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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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Papers (including subtopics)

Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels ICML 2019 Understanding Dropouts in MOOCs AAAI 2019 Understanding Pictograph with Facial Features: End-to-End Sentence-Level Lip Reading of Chinese AAAI 2019 Understanding Straight-Through Estimator in Training Activation Quantized Neural Nets ICLR 2019 Understanding Teacher Gaze Patterns for Robot Learning CoRL 2019 Understanding the Behaviour of Neural Abstractive Summarizers using Contrastive Examples NAACL 2019 Understanding the Impact of Entropy on Policy Optimization ICML 2019 Unidirectional Neural Network Architectures for End-to-End Automatic Speech Recognition Interspeech 2019 Unified Embedding Alignment with Missing Views Inferring for Incomplete Multi-View Clustering AAAI 2019 Unified Policy Optimization for Robust Reinforcement Learning ACML 2019 Unified Semantic Parsing with Weak Supervision ACL 2019 Unified Visual-Semantic Embeddings: Bridging Vision and Language With Structured Meaning Representations CVPR 2019 Uniform Error Bounds for Gaussian Process Regression with Application to Safe Control NeurIPS 2019 Unifying Heterogeneous Classifiers With Distillation CVPR 2019 Universal Adversarial Perturbations for Speech Recognition Systems Interspeech 2019 Universal Adversarial Perturbation via Prior Driven Uncertainty Approximation ICCV 2019 Universal Adversarial Triggers for Attacking and Analyzing NLP EMNLP 2019 Universal Domain Adaptation CVPR 2019 Universality in Learning from Linear Measurements NeurIPS 2019 Universal Multi-Party Poisoning Attacks ICML 2019 Universal Perturbation Attack Against Image Retrieval ICCV 2019 Universal Semi-Supervised Semantic Segmentation ICCV 2019 University of Tartu’s Multilingual Multi-domain WMT19 News Translation Shared Task Submission ACL 2019 Unlabeled Data Improves Adversarial Robustness NeurIPS 2019 Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual EMNLP 2019