Skip to content
conftrace_

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

1
52
352
828
3,646
5,854
2000
'5
'10
'15
'20
'25

Papers (including subtopics)

Navigating Extremes: Dynamic Sparsity in Large Output Spaces NeurIPS 2024 Navigating Noisy Feedback: Enhancing Reinforcement Learning with Error-Prone Language Models EMNLP 2024 Navigating Scaling Laws: Compute Optimality in Adaptive Model Training ICML 2024 Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generation ICLR 2024 Navigating the Maze of Explainable AI: A Systematic Approach to Evaluating Methods and Metrics NeurIPS 2024 Navigating the Metrics Maze: Reconciling Score Magnitudes and Accuracies ACL 2024 Navigating the Minefield of MT Beam Search in Cascaded Streaming Speech Translation Interspeech 2024 Navigating the Modern Evaluation Landscape: Considerations in Benchmarks and Frameworks for Large Language Models (LLMs) COLING 2024 NDOT: Neuronal Dynamics-based Online Training for Spiking Neural Networks ICML 2024 Nearest Neighbor Speculative Decoding for LLM Generation and Attribution NeurIPS 2024 Near-Interpolators: Rapid Norm Growth and the Trade-Off between Interpolation and Generalization AISTATS 2024 Near-Linear Time Approximation Algorithms for k-means with Outliers ICML 2024 Nearly d-Linear Convergence Bounds for Diffusion Models via Stochastic Localization ICLR 2024 Nearly Minimax Optimal Submodular Maximization with Bandit Feedback NeurIPS 2024 Nearly Optimal Approximation of Matrix Functions by the Lanczos Method NeurIPS 2024 Nearly Optimal Regret for Decentralized Online Convex Optimization COLT 2024 Nearly Tight Black-Box Auditing of Differentially Private Machine Learning NeurIPS 2024 Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model NeurIPS 2024 Near Optimal Adversarial Attacks on Stochastic Bandits and Defenses with Smoothed Responses AISTATS 2024 Near-Optimal Algorithms for Making the Gradient Small in Stochastic Minimax Optimization JMLR 2024 Near-Optimal Convex Simple Bilevel Optimization with a Bisection Method AISTATS 2024 Near-Optimal Distributed Minimax Optimization under the Second-Order Similarity NeurIPS 2024 Near-Optimal Distributionally Robust Reinforcement Learning with General L_p Norms NeurIPS 2024 Near-Optimal Dynamic Regret for Adversarial Linear Mixture MDPs NeurIPS 2024 Near-Optimality of Contrastive Divergence Algorithms NeurIPS 2024