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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)

Data-driven Rank Breaking for Efficient Rank Aggregation ICML 2016 Data-driven Rank Breaking for Efficient Rank Aggregation JMLR 2016 Data-Efficient Off-Policy Policy Evaluation for Reinforcement Learning ICML 2016 Data Selection by Sequence Summarizing Neural Network in Mismatch Condition Training Interspeech 2016 Data Selection for Within-Class Covariance Estimation Interspeech 2016 Dealbreaker: A Nonlinear Latent Variable Model for Educational Data ICML 2016 DECOrrelated feature space partitioning for distributed sparse regression NeurIPS 2016 Deep Gate Recurrent Neural Network ACML 2016 Deep Gaussian Processes for Regression using Approximate Expectation Propagation ICML 2016 Deep Learning without Poor Local Minima NeurIPS 2016 Deeply-Recursive Convolutional Network for Image Super-Resolution CVPR 2016 DeepMath - Deep Sequence Models for Premise Selection NeurIPS 2016 Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin ICML 2016 Deep Submodular Functions: Definitions and Learning NeurIPS 2016 Delay and Cooperation in Nonstochastic Bandits COLT 2016 Dense Monocular Depth Estimation in Complex Dynamic Scenes CVPR 2016 Density Evolution in the Degree-correlated Stochastic Block Model COLT 2016 Designing smoothing functions for improved worst-case competitive ratio in online optimization NeurIPS 2016 Determinantal Regularization for Ensemble Variable Selection AISTATS 2016 D-GloVe: A Feasible Least Squares Model for Estimating Word Embedding Densities COLING 2016 Differential Geometric Regularization for Supervised Learning of Classifiers ICML 2016 Differentially Private Chi-Squared Hypothesis Testing: Goodness of Fit and Independence Testing ICML 2016 Dimensionality Reduction of Massive Sparse Datasets Using Coresets NeurIPS 2016 Dimension-free Concentration Bounds on Hankel Matrices for Spectral Learning JMLR 2016 Dimension-Free Iteration Complexity of Finite Sum Optimization Problems NeurIPS 2016