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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)

Towards Robust Trajectory Representations: Isolating Environmental Confounders with Causal Learning IJCAI 2024 Towards Safe Policy Learning under Partial Identifiability: A Causal Approach AAAI 2024 Towards Safer Large Language Models through Machine Unlearning ACL 2024 Towards Scalable 3D Anomaly Detection and Localization: A Benchmark via 3D Anomaly Synthesis and A Self-Supervised Learning Network CVPR 2024 Towards Sharper Generalization Bounds for Adversarial Contrastive Learning IJCAI 2024 Towards Stable Representations for Protein Interface Prediction NeurIPS 2024 Towards Supervised Performance on Speaker Verification with Self-Supervised Learning by Leveraging Large-Scale ASR Models Interspeech 2024 Towards Surveillance Video-and-Language Understanding: New Dataset Baselines and Challenges CVPR 2024 Towards the Robustness of Differentially Private Federated Learning AAAI 2024 Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms ICML 2024 Towards the Transferability of Rewards Recovered via Regularized Inverse Reinforcement Learning NeurIPS 2024 Towards the Uncharted: Density-Descending Feature Perturbation for Semi-supervised Semantic Segmentation CVPR 2024 Towards Tool Use Alignment of Large Language Models EMNLP 2024 Towards training digitally-tied analog blocks via hybrid gradient computation NeurIPS 2024 Towards Transferable Adversarial Attacks with Centralized Perturbation AAAI 2024 Towards Transferable Targeted 3D Adversarial Attack in the Physical World CVPR 2024 Towards Transparent Time Series Forecasting ICLR 2024 Towards Trustworthy Deep Learning AAAI 2024 Towards Unbiased Exploration in Partial Label Learning JMLR 2024 Towards Uncertainty-Aware Language Agent ACL 2024 Towards Understanding and Improving Adversarial Robustness of Vision Transformers CVPR 2024 Towards Understanding Counseling Conversations: Domain Knowledge and Large Language Models EACL 2024 Towards Understanding the Relationship between In-context Learning and Compositional Generalization COLING 2024 Towards Unified Task Embeddings Across Multiple Models: Bridging the Gap for Prompt-Based Large Language Models and Beyond ACL 2024 Towards Unsupervised Model Selection for Domain Adaptive Object Detection NeurIPS 2024