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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)

Globally Convergent Parallel MAP LP Relaxation Solver using the Frank-Wolfe Algorithm ICML 2014 Global Sensitivity Analysis for MAP Inference in Graphical Models NeurIPS 2014 Good Vibrations: A Modal Analysis Approach for Sequential Non-Rigid Structure from Motion CVPR 2014 Gradient Hard Thresholding Pursuit for Sparsity-Constrained Optimization ICML 2014 Graph Clustering With Missing Data: Convex Algorithms and Analysis NeurIPS 2014 Graph Cut based Continuous Stereo Matching using Locally Shared Labels CVPR 2014 Greedy Subspace Clustering NeurIPS 2014 Ground Plane Estimation using a Hidden Markov Model CVPR 2014 Grouping-Based Low-Rank Trajectory Completion and 3D Reconstruction NeurIPS 2014 Guess-Averse Loss Functions For Cost-Sensitive Multiclass Boosting ICML 2014 Hamiltonian Monte Carlo Without Detailed Balance ICML 2014 Hamming Ball Auxiliary Sampling for Factorial Hidden Markov Models NeurIPS 2014 Hard-Margin Active Linear Regression ICML 2014 Hardness of parameter estimation in graphical models NeurIPS 2014 Hash-SVM: Scalable Kernel Machines for Large-Scale Visual Classification CVPR 2014 Heavy-tailed regression with a generalized median-of-means ICML 2014 Hierarchical Dirichlet Scaling Process ICML 2014 High-Dimensional Covariance Decomposition into Sparse Markov and Independence Models JMLR 2014 High-Dimensional Density Ratio Estimation with Extensions to Approximate Likelihood Computation AISTATS 2014 High-Dimensional Learning of Linear Causal Networks via Inverse Covariance Estimation JMLR 2014 Higher-Order Clique Reduction Without Auxiliary Variables CVPR 2014 Higher-Order Regret Bounds with Switching Costs COLT 2014 How hard is my MDP?" The distribution-norm to the rescue" NeurIPS 2014 How transferable are features in deep neural networks? NeurIPS 2014 Identifying and attacking the saddle point problem in high-dimensional non-convex optimization NeurIPS 2014