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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)

Safe non-smooth black-box optimization with application to policy search L4DC 2020 SAFER: A Structure-free Approach for Certified Robustness to Adversarial Word Substitutions ACL 2020 SalamNET at SemEval-2020 Task 12: Deep Learning Approach for Arabic Offensive Language Detection SemEval 2020 Same Features, Different Day: Weakly Supervised Feature Learning for Seasonal Invariance CVPR 2020 Sample Complexity of Estimating the Policy Gradient for Nearly Deterministic Dynamical Systems AISTATS 2020 Sample Complexity of Reinforcement Learning using Linearly Combined Model Ensembles AISTATS 2020 SampleNet: Differentiable Point Cloud Sampling CVPR 2020 Sampling-based Reachability Analysis: A Random Set Theory Approach with Adversarial Sampling CoRL 2020 Sampling-Decomposable Generative Adversarial Recommender NeurIPS 2020 Sampling from a k-DPP without looking at all items NeurIPS 2020 Samsung R&D Institute Poland submission to WMT20 News Translation Task EMNLP 2020 SATNet: Symmetric Adversarial Transfer Network Based on Two-Level Alignment Strategy towards Cross-Domain Sentiment Classification (Student Abstract) AAAI 2020 SCADA: Stochastic, Consistent and Adversarial Data Augmentation to Improve ASR Interspeech 2020 ScaIL: Classifier Weights Scaling for Class Incremental Learning WACV 2020 Scalable and Order-robust Continual Learning with Additive Parameter Decomposition ICLR 2020 Scalable Differential Privacy with Certified Robustness in Adversarial Learning ICML 2020 Scalable Feature Selection for (Multitask) Gradient Boosted Trees AISTATS 2020 Scalable Inference on the Soft Affiliation Graph Model for Overlapping Community Detection ACML 2020 Scalable Methods for Computing State Similarity in Deterministic Markov Decision Processes AAAI 2020 Scalable Reinforcement Learning of Localized Policies for Multi-Agent Networked Systems L4DC 2020 Scalable Zero-shot Entity Linking with Dense Entity Retrieval EMNLP 2020 ScaleNet - Improve CNNs through Recursively Rescaling Objects AAAI 2020 Scaling All-Goals Updates in Reinforcement Learning Using Convolutional Neural Networks AAAI 2020 Scaling data-driven robotics with reward sketching and batch reinforcement learning RSS 2020 Scaling Systematic Literature Reviews with Machine Learning Pipelines EMNLP 2020