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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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'25

Papers (including subtopics)

Learning and Collusion in Multi-unit Auctions NeurIPS 2023 Learning and Testing Latent-Tree Ising Models Efficiently COLT 2023 Learning a Neuron by a Shallow ReLU Network: Dynamics and Implicit Bias for Correlated Inputs NeurIPS 2023 Learning an Explicit Hyper-parameter Prediction Function Conditioned on Tasks JMLR 2023 Learning-Assisted Algorithm Unrolling for Online Optimization with Budget Constraints AAAI 2023 Learning-augmented count-min sketches via Bayesian nonparametrics JMLR 2023 Learning-augmented private algorithms for multiple quantile release ICML 2023 Learning Better Masking for Better Language Model Pre-training ACL 2023 Learning better with Dale’s Law: A Spectral Perspective NeurIPS 2023 Learning Calibrated Uncertainties for Domain Shift: A Distributionally Robust Learning Approach IJCAI 2023 Learning Compact Features via In-Training Representation Alignment AAAI 2023 Learning Compiler Pass Orders using Coreset and Normalized Value Prediction ICML 2023 Learning Constrained Structured Spaces with Application to Multi-Graph Matching AISTATS 2023 Learning Continuous Normalizing Flows For Faster Convergence To Target Distribution via Ascent Regularizations ICLR 2023 Learning Curves for Deep Structured Gaussian Feature Models NeurIPS 2023 Learning Curves for Noisy Heterogeneous Feature-Subsampled Ridge Ensembles NeurIPS 2023 Learning DAGs from Data with Few Root Causes NeurIPS 2023 Learning Decorrelated Representations Efficiently Using Fast Fourier Transform CVPR 2023 Learning Descriptive Image Captioning via Semipermeable Maximum Likelihood Estimation NeurIPS 2023 Learning differentiable solvers for systems with hard constraints ICLR 2023 Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval (Extended Abstract) IJCAI 2023 Learning Dissemination Strategies for External Sources in Opinion Dynamic Models with Cognitive Biases IJCAI 2023 Learning Distortion Invariant Representation for Image Restoration From a Causality Perspective CVPR 2023 Learning Distributions over Quantum Measurement Outcomes ICML 2023 Learning Disturbances Online for Risk-Aware Control: Risk-Aware Flight with Less Than One Minute of Data L4DC 2023