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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)

Higher-Order Correlation Clustering for Image Segmentation NeurIPS 2011 Hogwild!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent NeurIPS 2011 How biased are maximum entropy models? NeurIPS 2011 Hyper-Sparse Optimal Aggregation JMLR 2011 Identifiability of Priors from Bounded Sample Sizes with Applications to Transfer Learning COLT 2011 Improved Algorithms for Linear Stochastic Bandits NeurIPS 2011 Improved Loss Bounds For Multiple Kernel Learning AISTATS 2011 Improved Regret Guarantees for Online Smooth Convex Optimization with Bandit Feedback AISTATS 2011 Improving Policy Gradient Estimates with Influence Information ACML 2011 In All Likelihood, Deep Belief Is Not Enough JMLR 2011 Inductive reasoning about chimeric creatures NeurIPS 2011 Inference in continuous-time change-point models NeurIPS 2011 Inferring Interaction Networks using the IBP applied to microRNA Target Prediction NeurIPS 2011 Inferring spike-timing-dependent plasticity from spike train data NeurIPS 2011 Information, Divergence and Risk for Binary Experiments JMLR 2011 Information Rates and Optimal Decoding in Large Neural Populations NeurIPS 2011 Information Rates of Nonparametric Gaussian Process Methods JMLR 2011 Internal Regret with Partial Monitoring: Calibration-Based Optimal Algorithms JMLR 2011 Iterative Learning for Reliable Crowdsourcing Systems NeurIPS 2011 Kernel Bayes' Rule NeurIPS 2011 Kernel Belief Propagation AISTATS 2011 Kernel Embeddings of Latent Tree Graphical Models NeurIPS 2011 Kernel Regression in the Presence of Correlated Errors JMLR 2011 k-NN Regression Adapts to Local Intrinsic Dimension NeurIPS 2011 Large-Scale Sparse Principal Component Analysis with Application to Text Data NeurIPS 2011