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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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2000
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Papers (including subtopics)

PAGE: A Simple and Optimal Probabilistic Gradient Estimator for Nonconvex Optimization ICML 2021 PALM: Probabilistic area loss Minimization for Protein Sequence Alignment UAI 2021 **Paper retracted by author request (see pdf for retraction notice from the authors)** Nonparametric Regression with Shallow Overparameterized Neural Networks Trained by GD with Early Stopping COLT 2021 PAPRIKA: Private Online False Discovery Rate Control ICML 2021 Parallel and Efficient Hierarchical k-Median Clustering NeurIPS 2021 Parallel and Flexible Sampling from Autoregressive Models via Langevin Dynamics ICML 2021 Parallel Bayesian Optimization of Multiple Noisy Objectives with Expected Hypervolume Improvement NeurIPS 2021 Parallel Droplet Control in MEDA Biochips using Multi-Agent Reinforcement Learning ICML 2021 Parallelised Diffeomorphic Sampling-based Motion Planning CoRL 2021 Parallelizing Legendre Memory Unit Training ICML 2021 Parallel Rectangle Flip Attack: A Query-Based Black-Box Attack Against Object Detection ICCV 2021 Parallel tempering on optimized paths ICML 2021 Parameter-Based Value Functions ICLR 2021 Parameter-Efficient Transfer Learning with Diff Pruning ACL 2021 Parameter-free HE-friendly Logistic Regression NeurIPS 2021 Parameter-free Locally Accelerated Conditional Gradients ICML 2021 Parameter Inference with Bifurcation Diagrams NeurIPS 2021 Parameterized Complexity of Logic-Based Argumentation in Schaefer's Framework AAAI 2021 Parameterized Complexity of Small Decision Tree Learning AAAI 2021 Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies AAAI 2021 Parameter Selection: Why We Should Pay More Attention to It ACL 2021 Parametric Complexity Bounds for Approximating PDEs with Neural Networks NeurIPS 2021 Parametric Graph for Unimodal Ranking Bandit ICML 2021 Parametric Programming Approach for More Powerful and General Lasso Selective Inference AISTATS 2021 Parametrized Quantum Policies for Reinforcement Learning NeurIPS 2021