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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
352
828
3,646
5,854
2000
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Papers (including subtopics)

Non-Rigid Structure-from-Motion: Temporally-Smooth Procrustean Alignment and Spatially-Variant Deformation Modeling CVPR 2024 Nonsmooth Implicit Differentiation: Deterministic and Stochastic Convergence Rates ICML 2024 Non-splitting Neyman-Pearson Classifiers JMLR 2024 Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset NeurIPS 2024 Non-stationary Projection-Free Online Learning with Dynamic and Adaptive Regret Guarantees AAAI 2024 Nonstationary Sparse Spectral Permanental Process NeurIPS 2024 Non-transferable Pruning ECCV 2024 Non-vacuous Generalization Bounds for Adversarial Risk in Stochastic Neural Networks AISTATS 2024 Non-Vacuous Generalization Bounds for Large Language Models ICML 2024 No-Regret Algorithms for Safe Bayesian Optimization with Monotonicity Constraints AISTATS 2024 No-Regret Bandit Exploration based on Soft Tree Ensemble Model NeurIPS 2024 No-Regret Learning of Nash Equilibrium for Black-Box Games via Gaussian Processes UAI 2024 No-Regret M${}^{\natural}$-Concave Function Maximization: Stochastic Bandit Algorithms and NP-Hardness of Adversarial Full-Information Setting NeurIPS 2024 Normalization and effective learning rates in reinforcement learning NeurIPS 2024 Normalization Layer Per-Example Gradients are Sufficient to Predict Gradient Noise Scale in Transformers NeurIPS 2024 Normalized Narrow Jump To Conclusions: Normalized Narrow Shortcuts for Parameter Efficient Early Exit Transformer Prediction EMNLP 2024 Not all distributional shifts are equal: Fine-grained robust conformal inference ICML 2024 Not All Errors Are Made Equal: A Regret Metric for Detecting System-level Trajectory Prediction Failures CoRL 2024 Not All Learnable Distribution Classes are Privately Learnable ALT 2024 Not Everything is All You Need: Toward Low-Redundant Optimization for Large Language Model Alignment EMNLP 2024 NOTSOFAR-1 Challenge: New Datasets, Baseline, and Tasks for Distant Meeting Transcription Interspeech 2024 Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations ICLR 2024 Novelty vs. Potential Heuristics: A Comparison of Hardness Measures for Satisficing Planning AAAI 2024 NovoBench: Benchmarking Deep Learning-based \emph{De Novo} Sequencing Methods in Proteomics NeurIPS 2024 Nowcasting Temporal Trends Using Indirect Surveys AAAI 2024