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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 Theoretically Grounded Application of Dropout in Recurrent Neural Networks NeurIPS 2016 Augmentable Gamma Belief Networks JMLR 2016 A Unified View on Multi-class Support Vector Classification JMLR 2016 Automatic Image Cropping : A Computational Complexity Study CVPR 2016 A Variational Analysis of Stochastic Gradient Algorithms ICML 2016 A Variational Approach to Path Estimation and Parameter Inference of Hidden Diffusion Processes JMLR 2016 Average-case hardness of RIP certification NeurIPS 2016 A Voice Conversion Mapping Function Based on a Stacked Joint-Autoencoder Interspeech 2016 A Weighted Variational Model for Simultaneous Reflectance and Illumination Estimation CVPR 2016 Back to the Future: Radial Basis Function Networks Revisited AISTATS 2016 Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition NeurIPS 2016 Barron and Cover’s Theory in Supervised Learning and its Application to Lasso ICML 2016 Barzilai-Borwein Step Size for Stochastic Gradient Descent NeurIPS 2016 BASC: Applying Bayesian Optimization to the Search for Global Minima on Potential Energy Surfaces ICML 2016 Batch Bayesian Optimization via Local Penalization AISTATS 2016 Batched Gaussian Process Bandit Optimization via Determinantal Point Processes NeurIPS 2016 Bayesian Decision Process for Cost-Efficient Dynamic Ranking via Crowdsourcing JMLR 2016 Bayesian Generalised Ensemble Markov Chain Monte Carlo AISTATS 2016 Bayesian Graphical Models for Multivariate Functional Data JMLR 2016 Bayesian Intermittent Demand Forecasting for Large Inventories NeurIPS 2016 Bayesian Language Model based on Mixture of Segmental Contexts for Spontaneous Utterances with Unexpected Words COLING 2016 Bayesian Leave-One-Out Cross-Validation Approximations for Gaussian Latent Variable Models JMLR 2016 Bayesian Matrix Factorization with Non-Random Missing Data using Informative Gaussian Process Priors and Soft Evidences PGM 2016 Bayesian Networks: a Combined Tuning Heuristic PGM 2016 Bayesian Nonparametric Kernel-Learning AISTATS 2016