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)

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Papers (including subtopics)

Double or Nothing: Multiplicative Incentive Mechanisms for Crowdsourcing NeurIPS 2015 Dynamic Sensing: Better Classification under Acquisition Constraints ICML 2015 Efficient and Parsimonious Agnostic Active Learning NeurIPS 2015 Efficient and Robust Automated Machine Learning NeurIPS 2015 Efficient Classifier Training to Minimize False Merges in Electron Microscopy Segmentation ICCV 2015 Efficient Label Collection for Unlabeled Image Datasets CVPR 2015 Efficient Learning by Directed Acyclic Graph For Resource Constrained Prediction NeurIPS 2015 Efficient Learning in Large-Scale Combinatorial Semi-Bandits ICML 2015 Efficient Learning of Linear Separators under Bounded Noise COLT 2015 Efficient Output Kernel Learning for Multiple Tasks NeurIPS 2015 Efficient Representations for Lifelong Learning and Autoencoding COLT 2015 Efficient Second-Order Gradient Boosting for Conditional Random Fields AISTATS 2015 Efficient Thompson Sampling for Online Matrix-Factorization Recommendation NeurIPS 2015 Eigenwords: Spectral Word Embeddings JMLR 2015 Embedding Inference for Structured Multilabel Prediction NeurIPS 2015 Empirical Localization of Homogeneous Divergences on Discrete Sample Spaces NeurIPS 2015 Encoding Based Saliency Detection for Videos and Images CVPR 2015 End-to-end Learning of LDA by Mirror-Descent Back Propagation over a Deep Architecture NeurIPS 2015 Enforcing balance allows local supervised learning in spiking recurrent networks NeurIPS 2015 Entropic Graph-based Posterior Regularization ICML 2015 Entropy evaluation based on confidence intervals of frequency estimates : Application to the learning of decision trees ICML 2015 Estimating the accuracies of multiple classifiers without labeled data AISTATS 2015 Evaluation of Output Embeddings for Fine-Grained Image Classification CVPR 2015 Expanding Object Detector's Horizon: Incremental Learning Framework for Object Detection in Videos CVPR 2015 Explore no more: Improved high-probability regret bounds for non-stochastic bandits NeurIPS 2015