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)

Unbiased Contrastive Divergence Algorithm for Training Energy-Based Latent Variable Models ICLR 2020 Unbiased Risk Estimators Can Mislead: A Case Study of Learning with Complementary Labels ICML 2020 Uncertain multi-agent MILPs: A data-driven decentralized solution with probabilistic feasibility guarantees L4DC 2020 Uncertainty-Aware CNNs for Depth Completion: Uncertainty from Beginning to End CVPR 2020 Uncertainty-Aware Constraint Learning for Adaptive Safe Motion Planning from Demonstrations CoRL 2020 Uncertainty-Aware Curriculum Learning for Neural Machine Translation ACL 2020 Uncertainty-Aware Deep Classifiers Using Generative Models AAAI 2020 Uncertainty-Aware Label Refinement for Sequence Labeling EMNLP 2020 Uncertainty-Aware Learning for Zero-Shot Semantic Segmentation NeurIPS 2020 Uncertainty-Aware Lookahead Factor Models for Quantitative Investing ICML 2020 Uncertainty-Aware Machine Support for Paper Reviewing on the Interspeech 2019 Submission Corpus Interspeech 2020 Uncertainty-Aware Multi-Shot Knowledge Distillation for Image-Based Object Re-Identification AAAI 2020 Uncertainty-Aware Search Framework for Multi-Objective Bayesian Optimization AAAI 2020 Uncertainty-aware Self-training for Few-shot Text Classification NeurIPS 2020 Uncertainty Aware Semi-Supervised Learning on Graph Data NeurIPS 2020 Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving WACV 2020 Uncertainty-Aware Training of Neural Networks for Selective Medical Image Segmentation MIDL 2020 Uncertainty Based Camera Model Selection CVPR 2020 Uncertainty-guided Continual Learning with Bayesian Neural Networks ICLR 2020 Uncertainty in Model-Agnostic Meta-Learning using Variational Inference WACV 2020 Uncertainty in Neural Networks: Approximately Bayesian Ensembling AISTATS 2020 Uncertainty Quantification for Inferring Hawkes Networks NeurIPS 2020 Uncertainty quantification for nonconvex tensor completion: Confidence intervals, heteroscedasticity and optimality ICML 2020 Uncertainty Quantification for Sparse Deep Learning AISTATS 2020 Unconditional Audio Generation with Generative Adversarial Networks and Cycle Regularization Interspeech 2020