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

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Papers (including subtopics)

Reinforcement Learning to adjust Robot Movements to New Situations RSS 2010 Relating Function Class Complexity and Cluster Structure in the Function Domain with Applications to Transduction AISTATS 2010 Relaxed Clipping: A Global Training Method for Robust Regression and Classification NeurIPS 2010 Repeated Games against Budgeted Adversaries NeurIPS 2010 Reverse Multi-Label Learning NeurIPS 2010 Reward Design via Online Gradient Ascent NeurIPS 2010 Robust Clustering as Ensembles of Affinity Relations NeurIPS 2010 Robust PCA via Outlier Pursuit NeurIPS 2010 Sample Complexity of Testing the Manifold Hypothesis NeurIPS 2010 Segmentation and Unsupervised Part-based Discovery of Repetitive Objects RSS 2010 Self-Paced Learning for Latent Variable Models NeurIPS 2010 Semi-Supervised Learning via Generalized Maximum Entropy AISTATS 2010 Semi-Supervised Learning with Adversarially Missing Label Information NeurIPS 2010 Semi-Supervised Learning with Max-Margin Graph Cuts AISTATS 2010 Semi-Supervised Novelty Detection JMLR 2010 Shadow Dirichlet for Restricted Probability Modeling NeurIPS 2010 Sidestepping Intractable Inference with Structured Ensemble Cascades NeurIPS 2010 Simultaneous Object Detection and Ranking with Weak Supervision NeurIPS 2010 Sparse Instrumental Variables (SPIV) for Genome-Wide Studies NeurIPS 2010 Sparse Semi-supervised Learning Using Conjugate Functions JMLR 2010 Spatial and anatomical regularization of SVM for brain image analysis NeurIPS 2010 Spectral Regularization for Support Estimation NeurIPS 2010 Sphere Embedding: An Application to Part-of-Speech Induction NeurIPS 2010 Spike timing-dependent plasticity as dynamic filter NeurIPS 2010 Stability Approach to Regularization Selection (StARS) for High Dimensional Graphical Models NeurIPS 2010