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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)

Equivalence of Segmental and Neural Transducer Modeling: A Proof of Concept Interspeech 2021 Equivariant Manifold Flows NeurIPS 2021 ERNIE-Doc: A Retrospective Long-Document Modeling Transformer ACL 2021 Error Compensated Distributed SGD Can Be Accelerated NeurIPS 2021 ErrorCompensatedX: error compensation for variance reduced algorithms NeurIPS 2021 Error-Sensitive Evaluation for Ordinal Target Variables EMNLP 2021 ESCAPED: Efficient Secure and Private Dot Product Framework for Kernel-based Machine Learning Algorithms with Applications in Healthcare AAAI 2021 Escape saddle points by a simple gradient-descent based algorithm NeurIPS 2021 Escaping from zero gradient: Revisiting action-constrained reinforcement learning via Frank-Wolfe policy optimization UAI 2021 Escaping Local Optima with Non-Elitist Evolutionary Algorithms AAAI 2021 Escaping Saddle Points with Compressed SGD NeurIPS 2021 Estimating $α$-Rank from A Few Entries with Low Rank Matrix Completion ICML 2021 Estimating and Evaluating Regression Predictive Uncertainty in Deep Object Detectors ICLR 2021 Estimating Calibrated Individualized Survival Curves with Deep Learning AAAI 2021 Estimating High Order Gradients of the Data Distribution by Denoising NeurIPS 2021 Estimating informativeness of samples with Smooth Unique Information ICLR 2021 Estimating Lipschitz constants of monotone deep equilibrium models ICLR 2021 Estimating Smooth GLM in Non-interactive Local Differential Privacy Model with Public Unlabeled Data ALT 2021 Estimating Subjective Crowd-Evaluations as an Additional Objective to Improve Natural Language Generation EACL 2021 Estimating the Lasso's Effective Noise JMLR 2021 Estimating the Number of Induced Subgraphs from Incomplete Data and Neighborhood Queries AAAI 2021 Estimating the Unique Information of Continuous Variables NeurIPS 2021 Estimating treatment effects with observed confounders and mediators UAI 2021 Estimating Uncertainty Intervals from Collaborating Networks JMLR 2021 Estimation and Inference for High Dimensional Generalized Linear Models: A Splitting and Smoothing Approach JMLR 2021