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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)

Deep Statistical Solvers NeurIPS 2020 Deep Stereo Using Adaptive Thin Volume Representation With Uncertainty Awareness CVPR 2020 Deep Structured Mixtures of Gaussian Processes AISTATS 2020 Deep Symbolic Superoptimization Without Human Knowledge ICLR 2020 Deep Time-Stream Framework for Click-through Rate Prediction by Tracking Interest Evolution AAAI 2020 Deep Transformers with Latent Depth NeurIPS 2020 Deep Unfolding Network for Image Super-Resolution CVPR 2020 DeepView: Visualizing Classification Boundaries of Deep Neural Networks as Scatter Plots Using Discriminative Dimensionality Reduction IJCAI 2020 Deep Weighted MaxSAT for Aspect-based Opinion Extraction EMNLP 2020 Defense Through Diverse Directions ICML 2020 Delay-Adaptive Distributed Stochastic Optimization AAAI 2020 Delay and Cooperation in Nonstochastic Linear Bandits NeurIPS 2020 DeltaGrad: Rapid retraining of machine learning models ICML 2020 Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians NeurIPS 2020 Demo Application for the AutoGOAL Framework COLING 2020 Dempster-Shafer Theoretic Learning of Indirect Speech Act Comprehension Norms AAAI 2020 Demystifying Orthogonal Monte Carlo and Beyond NeurIPS 2020 Denoising and Regularization via Exploiting the Structural Bias of Convolutional Generators ICLR 2020 Densely Connected Search Space for More Flexible Neural Architecture Search CVPR 2020 Density-Based Clustering for 3D Object Detection in Point Clouds CVPR 2020 Depth Completion via Deep Basis Fitting WACV 2020 Depth Uncertainty in Neural Networks NeurIPS 2020 Depth-Width Trade-offs for ReLU Networks via Sharkovsky's Theorem ICLR 2020 (De)Randomized Smoothing for Certifiable Defense against Patch Attacks NeurIPS 2020 Derivative-Free & Order-Robust Optimisation AISTATS 2020