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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

1
52
352
828
3,646
5,854
2000
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Papers (including subtopics)

Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation ICLR 2024 Towards a statistical theory of data selection under weak supervision ICLR 2024 Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics NeurIPS 2024 Towards a Theoretical Understanding of Why Local Search Works for Clustering with Fair-Center Representation AAAI 2024 Towards a theory of how the structure of language is acquired by deep neural networks NeurIPS 2024 Towards a Theory of Machine Learning on Graphs and its Applications in Combinatorial Optimization IJCAI 2024 Towards A Unified View of Answer Calibration for Multi-Step Reasoning ACL 2024 Towards AutoAI: Optimizing a Machine Learning System with Black-box and Differentiable Components ICML 2024 Towards Benchmarking Situational Awareness of Large Language Models:Comprehensive Benchmark, Evaluation and Analysis EMNLP 2024 Towards Better Structured Pruning Saliency by Reorganizing Convolution WACV 2024 Towards Calibrated Multi-label Deep Neural Networks CVPR 2024 Towards Certifiably Robust Face Recognition ECCV 2024 Towards Certified Unlearning for Deep Neural Networks ICML 2024 Towards Convergence Rates for Parameter Estimation in Gaussian-gated Mixture of Experts AISTATS 2024 Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective AISTATS 2024 Towards Dynamic Message Passing on Graphs NeurIPS 2024 Towards Effective and Efficient Non-autoregressive Decoding Using Block-based Attention Mask Interspeech 2024 Towards Efficient and Optimal Covariance-Adaptive Algorithms for Combinatorial Semi-Bandits NeurIPS 2024 Towards Efficient Exact Optimization of Language Model Alignment ICML 2024 Towards Efficient MCMC Sampling in Bayesian Neural Networks by Exploiting Symmetry (Extended Abstract) IJCAI 2024 Towards Efficient Training and Evaluation of Robust Models against l_0 Bounded Adversarial Perturbations ICML 2024 Towards Efficient Verification of Quantized Neural Networks AAAI 2024 Toward Self-Improvement of LLMs via Imagination, Searching, and Criticizing NeurIPS 2024 Towards Establishing Guaranteed Error for Learned Database Operations ICLR 2024 Towards Estimating Bounds on the Effect of Policies under Unobserved Confounding NeurIPS 2024