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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
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2000
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Papers (including subtopics)

NIRVANA: Neural Implicit Representations of Videos With Adaptive Networks and Autoregressive Patch-Wise Modeling CVPR 2023 NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark EMNLP 2023 “No Free Lunch” in Neural Architectures? A Joint Analysis of Expressivity, Convergence, and Generalization AutoML 2023 Noise-Adaptive Thompson Sampling for Linear Contextual Bandits NeurIPS 2023 Noise-Aware Statistical Inference with Differentially Private Synthetic Data AISTATS 2023 Noisy Low-rank Matrix Optimization: Geometry of Local Minima and Convergence Rate AISTATS 2023 NoisyQuant: Noisy Bias-Enhanced Post-Training Activation Quantization for Vision Transformers CVPR 2023 NoisywikiHow: A Benchmark for Learning with Real-world Noisy Labels in Natural Language Processing ACL 2023 Non-adversarial training of Neural SDEs with signature kernel scores NeurIPS 2023 Non-Asymptotic Analysis of a UCB-based Top Two Algorithm NeurIPS 2023 Non-asymptotic convergence bounds for Sinkhorn iterates and their gradients: a coupling approach. COLT 2023 Non-Asymptotic Guarantees for Robust Statistical Learning under Infinite Variance Assumption JMLR 2023 Non-autoregressive Streaming Transformer for Simultaneous Translation EMNLP 2023 Non-Convex Bilevel Optimization with Time-Varying Objective Functions NeurIPS 2023 Nonconvex stochastic scaled gradient descent and generalized eigenvector problems UAI 2023 Non-exponential Reward Discounting in Reinforcement Learning AAAI 2023 Nonlinear Advantage: Trained Networks Might Not Be As Complex as You Think ICML 2023 Nonlinear Controllability and Function Representation by Neural Stochastic Differential Equations L4DC 2023 Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities ICLR 2023 Nonmyopic Multiclass Active Search with Diminishing Returns for Diverse Discovery AISTATS 2023 Nonparametric Boundary Geometry in Physics Informed Deep Learning NeurIPS 2023 Nonparametric Density Estimation under Distribution Drift ICML 2023 Nonparametric Gaussian Process Covariances via Multidimensional Convolutions AISTATS 2023 Nonparametric Generative Modeling with Conditional Sliced-Wasserstein Flows ICML 2023 Non-parametric identifiability and sensitivity analysis of synthetic control models CLeaR 2023