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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 Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe AISTATS 2017 A Unified Variance Reduction-Based Framework for Nonconvex Low-Rank Matrix Recovery ICML 2017 A Unifying Framework for Gaussian Process Pseudo-Point Approximations using Power Expectation Propagation JMLR 2017 A Universal Analysis of Large-Scale Regularized Least Squares Solutions NeurIPS 2017 Automated Curriculum Learning for Neural Networks ICML 2017 Automated Inference with Adaptive Batches AISTATS 2017 Automatic Differentiation Variational Inference JMLR 2017 Automatic Discovery of the Statistical Types of Variables in a Dataset ICML 2017 Auto-WEKA 2.0: Automatic model selection and hyperparameter optimization in WEKA JMLR 2017 Averaged Collapsed Variational Bayes Inference JMLR 2017 Averaged-DQN: Variance Reduction and Stabilization for Deep Reinforcement Learning ICML 2017 A Verified SAT Solver Framework with Learn, Forget, Restart, and Incrementality IJCAI 2017 Backstitch: Counteracting Finite-Sample Bias via Negative Steps Interspeech 2017 Balancing information exposure in social networks NeurIPS 2017 Bandit Structured Prediction for Neural Sequence-to-Sequence Learning ACL 2017 Bandits with Movement Costs and Adaptive Pricing COLT 2017 Batched High-dimensional Bayesian Optimization via Structural Kernel Learning ICML 2017 Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models NeurIPS 2017 Bayesian Aggregation of Categorical Distributions with Applications in Crowdsourcing IJCAI 2017 Bayesian Compression for Deep Learning NeurIPS 2017 Bayesian Dynamic Mode Decomposition IJCAI 2017 Bayesian GAN NeurIPS 2017 Bayesian Hilbert Maps for Dynamic Continuous Occupancy Mapping CoRL 2017 Bayesian Hybrid Matrix Factorisation for Data Integration AISTATS 2017 Bayesian Inference for Spatio-temporal Spike-and-Slab Priors JMLR 2017