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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
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828
3,646
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2000
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Papers (including subtopics)

Simultaneous Inference for Massive Data: Distributed Bootstrap ICML 2020 Simultaneous Inference for Pairwise Graphical Models with Generalized Score Matching JMLR 2020 Simultaneously Learning Stochastic and Adversarial Episodic MDPs with Known Transition NeurIPS 2020 Simultaneous Translation Policies: From Fixed to Adaptive ACL 2020 Single Image Optical Flow Estimation With an Event Camera CVPR 2020 Sinkhorn Natural Gradient for Generative Models NeurIPS 2020 Sinkhorn Regression IJCAI 2020 SI-VDNAS: Semi-Implicit Variational Dropout for Hierarchical One-shot Neural Architecture Search IJCAI 2020 Sketching Transformed Matrices with Applications to Natural Language Processing AISTATS 2020 Slice Sampling for General Completely Random Measures UAI 2020 Slot-consistent NLG for Task-oriented Dialogue Systems with Iterative Rectification Network ACL 2020 SlowMo: Improving Communication-Efficient Distributed SGD with Slow Momentum ICLR 2020 Small Data, Big Decisions: Model Selection in the Small-Data Regime ICML 2020 Smaller, more accurate regression forests using tree alternating optimization ICML 2020 Small-GAN: Speeding up GAN Training using Core-Sets ICML 2020 Smart Forgetting for Safe Online Learning with Gaussian Processes L4DC 2020 Smart Predict-and-Optimize for Hard Combinatorial Optimization Problems AAAI 2020 SMART: Robust and Efficient Fine-Tuning for Pre-trained Natural Language Models through Principled Regularized Optimization ACL 2020 SM-NAS: Structural-to-Modular Neural Architecture Search for Object Detection AAAI 2020 Smooth Contextual Bandits: Bridging the Parametric and Non-differentiable Regret Regimes COLT 2020 Smoothed Analysis of Online and Differentially Private Learning NeurIPS 2020 Smoothed Nonparametric Derivative Estimation using Weighted Difference Quotients JMLR 2020 SmoothFool: An Efficient Framework for Computing Smooth Adversarial Perturbations WACV 2020 Smoothly Bounding User Contributions in Differential Privacy NeurIPS 2020 Smooth markets: A basic mechanism for organizing gradient-based learners ICLR 2020