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Learning Types

56,253 papers (3 classified directly here)

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)
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Papers (including subtopics)

PrefAce: Face-Centric Pretraining with Self-Structure Aware Distillation AAAI 2024 Preference Alignment with Flow Matching NeurIPS 2024 Preference-Aware Constrained Multi-Objective Bayesian Optimization (Student Abstract) AAAI 2024 Preference Aware Dual Contrastive Learning for Item Cold-Start Recommendation AAAI 2024 Preference-based Pure Exploration NeurIPS 2024 Preference-Guided Reflective Sampling for Aligning Language Models EMNLP 2024 Preference Learning of Latent Decision Utilities with a Human-like Model of Preferential Choice NeurIPS 2024 Prefix-diffusion: A Lightweight Diffusion Model for Diverse Image Captioning COLING 2024 Premier-TACO is a Few-Shot Policy Learner: Pretraining Multitask Representation via Temporal Action-Driven Contrastive Loss ICML 2024 Preserving Fairness Generalization in Deepfake Detection CVPR 2024 Preserving Generalization of Language models in Few-shot Continual Relation Extraction EMNLP 2024 Pre-trained Language Models Return Distinguishable Probability Distributions to Unfaithfully Hallucinated Texts EMNLP 2024 Pre-trained Model Guided Fine-Tuning for Zero-Shot Adversarial Robustness CVPR 2024 Pre-Trained Multi-Goal Transformers with Prompt Optimization for Efficient Online Adaptation NeurIPS 2024 Pre-trained Online Contrastive Learning for Insurance Fraud Detection AAAI 2024 Pre-trained Text-to-Image Diffusion Models Are Versatile Representation Learners for Control NeurIPS 2024 Pretrained Transformer Efficiently Learns Low-Dimensional Target Functions In-Context NeurIPS 2024 Pre-trained Vision and Language Transformers Are Few-Shot Incremental Learners CVPR 2024 Pre-trained Visual Dynamics Representations for Efficient Policy Learning ECCV 2024 Pretraining and Finetuning Language Models on Geospatial Networks for Accurate Address Matching EMNLP 2024 Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs NeurIPS 2024 Pre-training Cross-Modal Retrieval by Expansive Lexicon-Patch Alignment COLING 2024 Pretraining Data Detection for Large Language Models: A Divergence-based Calibration Method EMNLP 2024 Pre-training Differentially Private Models with Limited Public Data NeurIPS 2024 Pretraining End-to-End Keyword Search with Automatically Discovered Acoustic Units Interspeech 2024