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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)

A Convex Atomic-Norm Approach to Multiple Sequence Alignment and Motif Discovery ICML 2016 A Convex Model for Linguistic Influence in Group Conversations Interspeech 2016 A Convex Surrogate Operator for General Non-Modular Loss Functions AISTATS 2016 Acoustic Properties of Formality in Conversational Japanese Interspeech 2016 Active Learning with Oracle Epiphany NeurIPS 2016 Actively Learning Hemimetrics with Applications to Eliciting User Preferences ICML 2016 Active Nearest-Neighbor Learning in Metric Spaces NeurIPS 2016 AdaDelay: Delay Adaptive Distributed Stochastic Optimization AISTATS 2016 Adapting Multicomponent Predictive Systems using Hybrid Adaptation Strategies with Auto-WEKA in Process Industry AutoML 2016 Adaptive Algorithms for Online Convex Optimization with Long-term Constraints ICML 2016 Adaptive Averaging in Accelerated Descent Dynamics NeurIPS 2016 Adaptive Concentration Inequalities for Sequential Decision Problems NeurIPS 2016 Adaptive Group Sparsity for Non-Negative Matrix Factorization with Application to Unsupervised Source Separation Interspeech 2016 Adaptive Lasso and group-Lasso for functional Poisson regression JMLR 2016 Adaptive Learning with Robust Generalization Guarantees COLT 2016 Adaptive Neural Compilation NeurIPS 2016 Adaptive Newton Method for Empirical Risk Minimization to Statistical Accuracy NeurIPS 2016 Adaptive Sampling for SGD by Exploiting Side Information ICML 2016 Adaptive Smoothed Online Multi-Task Learning NeurIPS 2016 Additive Approximations in High Dimensional Nonparametric Regression via the SALSA ICML 2016 A Differential Equation for Modeling Nesterov's Accelerated Gradient Method: Theory and Insights JMLR 2016 A DNN-HMM Approach to Story Segmentation Interspeech 2016 A Field Model for Repairing 3D Shapes CVPR 2016 A Fixed-Point Operator for Inference in Variational Bayesian Latent Gaussian Models AISTATS 2016 A General Framework for Consistency of Principal Component Analysis JMLR 2016