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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)

Understanding the Generalization Ability of Deep Learning Algorithms: A Kernelized Rényi's Entropy Perspective IJCAI 2023 Understanding the Generalization of Adam in Learning Neural Networks with Proper Regularization ICLR 2023 Understanding the Generalization Performance of Spectral Clustering Algorithms AAAI 2023 Understanding the Impact of Adversarial Robustness on Accuracy Disparity ICML 2023 Understanding the Impact of Competing Events on Heterogeneous Treatment Effect Estimation from Time-to-Event Data AISTATS 2023 Understanding the Inner-workings of Language Models Through Representation Dissimilarity EMNLP 2023 Understanding the Role of Feedback in Online Learning with Switching Costs ICML 2023 Understanding the Role of Nonlinearity in Training Dynamics of Contrastive Learning ICLR 2023 Understanding Train-Validation Split in Meta-Learning with Neural Networks ICLR 2023 Understanding weight-magnitude hyperparameters in training binary networks ICLR 2023 Understanding Why Generalized Reweighting Does Not Improve Over ERM ICLR 2023 Undirected Probabilistic Model for Tensor Decomposition NeurIPS 2023 Unexpected Improvements to Expected Improvement for Bayesian Optimization NeurIPS 2023 Unfolding Framework with Prior of Convolution-Transformer Mixture and Uncertainty Estimation for Video Snapshot Compressive Imaging ICCV 2023 UniFace: Unified Cross-Entropy Loss for Deep Face Recognition ICCV 2023 Unified Embedding: Battle-Tested Feature Representations for Web-Scale ML Systems NeurIPS 2023 Unified Enhancement of Privacy Bounds for Mixture Mechanisms via f-Differential Privacy NeurIPS 2023 Unified Lower Bounds for Interactive High-dimensional Estimation under Information Constraints NeurIPS 2023 Unified Low-Resource Sequence Labeling by Sample-Aware Dynamic Sparse Finetuning EMNLP 2023 Unified Out-Of-Distribution Detection: A Model-Specific Perspective ICCV 2023 Unified Perspective on Probability Divergence via the Density-Ratio Likelihood: Bridging KL-Divergence and Integral Probability Metrics AISTATS 2023 Uniform Convergence with Square-Root Lipschitz Loss NeurIPS 2023 Uniform-in-time propagation of chaos for the mean-field gradient Langevin dynamics ICLR 2023 Uniform-in-Time Wasserstein Stability Bounds for (Noisy) Stochastic Gradient Descent NeurIPS 2023 Uniform-PAC Guarantees for Model-Based RL with Bounded Eluder Dimension UAI 2023