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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)

Generalized Tensor Models for Recurrent Neural Networks ICLR 2019 General Proximal Incremental Aggregated Gradient Algorithms: Better and Novel Results under General Scheme NeurIPS 2019 Generating and Sampling Orbits for Lifted Probabilistic Inference UAI 2019 Generating Classical Chinese Poems from Vernacular Chinese EMNLP 2019 Generative Modeling by Estimating Gradients of the Data Distribution NeurIPS 2019 Generic Inference in Latent Gaussian Process Models JMLR 2019 GENO -- GENeric Optimization for Classical Machine Learning NeurIPS 2019 Geometric Hawkes Processes with Graph Convolutional Recurrent Neural Networks AAAI 2019 Geometry-Aware Maximum Likelihood Estimation of Intrinsic Dimension ACML 2019 Geometry Normalization Networks for Accurate Scene Text Detection ICCV 2019 GEval: Tool for Debugging NLP Datasets and Models ACL 2019 GIRNet: Interleaved Multi-Task Recurrent State Sequence Models AAAI 2019 Global Autoregressive Models for Data-Efficient Sequence Learning CoNLL 2019 Global Convergence of Block Coordinate Descent in Deep Learning ICML 2019 Global Convergence of Gradient Descent for Deep Linear Residual Networks NeurIPS 2019 Global Convergence of Least Squares EM for Demixing Two Log-Concave Densities NeurIPS 2019 Global Convergence of the EM Algorithm for Mixtures of Two Component Linear Regression COLT 2019 Global Guarantees for Blind Demodulation with Generative Priors NeurIPS 2019 Globally Convergent Newton Methods for Ill-conditioned Generalized Self-concordant Losses NeurIPS 2019 Globally Optimal Learning for Structured Elliptical Losses NeurIPS 2019 Globally optimal score-based learning of directed acyclic graphs in high-dimensions NeurIPS 2019 Global Reasoning over Database Structures for Text-to-SQL Parsing EMNLP 2019 Global Robustness Evaluation of Deep Neural Networks with Provable Guarantees for the Hamming Distance IJCAI 2019 Global Sparse Momentum SGD for Pruning Very Deep Neural Networks NeurIPS 2019 Goal-Oriented End-to-End Conversational Models with Profile Features in a Real-World Setting NAACL 2019