Skip to content
conftrace_

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
'5
'10
'15
'20
'25

Papers (including subtopics)

Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models NeurIPS 2021 Representer Theorems in Banach Spaces: Minimum Norm Interpolation, Regularized Learning and Semi-Discrete Inverse Problems JMLR 2021 Representing Hyperbolic Space Accurately using Multi-Component Floats NeurIPS 2021 RepVGG: Making VGG-Style ConvNets Great Again CVPR 2021 Research Reproducibility as a Survival Analysis AAAI 2021 Reservoir Transformers ACL 2021 Residual Pathway Priors for Soft Equivariance Constraints NeurIPS 2021 ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees NeurIPS 2021 ResNet After All: Neural ODEs and Their Numerical Solution ICLR 2021 ResNet or DenseNet? Introducing Dense Shortcuts to ResNet WACV 2021 Responsibility Attribution in Parameterized Markovian Models AAAI 2021 Results of the WMT21 Metrics Shared Task: Evaluating Metrics with Expert-based Human Evaluations on TED and News Domain EMNLP 2021 Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization NeurIPS 2021 Rethinking Attention with Performers ICLR 2021 Rethinking Bi-Level Optimization in Neural Architecture Search: A Gibbs Sampling Perspective AAAI 2021 Rethinking BiSeNet for Real-Time Semantic Segmentation CVPR 2021 Rethinking Calibration of Deep Neural Networks: Do Not Be Afraid of Overconfidence NeurIPS 2021 Rethinking Channel Dimensions for Efficient Model Design CVPR 2021 Rethinking Deep Image Prior for Denoising ICCV 2021 Rethinking gradient sparsification as total error minimization NeurIPS 2021 Rethinking Neural Operations for Diverse Tasks NeurIPS 2021 Rethinking Perturbations in Encoder-Decoders for Fast Training NAACL 2021 Rethinking Rotated Object Detection with Gaussian Wasserstein Distance Loss ICML 2021 Rethinking Soft Labels for Knowledge Distillation: A Bias–Variance Tradeoff Perspective ICLR 2021 Rethinking the Pruning Criteria for Convolutional Neural Network NeurIPS 2021