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

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1,391

1,913

3,012

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6,155

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Papers (including subtopics)

Feature selection and low test error in shallow low-rotation ReLU networks ICLR 2023 FedALA: Adaptive Local Aggregation for Personalized Federated Learning AAAI 2023 FedAvg Converges to Zero Training Loss Linearly for Overparameterized Multi-Layer Neural Networks ICML 2023 Fed-CBS: A Heterogeneity-Aware Client Sampling Mechanism for Federated Learning via Class-Imbalance Reduction ICML 2023 FedDisco: Federated Learning with Discrepancy-Aware Collaboration ICML 2023 FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning CVPR 2023 FedDWA: Personalized Federated Learning with Dynamic Weight Adjustment IJCAI 2023 Federated Adversarial Learning: A Framework with Convergence Analysis ICML 2023 Federated Asymptotics: a model to compare federated learning algorithms AISTATS 2023 Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms AISTATS 2023 Federated Compositional Deep AUC Maximization NeurIPS 2023 Federated Conditional Stochastic Optimization NeurIPS 2023 Federated Heavy Hitter Recovery under Linear Sketching ICML 2023 Federated Learning as Variational Inference: A Scalable Expectation Propagation Approach ICLR 2023 Federated Learning for Commercial Image Sources WACV 2023 Federated Learning from Small Datasets ICLR 2023 Federated Learning of Large Language Models with Parameter-Efficient Prompt Tuning and Adaptive Optimization EMNLP 2023 Federated learning of models pre-trained on different features with consensus graphs UAI 2023 Federated Learning with Client Subsampling, Data Heterogeneity, and Unbounded Smoothness: A New Algorithm and Lower Bounds NeurIPS 2023 Federated Learning With Data-Agnostic Distribution Fusion CVPR 2023 Federated Learning with Uncertainty via Distilled Predictive Distributions ACML 2023 Federated Linear Contextual Bandits with User-level Differential Privacy ICML 2023 Federated Neural Bandits ICLR 2023 Federated Online and Bandit Convex Optimization ICML 2023 Federated Robustness Propagation: Sharing Adversarial Robustness in Heterogeneous Federated Learning AAAI 2023