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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

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52
352
828
3,646
5,854
2000
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Papers (including subtopics)

A Unified Analysis of Stochastic Momentum Methods for Deep Learning IJCAI 2018 A Unified Approach for Multi-step Temporal-Difference Learning with Eligibility Traces in Reinforcement Learning IJCAI 2018 A Unified Dynamic Approach to Sparse Model Selection AISTATS 2018 A Unified Framework for Extensive-Form Game Abstraction with Bounds NeurIPS 2018 A Unified Framework for Nonconvex Low-Rank plus Sparse Matrix Recovery AISTATS 2018 A Unified View of Piecewise Linear Neural Network Verification NeurIPS 2018 Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language NeurIPS 2018 Auto-Encoding Sequential Monte Carlo ICLR 2018 Automatically Selecting the Best Dependency Annotation Design with Dynamic Oracles NAACL 2018 Automatic Differentiation in Machine Learning: a Survey JMLR 2018 Automatic differentiation in ML: Where we are and where we should be going NeurIPS 2018 Automatic DNN Node Pruning Using Mixture Distribution-based Group Regularization Interspeech 2018 Automatic Metric Validation for Grammatical Error Correction ACL 2018 Automatic Poetry Generation with Mutual Reinforcement Learning EMNLP 2018 Automating Bayesian optimization with Bayesian optimization NeurIPS 2018 AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning ICML 2018 Average Stability is Invariant to Data Preconditioning. Implications to Exp-concave Empirical Risk Minimization JMLR 2018 Averaging Stochastic Gradient Descent on Riemannian Manifolds COLT 2018 Avoiding Speaker Overfitting in End-to-End DNNs Using Raw Waveform for Text-Independent Speaker Verification Interspeech 2018 Backpropagating through Structured Argmax using a SPIGOT ACL 2018 Backpropagation through the Void: Optimizing control variates for black-box gradient estimation ICLR 2018 Backpropagation with Callbacks: Foundations for Efficient and Expressive Differentiable Programming NeurIPS 2018 Back to Basics: Benchmarking Canonical Evolution Strategies for Playing Atari IJCAI 2018 Back-Translation Sampling by Targeting Difficult Words in Neural Machine Translation EMNLP 2018 Balanced Policy Evaluation and Learning NeurIPS 2018