Fine-Grained Emotion Detection EMNLP 2020 Can Cross Entropy Loss Be Robust to Label Noise? IJCAI 2020 Can Eruptions Be Predicted? Short-Term Prediction of Volcanic Eruptions via Attention-Based Long Short-Term Memory AAAI 2020 Can gradient clipping mitigate label noise? ICLR 2020 Can Increasing Input Dimensionality Improve Deep Reinforcement Learning? ICML 2020 Can I Trust My Fairness Metric? Assessing Fairness with Unlabeled Data and Bayesian Inference NeurIPS 2020 Can Monolingual Pretrained Models Help Cross-Lingual Classification? AACL 2020 Canonical 3D Deformer Maps: Unifying parametric and non-parametric methods for dense weakly-supervised category reconstruction NeurIPS 2020 Can Weight Sharing Outperform Random Architecture Search? An Investigation With TuNAS CVPR 2020 Can We Learn Heuristics for Graphical Model Inference Using Reinforcement Learning? CVPR 2020