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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)

Optimal Regularized Dual Averaging Methods for Stochastic Optimization NeurIPS 2012 Optimistic Bayesian Sampling in Contextual-Bandit Problems JMLR 2012 Optimization of Temporal Dynamics for Adaptive Human-Robot Interaction in Assembly Manufacturing RSS 2012 PAC-Bayes Bounds with Data Dependent Priors JMLR 2012 PAC-Bayesian Bound for Gaussian Process Regression and Multiple Kernel Additive Model COLT 2012 Part & Clamp: Efficient Structured Output Learning AISTATS 2012 Perfect Dimensionality Recovery by Variational Bayesian PCA NeurIPS 2012 Persistent Homology for Learning Densities with Bounded Support NeurIPS 2012 Perturbation based Large Margin Approach for Ranking AISTATS 2012 Phoneme Classification using Constrained Variational Gaussian Process Dynamical System NeurIPS 2012 Pointwise Tracking the Optimal Regression Function NeurIPS 2012 Positive Semidefinite Metric Learning Using Boosting-like Algorithms JMLR 2012 Practical Bayesian Optimization of Machine Learning Algorithms NeurIPS 2012 Practical Route Planning Under Delay Uncertainty: Stochastic Shortest Path Queries RSS 2012 Priors for Diversity in Generative Latent Variable Models NeurIPS 2012 Privacy Aware Learning NeurIPS 2012 Private Convex Empirical Risk Minimization and High-dimensional Regression COLT 2012 Probabilistic Low-Rank Subspace Clustering NeurIPS 2012 Proper losses for learning from partial labels NeurIPS 2012 Protocols for Learning Classifiers on Distributed Data AISTATS 2012 Provable ICA with Unknown Gaussian Noise, with Implications for Gaussian Mixtures and Autoencoders NeurIPS 2012 Proximal Newton-type methods for convex optimization NeurIPS 2012 Putting Bayes to sleep NeurIPS 2012 Query Complexity of Derivative-Free Optimization NeurIPS 2012 Random Design Analysis of Ridge Regression COLT 2012