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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)

Spectral Experts for Estimating Mixtures of Linear Regressions ICML 2013 Spectral Learning of Hidden Markov Models from Dynamic and Static Data ICML 2013 Spectral methods for neural characterization using generalized quadratic models NeurIPS 2013 Spectral Modeling and Relighting of Reflective-Fluorescent Scenes CVPR 2013 Speeding up Permutation Testing in Neuroimaging NeurIPS 2013 Speedup Matrix Completion with Side Information: Application to Multi-Label Learning NeurIPS 2013 Spike train entropy-rate estimation using hierarchical Dirichlet process priors NeurIPS 2013 Squared-loss Mutual Information Regularization: A Novel Information-theoretic Approach to Semi-supervised Learning ICML 2013 Stability and Hypothesis Transfer Learning ICML 2013 Stability of Multi-Task Kernel Regression Algorithms ACML 2013 Stable Coactive Learning via Perturbation ICML 2013 Statistical Active Learning Algorithms NeurIPS 2013 Statistical analysis of coupled time series with Kernel Cross-Spectral Density operators. NeurIPS 2013 Statistical Tests for Contagion in Observational Social Network Studies AISTATS 2013 Stochastic Alternating Direction Method of Multipliers ICML 2013 Stochastic blockmodel approximation of a graphon: Theory and consistent estimation NeurIPS 2013 Stochastic Deconvolution CVPR 2013 Stochastic Dual Coordinate Ascent Methods for Regularized Loss Minimization JMLR 2013 Stochastic Gradient Descent for Non-smooth Optimization: Convergence Results and Optimal Averaging Schemes ICML 2013 Stochastic Gradient Riemannian Langevin Dynamics on the Probability Simplex NeurIPS 2013 Stochastic Majorization-Minimization Algorithms for Large-Scale Optimization NeurIPS 2013 Stochastic Optimization of PCA with Capped MSG NeurIPS 2013 Stochastic Simultaneous Optimistic Optimization ICML 2013 Stochastic Variational Inference JMLR 2013 Streaming Variational Bayes NeurIPS 2013