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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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Papers (including subtopics)

Searching for a Search Method: Benchmarking Search Algorithms for Generating NLP Adversarial Examples EMNLP 2020 Searching for Low-Bit Weights in Quantized Neural Networks NeurIPS 2020 Searching to Exploit Memorization Effect in Learning with Noisy Labels ICML 2020 Search Tree Pruning for Progressive Neural Architecture Search (Student Abstract) AAAI 2020 Second-Order Information in Non-Convex Stochastic Optimization: Power and Limitations COLT 2020 Second Order Optimality in Decentralized Non-Convex Optimization via Perturbed Gradient Tracking NeurIPS 2020 Second Order PAC-Bayesian Bounds for the Weighted Majority Vote NeurIPS 2020 Second-Order Provable Defenses against Adversarial Attacks ICML 2020 SEED RL: Scalable and Efficient Deep-RL with Accelerated Central Inference ICLR 2020 Selective Dyna-Style Planning Under Limited Model Capacity ICML 2020 SelectScale: Mining More Patterns from Images via Selective and Soft Dropout IJCAI 2020 Select to Better Learn: Fast and Accurate Deep Learning Using Data Selection From Nonlinear Manifolds CVPR 2020 Self-Adaptively Learning to Demoiré from Focused and Defocused Image Pairs NeurIPS 2020 Self-Adaptive Training: beyond Empirical Risk Minimization NeurIPS 2020 Self-Concordant Analysis of Frank-Wolfe Algorithms ICML 2020 Self-Distillation Amplifies Regularization in Hilbert Space NeurIPS 2020 Self-Distillation as Instance-Specific Label Smoothing NeurIPS 2020 Self-Guided Evolution Strategies with Historical Estimated Gradients IJCAI 2020 Self-Orthogonality Module: A Network Architecture Plug-in for Learning Orthogonal Filters WACV 2020 Semantic Complexity in End-to-End Spoken Language Understanding Interspeech 2020 Semantic Label Smoothing for Sequence to Sequence Problems EMNLP 2020 Semantic Width and the Fixed-Parameter Tractability of Constraint Satisfaction Problems IJCAI 2020 Semialgebraic Optimization for Lipschitz Constants of ReLU Networks NeurIPS 2020 Semi-bandit Optimization in the Dispersed Setting UAI 2020 Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of components AISTATS 2020