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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)

Implicit Regularization in Over-Parameterized Support Vector Machine NeurIPS 2023 Implicit Regularization Leads to Benign Overfitting for Sparse Linear Regression ICML 2023 Implicit Regularization Towards Rank Minimization in ReLU Networks ALT 2023 Implicit Stochastic Gradient Descent for Training Physics-Informed Neural Networks AAAI 2023 Implicit Training of Inference Network Models for Structured Prediction UAI 2023 Implicit variance regularization in non-contrastive SSL NeurIPS 2023 Implicit Variational Inference for High-Dimensional Posteriors NeurIPS 2023 Importance Sparsification for Sinkhorn Algorithm JMLR 2023 Importance Weighted Expectation-Maximization for Protein Sequence Design ICML 2023 Improper Multiclass Boosting COLT 2023 Improvable Gap Balancing for Multi-Task Learning UAI 2023 Improved Algorithm for Regret Ratio Minimization in Multi-Objective Submodular Maximization AAAI 2023 Improved Algorithms for Multi-period Multi-class Packing Problems with Bandit Feedback ICML 2023 Improved Algorithms for Stochastic Linear Bandits Using Tail Bounds for Martingale Mixtures NeurIPS 2023 Improved Algorithms for White-Box Adversarial Streams ICML 2023 Improved Analysis of Score-based Generative Modeling: User-Friendly Bounds under Minimal Smoothness Assumptions ICML 2023 Improved Bayesian Regret Bounds for Thompson Sampling in Reinforcement Learning NeurIPS 2023 Improved Best-of-Both-Worlds Guarantees for Multi-Armed Bandits: FTRL with General Regularizers and Multiple Optimal Arms NeurIPS 2023 Improved Bound on Generalization Error of Compressed KNN Estimator AISTATS 2023 Improved Communication Efficiency in Federated Natural Policy Gradient via ADMM-based Gradient Updates NeurIPS 2023 Improved Convergence in High Probability of Clipped Gradient Methods with Heavy Tailed Noise NeurIPS 2023 Improved Convergence of Differential Private SGD with Gradient Clipping ICLR 2023 Improved Dynamic Regret for Online Frank-Wolfe COLT 2023 Improved Generalization Bound and Learning of Sparsity Patterns for Data-Driven Low-Rank Approximation AISTATS 2023 Improved High-Probability Regret for Adversarial Bandits with Time-Varying Feedback Graphs ALT 2023