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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)

Unbiased Learning-to-Rank with Biased Feedback IJCAI 2018 Unbiased Objective Estimation in Predictive Optimization ICML 2018 Uncertainty-aware generative models for inferring document class prevalence EMNLP 2018 Uncertainty Sampling is Preconditioned Stochastic Gradient Descent on Zero-One Loss NeurIPS 2018 Uncovering Causality from Multivariate Hawkes Integrated Cumulants JMLR 2018 Underdamped Langevin MCMC: A non-asymptotic analysis COLT 2018 Understanding and Simplifying One-Shot Architecture Search ICML 2018 Understanding Deep Learning Performance through an Examination of Test Set Difficulty: A Psychometric Case Study EMNLP 2018 Understanding Deep Neural Networks with Rectified Linear Units ICLR 2018 Understanding Generalization and Optimization Performance of Deep CNNs ICML 2018 Understanding Short-Horizon Bias in Stochastic Meta-Optimization ICLR 2018 Understanding the Loss Surface of Neural Networks for Binary Classification ICML 2018 Understanding Weight Normalized Deep Neural Networks with Rectified Linear Units NeurIPS 2018 Uniform Convergence of Gradients for Non-Convex Learning and Optimization NeurIPS 2018 Universal discrete-time reservoir computers with stochastic inputs and linear readouts using non-homogeneous state-affine systems JMLR 2018 Unleashing Linear Optimizers for Group-Fair Learning and Optimization COLT 2018 Unsupervised Image-to-Image Translation Using Domain-Specific Variational Information Bound NeurIPS 2018 Unsupervised Morphology Learning with Statistical Paradigms COLING 2018 Uplift Modeling from Separate Labels NeurIPS 2018 User-centric Evaluation of Automatic Punctuation in ASR Closed Captioning Interspeech 2018 Using Inherent Structures to design Lean 2-layer RBMs ICML 2018 Using J-K-fold Cross Validation To Reduce Variance When Tuning NLP Models COLING 2018 Using Large Ensembles of Control Variates for Variational Inference NeurIPS 2018 Using Linguistic Resources to Evaluate the Quality of Annotated Corpora COLING 2018 Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning ICML 2018