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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)

From Tempered to Benign Overfitting in ReLU Neural Networks NeurIPS 2023 From Understanding the Population Dynamics of the NSGA-II to the First Proven Lower Bounds AAAI 2023 FrozenRecon: Pose-free 3D Scene Reconstruction with Frozen Depth Models ICCV 2023 Frustratingly Easy Regularization on Representation Can Boost Deep Reinforcement Learning CVPR 2023 Frustratingly Easy Truth Discovery AAAI 2023 FULLER: Unified Multi-modality Multi-task 3D Perception via Multi-level Gradient Calibration ICCV 2023 Full Scaling Automation for Sustainable Development of Green Data Centers IJCAI 2023 Fully-Adaptive Composition in Differential Privacy ICML 2023 Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes ICML 2023 Fully-Dynamic Decision Trees AAAI 2023 Functional Distributional Semantics at Scale ACL 2023 Functional Equivalence and Path Connectivity of Reducible Hyperbolic Tangent Networks NeurIPS 2023 Functional L-Optimality Subsampling for Functional Generalized Linear Models with Massive Data JMLR 2023 Function Approximation for Solving Stackelberg Equilibrium in Large Perfect Information Games AAAI 2023 Function Space Bayesian Pseudocoreset for Bayesian Neural Networks NeurIPS 2023 Function-Space Regularization in Neural Networks: A Probabilistic Perspective ICML 2023 Function-space regularized Rényi divergences ICLR 2023 Fundamental limits and algorithms for sparse linear regression with sublinear sparsity JMLR 2023 Fundamental Limits in Formal Verification of Message-Passing Neural Networks ICLR 2023 Fundamental Limits of Two-layer Autoencoders, and Achieving Them with Gradient Methods ICML 2023 Fundamental limits on the robustness of image classifiers ICLR 2023 Fundamentals of Task-Agnostic Data Valuation AAAI 2023 Fundamental Tradeoffs in Learning with Prior Information ICML 2023 Further Adaptive Best-of-Both-Worlds Algorithm for Combinatorial Semi-Bandits AISTATS 2023 FV-Train: Quantum Convolutional Neural Network Training with a Finite Number of Qubits by Extracting Diverse Features (Student Abstract) AAAI 2023