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)

Top-m identification for linear bandits AISTATS 2021 Topological Machine Learning Methods for Power System Responses to Contingencies AAAI 2021 To Ship or Not to Ship: An Extensive Evaluation of Automatic Metrics for Machine Translation EMNLP 2021 To The Point: Correspondence-driven monocular 3D category reconstruction NeurIPS 2021 Toward a General Theory of Online Selective Sampling: Trading Off Mistakes and Queries AISTATS 2021 Toward Better Generalization Bounds with Locally Elastic Stability ICML 2021 Toward Nearly-Zero-Error Sketching via Compressive Sensing NSDI 2021 Toward Optimal Solution for the Context-Attentive Bandit Problem IJCAI 2021 Towards a Dimension-Free Understanding of Adaptive Linear Control COLT 2021 Towards a Theoretical Framework of Out-of-Distribution Generalization NeurIPS 2021 Towards a Theoretical Understanding of the Robustness of Variational Autoencoders AISTATS 2021 Towards a Unified Analysis of Random Fourier Features JMLR 2021 Towards a unified framework for fair and stable graph representation learning UAI 2021 Towards a Unified Game-Theoretic View of Adversarial Perturbations and Robustness NeurIPS 2021 Towards a Unified Information-Theoretic Framework for Generalization NeurIPS 2021 Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples NeurIPS 2021 Towards Biologically Plausible Convolutional Networks NeurIPS 2021 Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective NeurIPS 2021 Towards Compact CNNs via Collaborative Compression CVPR 2021 Towards Context-Agnostic Learning Using Synthetic Data NeurIPS 2021 Towards Deeper Deep Reinforcement Learning with Spectral Normalization NeurIPS 2021 Towards Document-Level Human MT Evaluation: On the Issues of Annotator Agreement, Effort and Misevaluation EACL 2021 Towards Efficient Selection of Activity Trajectories based on Diversity and Coverage AAAI 2021 Towards Efficient Tensor Decomposition-Based DNN Model Compression With Optimization Framework CVPR 2021 Towards Evaluating and Training Verifiably Robust Neural Networks CVPR 2021