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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)

Newton Informed Neural Operator for Solving Nonlinear Partial Differential Equations NeurIPS 2024 Newton Losses: Using Curvature Information for Learning with Differentiable Algorithms NeurIPS 2024 N-gram-Based Preprocessing for Sandhi Reversion in Vedic Sanskrit EMNLP 2024 NICE: To Optimize In-Context Examples or Not? ACL 2024 NN4SysBench: Characterizing Neural Network Verification for Computer Systems NeurIPS 2024 Noether's Razor: Learning Conserved Quantities NeurIPS 2024 No Free Delivery Service: Epistemic limits of passive data collection in complex social systems NeurIPS 2024 No Free Lunch Theorem and Black-Box Complexity Analysis for Adversarial Optimisation NeurIPS 2024 No Free Prune: Information-Theoretic Barriers to Pruning at Initialization ICML 2024 No Internal Regret with Non-convex Loss Functions AAAI 2024 Noise-Adaptive Confidence Sets for Linear Bandits and Application to Bayesian Optimization ICML 2024 Noise-Aware Algorithm for Heterogeneous Differentially Private Federated Learning ICML 2024 Noise-Aware Differentially Private Regression via Meta-Learning NeurIPS 2024 Noise Contrastive Alignment of Language Models with Explicit Rewards NeurIPS 2024 Noise-Free Optimization in Early Training Steps for Image Super-resolution AAAI 2024 Noise-free Score Distillation ICLR 2024 Noisy Interpolation Learning with Shallow Univariate ReLU Networks ICLR 2024 Noisy Label Learning with Instance-Dependent Outliers: Identifiability via Crowd Wisdom NeurIPS 2024 Noisy One-point Homographies are Surprisingly Good CVPR 2024 Non-asymptotic Analysis of Biased Adaptive Stochastic Approximation NeurIPS 2024 Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization JMLR 2024 Non-asymptotic Approximation Error Bounds of Parameterized Quantum Circuits NeurIPS 2024 Non-asymptotic Convergence of Training Transformers for Next-token Prediction NeurIPS 2024 Non-asymptotic Global Convergence Analysis of BFGS with the Armijo-Wolfe Line Search NeurIPS 2024 Nonasymptotic regret analysis of adaptive linear quadratic control with model misspecification L4DC 2024