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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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2000
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Papers (including subtopics)

Last iterate convergence in no-regret learning: constrained min-max optimization for convex-concave landscapes AISTATS 2021 Last-iterate Convergence of Decentralized Optimistic Gradient Descent/Ascent in Infinite-horizon Competitive Markov Games COLT 2021 Last iterate convergence of SGD for Least-Squares in the Interpolation regime. NeurIPS 2021 Last-Iterate Convergence Rates for Min-Max Optimization: Convergence of Hamiltonian Gradient Descent and Consensus Optimization ALT 2021 Last Round Convergence and No-Dynamic Regret in Asymmetric Repeated Games ALT 2021 Latent Convergent Cross Mapping ICLR 2021 Latent Equilibrium: A unified learning theory for arbitrarily fast computation with arbitrarily slow neurons NeurIPS 2021 Latent Gaussian process with composite likelihoods and numerical quadrature AISTATS 2021 Latent Matters: Learning Deep State-Space Models NeurIPS 2021 Lattice partition recovery with dyadic CART NeurIPS 2021 Layer-wise Model Pruning based on Mutual Information EMNLP 2021 Layerwise Optimization by Gradient Decomposition for Continual Learning CVPR 2021 Layer-Wise Searching for 1-Bit Detectors CVPR 2021 Lazy OCO: Online Convex Optimization on a Switching Budget COLT 2021 LB-DESPOT: Efficient Online POMDP Planning Considering Lower Bound in Action Selection (Student Abstract) AAAI 2021 Learn2Hop: Learned Optimization on Rough Landscapes ICML 2021 Learnability of Linear Thresholds from Label Proportions NeurIPS 2021 Learnable Companding Quantization for Accurate Low-Bit Neural Networks CVPR 2021 Learnable Graph Matching: Incorporating Graph Partitioning With Deep Feature Learning for Multiple Object Tracking CVPR 2021 Learnable uncertainty under Laplace approximations UAI 2021 Learned Extragradient ISTA with Interpretable Residual Structures for Sparse Coding AAAI 2021 Learned Initializations for Optimizing Coordinate-Based Neural Representations CVPR 2021 Learner-Private Convex Optimization ICML 2021 Learning 3-opt heuristics for traveling salesman problem via deep reinforcement learning ACML 2021 Learning Accurate Dense Correspondences and When To Trust Them CVPR 2021