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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)

QPLEX: Duplex Dueling Multi-Agent Q-Learning ICLR 2021 Quantifying and Improving Transferability in Domain Generalization NeurIPS 2021 Quantifying and Reducing Bias in Maximum Likelihood Estimation of Structured Anomalies ICML 2021 Quantifying Availability and Discovery in Recommender Systems via Stochastic Reachability ICML 2021 Quantifying Contextual Aspects of Inter-annotator Agreement in Intertextuality Research EMNLP 2021 Quantifying Ignorance in Individual-Level Causal-Effect Estimates under Hidden Confounding ICML 2021 Quantifying the Benefit of Using Differentiable Learning over Tangent Kernels ICML 2021 Quantifying the Privacy Risks of Learning High-Dimensional Graphical Models AISTATS 2021 Quantifying Variational Approximation for Log-Partition Function COLT 2021 Quantile Bandits for Best Arms Identification ICML 2021 Quantitative Understanding of VAE as a Non-linearly Scaled Isometric Embedding ICML 2021 Quantization Algorithms for Random Fourier Features ICML 2021 Quantum algorithms for reinforcement learning with a generative model ICML 2021 Quantum Tensor Networks, Stochastic Processes, and Weighted Automata AISTATS 2021 Quasi-global Momentum: Accelerating Decentralized Deep Learning on Heterogeneous Data ICML 2021 Quasi-Monte Carlo Quasi-Newton in Variational Bayes JMLR 2021 Query Complexity of Adversarial Attacks ICML 2021 Query complexity of least absolute deviation regression via robust uniform convergence COLT 2021 Query Training: Learning a Worse Model to Infer Better Marginals in Undirected Graphical Models with Hidden Variables AAAI 2021 Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning EMNLP 2021 Random Coordinate Langevin Monte Carlo COLT 2021 Randomized Algorithms for Submodular Function Maximization with a k-System Constraint ICML 2021 Randomized Automatic Differentiation ICLR 2021 Randomized Deep Structured Prediction for Discourse-Level Processing EACL 2021 Randomized Exploration in Reinforcement Learning with General Value Function Approximation ICML 2021