Skip to content
conftrace_

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)
1
20
220
477
4,652
9,258
2000
'5
'10
'15
'20
'25

Papers (including subtopics)

Dense Self-Supervised Learning for Medical Image Segmentation MIDL 2024 Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval NeurIPS 2024 Density-Guided Semi-Supervised 3D Semantic Segmentation with Dual-Space Hardness Sampling CVPR 2024 Density-guided Translator Boosts Synthetic-to-Real Unsupervised Domain Adaptive Segmentation of 3D Point Clouds CVPR 2024 Density Matters: Improved Core-Set for Active Domain Adaptive Segmentation AAAI 2024 Density-Regression: Efficient and Distance-aware Deep Regressor for Uncertainty Estimation under Distribution Shifts AISTATS 2024 Density Uncertainty Layers for Reliable Uncertainty Estimation AISTATS 2024 DePLM: Denoising Protein Language Models for Property Optimization NeurIPS 2024 Depression Detection in Clinical Interviews with LLM-Empowered Structural Element Graph NAACL 2024 Depression Detection via Capsule Networks with Contrastive Learning AAAI 2024 DePRL: Achieving Linear Convergence Speedup in Personalized Decentralized Learning with Shared Representations AAAI 2024 Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data CVPR 2024 Depth Anywhere: Enhancing 360 Monocular Depth Estimation via Perspective Distillation and Unlabeled Data Augmentation NeurIPS 2024 Depth Aware Hierarchical Replay Continual Learning for Knowledge Based Question Answering COLING 2024 Depth-aware Test-Time Training for Zero-shot Video Object Segmentation CVPR 2024 Derandomizing Multi-Distribution Learning NeurIPS 2024 DeRDaVa: Deletion-Robust Data Valuation for Machine Learning AAAI 2024 Derivative-enhanced Deep Operator Network NeurIPS 2024 DeS3: Adaptive Attention-Driven Self and Soft Shadow Removal Using ViT Similarity AAAI 2024 Design Choices for Enhancing Noisy Student Self-Training WACV 2024 Designing a Hybrid Neural System To Learn Real-World Crack Segmentation From Fractal-Based Simulation WACV 2024 Designing Behavior-Aware AI to Improve the Human-AI Team Performance in AI-Assisted Decision Making IJCAI 2024 Designing Cell-Type-Specific Promoter Sequences Using Conservative Model-Based Optimization NeurIPS 2024 Designing Informative Metrics for Few-Shot Example Selection ACL 2024 Designs for Enabling Collaboration in Human-Machine Teaming via Interactive and Explainable Systems NeurIPS 2024