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)

Towards Extracting Graph Neural Network Models via Prediction Queries (Student Abstract) AAAI 2021 Towards Flexible Device Participation in Federated Learning AISTATS 2021 Towards Generalized Implementation of Wasserstein Distance in GANs AAAI 2021 Towards Gradient-based Bilevel Optimization with Non-convex Followers and Beyond NeurIPS 2021 Towards Impartial Multi-task Learning ICLR 2021 Towards Improving the Consistency, Efficiency, and Flexibility of Differentiable Neural Architecture Search CVPR 2021 Towards Instance-Optimal Offline Reinforcement Learning with Pessimism NeurIPS 2021 Towards Learning Spatially Discriminative Feature Representations ICCV 2021 Towards Lower Bounds on the Depth of ReLU Neural Networks NeurIPS 2021 Towards Memory-Efficient Neural Networks via Multi-Level In Situ Generation ICCV 2021 Towards Mixed-Precision Quantization of Neural Networks via Constrained Optimization ICCV 2021 Towards More Fine-grained and Reliable NLP Performance Prediction EACL 2021 Towards More Practical and Efficient Automatic Dominance Breaking AAAI 2021 Towards Practical Mean Bounds for Small Samples ICML 2021 Towards Propagation Uncertainty: Edge-enhanced Bayesian Graph Convolutional Networks for Rumor Detection ACL 2021 Towards Reducing Biases in Combining Multiple Experts Online IJCAI 2021 Towards Resolving the Implicit Bias of Gradient Descent for Matrix Factorization: Greedy Low-Rank Learning ICLR 2021 Towards Robust Dynamic Network Embedding IJCAI 2021 Towards Robust Model Reuse in the Presence of Latent Domains IJCAI 2021 Towards Robustness of Deep Neural Networks via Regularization ICCV 2021 Towards Sample Efficient Agents through Algorithmic Alignment (Student Abstract) AAAI 2021 Towards Sample-Optimal Compressive Phase Retrieval with Sparse and Generative Priors NeurIPS 2021 Towards Scalable Complete Verification of Relu Neural Networks via Dependency-based Branching IJCAI 2021 Towards Sharper Generalization Bounds for Structured Prediction NeurIPS 2021 Towards Stable and Robust AdderNets NeurIPS 2021