← Authors

Gauri Joshi

26 papers · 2018–2025 · 9 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (13) 🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer πŸ—ΊοΈ Taxonomy Completionist (28) 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (7) 🌈 Renaissance Researcher (5) πŸ‘‘ Triple Crown πŸ”¬ Deep Specialist (15) πŸ† Keyword Champion (2) πŸ’Ž Century Club (26) ⚑ Prolific Year (5) πŸ”₯ Unstoppable (6) πŸ—ƒοΈ Keyword Collector (93)

Conferences

AISTATS (7) ICML (6) NIPS (3) UAI (3) ICLR (2) JMLR (2) EMNLP (1) ICCV (1) IJCAI (1)

Top co-authors

PRANAY SHARMA (9) Yae Jee Cho (5) Divyansh Jhunjhunwala (4) Jianyu Wang (4) Jiin Woo (3) Zheng Xu (3) Yuejie Chi (3) Carlee Joe-Wong (2) Dimitrios Dimitriadis (2) Shiqiang Wang (2)

Keywords

federated learning (13) communication efficiency (5) linear speedup (4) convergence analysis (4) distributed learning (4) stochastic gradient descent (3) knowledge distillation (2) model compression (2) reinforcement learning (2) tabular markov decision process (2) federated q-learning (2) importance averaging (2) semi-supervised learning (2) local updates (2) heterogeneous datum (2) policy gradient (1) biased sampling (1) bayesian inference (1) ensemble learning (1) model aggregation (1)

Papers

High-probability Convergence Bounds for Online Nonlinear Stochastic Gradient Descent under Heavy-tailed Noise AISTATS 2025
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond JMLR 2025
FedECADO: A Dynamical System Model of Federated Learning ICML 2025
Debiasing Federated Learning with Correlated Client Participation ICLR 2025
Federated Communication-Efficient Multi-Objective Optimization AISTATS 2025
FedAST: Federated Asynchronous Simultaneous Training UAI 2024
FedFisher: Leveraging Fisher Information for One-Shot Federated Learning AISTATS 2024
Efficient Reinforcement Learning for Routing Jobs in Heterogeneous Queueing Systems AISTATS 2024
Heterogeneous LoRA for Federated Fine-tuning of On-Device Foundation Models EMNLP 2024
Federated Offline Reinforcement Learning: Collaborative Single-Policy Coverage Suffices ICML 2024
On the Convergence of Federated Averaging with Cyclic Client Participation ICML 2023
The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond ICML 2023
Correlation Aware Sparsified Mean Estimation Using Random Projection NIPS 2023
Federated Learning under Distributed Concept Drift AISTATS 2023
Local or Global: Selective Knowledge Assimilation for Federated Learning with Limited Labels ICCV 2023
FedExP: Speeding Up Federated Averaging via Extrapolation ICLR 2023
Fedvarp: Tackling the variance due to partial client participation in federated learning UAI 2022
Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling ICML 2022
Federated Minimax Optimization: Improved Convergence Analyses and Algorithms ICML 2022
Heterogeneous Ensemble Knowledge Transfer for Training Large Models in Federated Learning IJCAI 2022
Towards Understanding Biased Client Selection in Federated Learning AISTATS 2022
Cooperative SGD: A Unified Framework for the Design and Analysis of Local-Update SGD Algorithms JMLR 2021
Leveraging Spatial and Temporal Correlations in Sparsified Mean Estimation NIPS 2021
Deep kernels with probabilistic embeddings for small-data learning UAI 2021
Tackling the Objective Inconsistency Problem in Heterogeneous Federated Optimization NIPS 2020
Slow and Stale Gradients Can Win the Race: Error-Runtime Trade-offs in Distributed SGD AISTATS 2018