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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)

Embedding Words as Distributions with a Bayesian Skip-gram Model COLING 2018 Emergence of Invariance and Disentanglement in Deep Representations JMLR 2018 Empirical bounds for functions with weak interactions COLT 2018 Empirical Risk Landscape Analysis for Understanding Deep Neural Networks ICLR 2018 Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited NeurIPS 2018 Empirical Study of the Topology and Geometry of Deep Networks CVPR 2018 End-to-End Differentiable Physics for Learning and Control NeurIPS 2018 Energy-Based Hindsight Experience Prioritization CoRL 2018 Energy-efficient Amortized Inference with Cascaded Deep Classifiers IJCAI 2018 Enhanced-alignment Measure for Binary Foreground Map Evaluation IJCAI 2018 Enhancing Existential Rules by Closed-World Variables IJCAI 2018 Ensemble Soft-Margin Softmax Loss for Image Classification IJCAI 2018 Entropy and mutual information in models of deep neural networks NeurIPS 2018 Entropy Rate Estimation for Markov Chains with Large State Space NeurIPS 2018 Entropy-SGD optimizes the prior of a PAC-Bayes bound: Generalization properties of Entropy-SGD and data-dependent priors ICML 2018 Environment Upgrade Reinforcement Learning for Non-Differentiable Multi-Stage Pipelines CVPR 2018 Error Compensated Quantized SGD and its Applications to Large-scale Distributed Optimization ICML 2018 Error Modeling via Asymmetric Laplace Distribution for Deep Neural Network Based Single-Channel Speech Enhancement Interspeech 2018 Escaping Saddle Points in Constrained Optimization NeurIPS 2018 Escaping Saddles with Stochastic Gradients ICML 2018 Essentially No Barriers in Neural Network Energy Landscape ICML 2018 Estimating Latent People Flow without Tracking Individuals IJCAI 2018 Estimating Learnability in the Sublinear Data Regime NeurIPS 2018 Estimation of Camera Locations in Highly Corrupted Scenarios: All About That Base, No Shape Trouble CVPR 2018 Estimation of Graphical Models through Structured Norm Minimization JMLR 2018