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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)

Evidential Conditional Neural Processes AAAI 2023 EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning NeurIPS 2023 Evolutionary Neural Architecture Search for Multivariate Time Series Forecasting ACML 2023 Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing NeurIPS 2023 EvolveMT: an Ensemble MT Engine Improving Itself with Usage Only ACL 2023 EvoPrompting: Language Models for Code-Level Neural Architecture Search NeurIPS 2023 Exact Count of Boundary Pieces of ReLU Classifiers: Towards the Proper Complexity Measure for Classification UAI 2023 Exact Generalization Guarantees for (Regularized) Wasserstein Distributionally Robust Models NeurIPS 2023 Exact Gradient Computation for Spiking Neural Networks via Forward Propagation AISTATS 2023 Exact Inference in High-order Structured Prediction ICML 2023 Exact-NeRF: An Exploration of a Precise Volumetric Parameterization for Neural Radiance Fields CVPR 2023 Exact Optimality of Communication-Privacy-Utility Tradeoffs in Distributed Mean Estimation NeurIPS 2023 Exact recovery and Bregman hard clustering of node-attributed Stochastic Block Model NeurIPS 2023 Excess Risk of Two-Layer ReLU Neural Networks in Teacher-Student Settings and its Superiority to Kernel Methods ICLR 2023 Existence and Estimation of Critical Batch Size for Training Generative Adversarial Networks with Two Time-Scale Update Rule ICML 2023 ExoFlow: A Universal Workflow System for Exactly-Once DAGs OSDI 2023 Expectation consistency for calibration of neural networks UAI 2023 Expected Gradients of Maxout Networks and Consequences to Parameter Initialization ICML 2023 Experimental Designs for Heteroskedastic Variance NeurIPS 2023 Experimental Observations of the Topology of Convolutional Neural Network Activations AAAI 2023 Experiment Planning with Function Approximation NeurIPS 2023 Expertise Trees Resolve Knowledge Limitations in Collective Decision-Making ICML 2023 Expert load matters: operating networks at high accuracy and low manual effort NeurIPS 2023 Explainability as statistical inference ICML 2023 Explainable and Efficient Randomized Voting Rules NeurIPS 2023