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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
5,854
2000
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Papers (including subtopics)

Graph Neural Architecture Search IJCAI 2020 Graph Neural Networks Meet Neural-Symbolic Computing: A Survey and Perspective IJCAI 2020 Graph Optimal Transport for Cross-Domain Alignment ICML 2020 Graph Structure of Neural Networks ICML 2020 Greedy inference with structure-exploiting lazy maps NeurIPS 2020 Greedy Optimization Provably Wins the Lottery: Logarithmic Number of Winning Tickets is Enough NeurIPS 2020 Group-Fair Online Allocation in Continuous Time NeurIPS 2020 Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression CVPR 2020 Growing Adaptive Multi-hyperplane Machines ICML 2020 Gryff: Unifying Consensus and Shared Registers NSDI 2020 Guaranteed Validity for Empirical Approaches to Adaptive Data Analysis AISTATS 2020 Guided Learning of Nonconvex Models through Successive Functional Gradient Optimization ICML 2020 Guiding CDCL SAT Search via Random Exploration amid Conflict Depression AAAI 2020 Guiding Deep Molecular Optimization with Genetic Exploration NeurIPS 2020 Guoym at SemEval-2020 Task 8: Ensemble-based Classification of Visuo-Lingual Metaphor in Memes SemEval 2020 HAL: Improved Text-Image Matching by Mitigating Visual Semantic Hubs AAAI 2020 Halpern Iteration for Near-Optimal and Parameter-Free Monotone Inclusion and Strong Solutions to Variational Inequalities COLT 2020 Hamiltonian Monte Carlo Swindles AISTATS 2020 Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation: Bayesian inference for latent Gaussian models and beyond NeurIPS 2020 Handling the Positive-Definite Constraint in the Bayesian Learning Rule ICML 2020 Hardness of Identity Testing for Restricted Boltzmann Machines and Potts models COLT 2020 Hardness of Learning Neural Networks with Natural Weights NeurIPS 2020 Hardware as Policy: Mechanical and Computational Co-Optimization using Deep Reinforcement Learning CoRL 2020 Hardware-in-the-Loop End-to-End Optimization of Camera Image Processing Pipelines CVPR 2020 HARK: Harshness-Aware Sentiment Analysis Framework for Product Review (Student Abstract) AAAI 2020