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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)

Simple Hardware-Efficient Long Convolutions for Sequence Modeling ICML 2023 Simple Hardware-Efficient PCFGs with Independent Left and Right Productions EMNLP 2023 Simple initialization and parametrization of sinusoidal networks via their kernel bandwidth ICLR 2023 Simpler neural networks prefer subregular languages EMNLP 2023 Simple, Scalable and Effective Clustering via One-Dimensional Projections NeurIPS 2023 SIMPLE: Specialized Model-Sample Matching for Domain Generalization ICLR 2023 Simple Transferability Estimation for Regression Tasks UAI 2023 Simplex Random Features ICML 2023 Simplicity Bias in 1-Hidden Layer Neural Networks NeurIPS 2023 Simplicity Bias in Transformers and their Ability to Learn Sparse Boolean Functions ACL 2023 Simplified State Space Layers for Sequence Modeling ICLR 2023 Simplifying Momentum-based Positive-definite Submanifold Optimization with Applications to Deep Learning ICML 2023 Simulated Annealing in Early Layers Leads to Better Generalization CVPR 2023 Simulator-Based Inference with WALDO: Confidence Regions by Leveraging Prediction Algorithms and Posterior Estimators for Inverse Problems AISTATS 2023 Simultaneous embedding of multiple attractor manifolds in a recurrent neural network using constrained gradient optimization NeurIPS 2023 Simultaneous Learning of Contact and Continuous Dynamics CoRL 2023 Single-Call Stochastic Extragradient Methods for Structured Non-monotone Variational Inequalities: Improved Analysis under Weaker Conditions NeurIPS 2023 Single Image Depth Prediction Made Better: A Multivariate Gaussian Take CVPR 2023 Single Image Reflection Separation via Component Synergy ICCV 2023 Single Point-Based Distributed Zeroth-Order Optimization with a Non-Convex Stochastic Objective Function ICML 2023 Single-shot General Hyper-parameter Optimization for Federated Learning ICLR 2023 Single Timescale Actor-Critic Method to Solve the Linear Quadratic Regulator with Convergence Guarantees JMLR 2023 Singularformer: Learning to Decompose Self-Attention to Linearize the Complexity of Transformer IJCAI 2023 Sketched Ridgeless Linear Regression: The Role of Downsampling ICML 2023 Sketching Algorithms for Sparse Dictionary Learning: PTAS and Turnstile Streaming NeurIPS 2023