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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)

ℓ_1-regression with Heavy-tailed Distributions NeurIPS 2018 3-in-1 Correlated Embedding via Adaptive Exploration of the Structure and Semantic Subspaces IJCAI 2018 A Bandit Approach to Sequential Experimental Design with False Discovery Control NeurIPS 2018 A Bayesian Approach for Inferring Local Causal Structure in Gene Regulatory Networks PGM 2018 A Bayesian Approach to Generative Adversarial Imitation Learning NeurIPS 2018 A Bayesian Latent Variable Model of User Preferences with Item Context IJCAI 2018 A Bayesian Nonparametric View on Count-Min Sketch NeurIPS 2018 A Bayesian Perspective on Generalization and Stochastic Gradient Descent ICLR 2018 A Better Resource Allocation Algorithm with Semi-Bandit Feedback ALT 2018 A Biresolution Spectral Framework for Product Quantization CVPR 2018 A Block Coordinate Ascent Algorithm for Mean-Variance Optimization NeurIPS 2018 A Boo(n) for Evaluating Architecture Performance ICML 2018 A Bridging Framework for Model Optimization and Deep Propagation NeurIPS 2018 A Causal And-Or Graph Model for Visibility Fluent Reasoning in Tracking Interacting Objects CVPR 2018 Accelerated Asynchronous Greedy Coordinate Descent Algorithm for SVMs IJCAI 2018 Accelerated Gradient Descent Escapes Saddle Points Faster than Gradient Descent COLT 2018 Accelerated Stochastic Matrix Inversion: General Theory and Speeding up BFGS Rules for Faster Second-Order Optimization NeurIPS 2018 Accelerated Stochastic Mirror Descent: From Continuous-time Dynamics to Discrete-time Algorithms AISTATS 2018 Accelerated Stochastic Power Iteration AISTATS 2018 Accelerating Asynchronous Stochastic Gradient Descent for Neural Machine Translation EMNLP 2018 Accelerating Cross-Validation in Multinomial Logistic Regression with ℓ_1-Regularization JMLR 2018 Accelerating Greedy Coordinate Descent Methods ICML 2018 Accelerating Natural Gradient with Higher-Order Invariance ICML 2018 Accelerating NMT Batched Beam Decoding with LMBR Posteriors for Deployment NAACL 2018 Accelerating Stochastic Gradient Descent for Least Squares Regression COLT 2018