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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)

Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms NeurIPS 2020 Fast and Accurate Ranking Regression AISTATS 2020 Fast and Bayes-consistent nearest neighbors AISTATS 2020 Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations ICML 2020 Fast and Flexible Temporal Point Processes with Triangular Maps NeurIPS 2020 Fast and Furious Convergence: Stochastic Second Order Methods under Interpolation AISTATS 2020 Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods ICML 2020 Fast Bayesian Inference of Sparse Networks with Automatic Sparsity Determination JMLR 2020 Fast Convergence of Langevin Dynamics on Manifold: Geodesics meet Log-Sobolev NeurIPS 2020 Fastened CROWN: Tightened Neural Network Robustness Certificates AAAI 2020 Fast Epigraphical Projection-based Incremental Algorithms for Wasserstein Distributionally Robust Support Vector Machine NeurIPS 2020 Faster Differentially Private Samplers via Rényi Divergence Analysis of Discretized Langevin MCMC NeurIPS 2020 Faster Projection-free Online Learning COLT 2020 Faster Randomized Infeasible Interior Point Methods for Tall/Wide Linear Programs NeurIPS 2020 Faster Wasserstein Distance Estimation with the Sinkhorn Divergence NeurIPS 2020 Fast Exact Matrix Completion: A Unified Optimization Framework for Matrix Completion JMLR 2020 Fast geometric learning with symbolic matrices NeurIPS 2020 Fast is better than free: Revisiting adversarial training ICLR 2020 Fast Learning of Graph Neural Networks with Guaranteed Generalizability: One-hidden-layer Case ICML 2020 Fast Markov chain Monte Carlo algorithms via Lie groups AISTATS 2020 Fast Matrix Square Roots with Applications to Gaussian Processes and Bayesian Optimization NeurIPS 2020 Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients JMLR 2020 Fast Neural Network Adaptation via Parameter Remapping and Architecture Search ICLR 2020 Fast Noise Removal for k-Means Clustering AISTATS 2020 Fast Postprocessing for Difficult Discrete Energy Minimization Problems WACV 2020