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Optimization & Theory

43,292 papers (3 classified directly here)

Subtopics · a paper can sit in several, so these overlap

Optimization (17,731) Learning Theory (6,809) Bayesian Inference (6,267) Theory (5,579) Statistical Learning (4,564) Neural Network Optimization (4,155) Stochastic Processes (2,948) Stochastic Methods (1,283) Loss Functions (1,220) Distributed Learning (1,202) Online Algorithms (1,013) Statistics (822) Generalization (376) Information Theory (370) Sample Complexity (282) Sparse Optimization (241) Game Theory (151) Convex Optimization (132) Optimal Transport (104) Robust Optimization (84) Distributed Optimization (73) Approximation Algorithms (33)

Papers per year

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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

The sample complexity of ERMs in stochastic convex optimization AISTATS 2024 The Sample Complexity of Gradient Descent in Stochastic Convex Optimization NeurIPS 2024 The sample complexity of multi-distribution learning COLT 2024 The Sample Complexity of Simple Binary Hypothesis Testing COLT 2024 The Secretary Problem with Predicted Additive Gap NeurIPS 2024 The Semantic Relations in LLMs: An Information-theoretic Compression Approach COLING 2024 The Shape of Learning: Anisotropy and Intrinsic Dimensions in Transformer-Based Models EACL 2024 The Shape of Word Embeddings: Quantifying Non-Isometry with Topological Data Analysis EMNLP 2024 The SMART approach to instance-optimal online learning COLT 2024 The Space Complexity of Approximating Logistic Loss NeurIPS 2024 The Star Geometry of Critic-Based Regularizer Learning NeurIPS 2024 The Star Number and Eluder Dimension: Elementary Observations About the Dimensions of Disagreement COLT 2024 The surprising efficiency of temporal difference learning for rare event prediction NeurIPS 2024 The Value of Reward Lookahead in Reinforcement Learning NeurIPS 2024 Think Before You Duel: Understanding Complexities of Preference Learning under Constrained Resources AISTATS 2024 Think before you speak: Training Language Models With Pause Tokens ICLR 2024 Think Global, Adapt Local: Learning Locally Adaptive K-Nearest Neighbor Kernel Density Estimators AISTATS 2024 Thinking Forward: Memory-Efficient Federated Finetuning of Language Models NeurIPS 2024 Think Twice Before Selection: Federated Evidential Active Learning for Medical Image Analysis with Domain Shifts CVPR 2024 This Too Shall Pass: Removing Stale Observations in Dynamic Bayesian Optimization NeurIPS 2024 Thompson Sampling For Combinatorial Bandits: Polynomial Regret and Mismatched Sampling Paradox NeurIPS 2024 Three-Way Trade-Off in Multi-Objective Learning: Optimization, Generalization and Conflict-Avoidance JMLR 2024 Threshold-Based Responsive Simulated Annealing for Directed Feedback Vertex Set Problem AAAI 2024 Threshold-Consistent Margin Loss for Open-World Deep Metric Learning ICLR 2024 Thunder : Unified Regression-Diffusion Speech Enhancement with a Single Reverse Step using Brownian Bridge Interspeech 2024