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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)

Differential Privacy Dynamics of Langevin Diffusion and Noisy Gradient Descent NeurIPS 2021 Differentiating the Value Function by using Convex Duality AISTATS 2021 Diffusion Probabilistic Models for 3D Point Cloud Generation CVPR 2021 Diffusion Schrödinger Bridge with Applications to Score-Based Generative Modeling NeurIPS 2021 Diffusion Source Identification on Networks with Statistical Confidence ICML 2021 Dimension-free empirical entropy estimation NeurIPS 2021 Dimension reduction for data with heterogeneous missingness UAI 2021 DiNTS: Differentiable Neural Network Topology Search for 3D Medical Image Segmentation CVPR 2021 Direct Differentiable Augmentation Search ICCV 2021 Direct Inference of Cell Positions using Lens-Free Microscopy and Deep Learning MIDL 2021 Directional Bias Amplification ICML 2021 Direction is what you need: Improving Word Embedding Compression in Large Language Models ACL 2021 Direction Matters: On the Implicit Bias of Stochastic Gradient Descent with Moderate Learning Rate ICLR 2021 Direct Loss Minimization for Sparse Gaussian Processes AISTATS 2021 Dirichlet Energy Constrained Learning for Deep Graph Neural Networks NeurIPS 2021 Dirichlet Pruning for Convolutional Neural Networks AISTATS 2021 Disambiguatory Signals are Stronger in Word-initial Positions EACL 2021 Discerning Decision-Making Process of Deep Neural Networks with Hierarchical Voting Transformation NeurIPS 2021 Discovering a set of policies for the worst case reward ICLR 2021 Discovering Better Model Architectures for Medical Query Understanding NAACL 2021 Discrete-Valued Latent Preference Matrix Estimation with Graph Side Information ICML 2021 Discretization Drift in Two-Player Games ICML 2021 Discretized Integrated Gradients for Explaining Language Models EMNLP 2021 DiSECt: A Differentiable Simulation Engine for Autonomous Robotic Cutting RSS 2021 Disentangled Contour Learning for Quadrilateral Text Detection WACV 2021