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

14

29

44

31

52

189

195

212

235

352

382

457

787

816

828

1,066

1,391

1,913

3,012

3,646

4,303

4,450

5,357

6,155

5,854

1,521

2000

'5

'10

'15

'20

'25

Papers (including subtopics)

Feature selection using e-values ICML 2022 Feature Space Particle Inference for Neural Network Ensembles ICML 2022 FedAvg with Fine Tuning: Local Updates Lead to Representation Learning NeurIPS 2022 FedCC: Federated Learning with Consensus Confirmation for Byzantine Attack Resistance (Student Abstract) AAAI 2022 FedChain: Chained Algorithms for Near-optimal Communication Cost in Federated Learning ICLR 2022 FedCor: Correlation-Based Active Client Selection Strategy for Heterogeneous Federated Learning CVPR 2022 FedDC: Federated Learning With Non-IID Data via Local Drift Decoupling and Correction CVPR 2022 Federated Learning for Face Recognition with Gradient Correction AAAI 2022 Federated Learning with Buffered Asynchronous Aggregation AISTATS 2022 Federated Learning with Label Distribution Skew via Logits Calibration ICML 2022 Federated Learning with Partial Model Personalization ICML 2022 Federated Minimax Optimization: Improved Convergence Analyses and Algorithms ICML 2022 Federated Myopic Community Detection with One-shot Communication AISTATS 2022 Federated Pruning: Improving Neural Network Efficiency with Federated Learning Interspeech 2022 Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling ICML 2022 Federated Submodel Optimization for Hot and Cold Data Features NeurIPS 2022 FedNest: Federated Bilevel, Minimax, and Compositional Optimization ICML 2022 FedNew: A Communication-Efficient and Privacy-Preserving Newton-Type Method for Federated Learning ICML 2022 FedNL: Making Newton-Type Methods Applicable to Federated Learning ICML 2022 FedNST: Federated Noisy Student Training for Automatic Speech Recognition Interspeech 2022 FedPop: A Bayesian Approach for Personalised Federated Learning NeurIPS 2022 FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction NeurIPS 2022 FedScale: Benchmarking Model and System Performance of Federated Learning at Scale ICML 2022 Fedvarp: Tackling the variance due to partial client participation in federated learning UAI 2022 Feedback Gradient Descent: Efficient and Stable Optimization with Orthogonality for DNNs AAAI 2022