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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)

Learning a Gradient-free Riemannian Optimizer on Tangent Spaces AAAI 2021 Learning a High-dimensional Linear Structural Equation Model via l1-Regularized Regression JMLR 2021 Learning a Latent Search Space for Routing Problems using Variational Autoencoders ICLR 2021 Learning a Latent Simplex in Input Sparsity Time ICLR 2021 Learning A Minimax Optimizer: A Pilot Study ICLR 2021 Learning a mixture of two subspaces over finite fields ALT 2021 Learning and Analyzing Generation Order for Undirected Sequence Models EMNLP 2021 Learning and certification under instance-targeted poisoning UAI 2021 Learning and Generalization in RNNs NeurIPS 2021 Learning and Planning in Average-Reward Markov Decision Processes ICML 2021 Learning and Planning Under Uncertainty for Green Security IJCAI 2021 Learning and Testing Irreducible Markov Chains via the k-Cover Time ALT 2021 Learning and testing junta distributions with sub cube conditioning COLT 2021 Learning an Explicit Weighting Scheme for Adapting Complex HSI Noise CVPR 2021 Learning a Non-Blind Deblurring Network for Night Blurry Images CVPR 2021 Learning Artificial Intelligence: Insights into How Youth Encounter and Build Understanding of AI Concepts AAAI 2021 Learning a Single Neuron with Bias Using Gradient Descent NeurIPS 2021 Learning-Augmented Dynamic Power Management with Multiple States via New Ski Rental Bounds NeurIPS 2021 Learning Augmented Methods for Matching: Improving Invasive Species Management and Urban Mobility AAAI 2021 Learning-based State Reconstruction for a Scalar Hyperbolic PDE under noisy Lagrangian Sensing L4DC 2021 Learning Bayesian Networks from Ordinal Data JMLR 2021 Learning Better Structured Representations Using Low-rank Adaptive Label Smoothing ICLR 2021 Learning Bounds for Open-Set Learning ICML 2021 Learning Branching Heuristics for Propositional Model Counting AAAI 2021 Learning by Turning: Neural Architecture Aware Optimisation ICML 2021