More from the Same Authors

• 2021 : Parallel Quasi-concave set optimization: A new frontier that scales without needing submodularity »
  Praneeth Vepakomma · Ramesh Raskar
• 2021 : BiG-Fed: Bilevel Optimization Enhanced Graph-Aided Federated Learning »
  Pengwei Xing · Xing pengwei · Han Yu
• 2021 : Industrial Booth (IBM) »
  Shiqiang Wang · Nathalie Baracaldo
• 2023 : Towards a Theoretical and Practical Understanding of One-Shot Federated Learning with Fisher Information »
  Divyansh Jhunjhunwala · Shiqiang Wang · Gauri Joshi
• 2023 : A New Theoretical Perspective on Data Heterogeneity in Federated Optimization »
  Jiayi Wang · Shiqiang Wang · Rong-Rong Chen · Mingyue Ji
• 2023 Workshop: Federated Learning and Analytics in Practice: Algorithms, Systems, Applications, and Opportunities »
  Zheng Xu · Peter Kairouz · Bo Li · Tian Li · John Nguyen · Jianyu Wang · Shiqiang Wang · Ayfer Ozgur
• 2023 Poster: The Blessing of Heterogeneity in Federated Q-Learning: Linear Speedup and Beyond »
  Jiin Woo · Gauri Joshi · Yuejie Chi
• 2023 Poster: On the Convergence of Federated Averaging with Cyclic Client Participation »
  Yae Jee Cho · PRANAY SHARMA · Gauri Joshi · Zheng Xu · Satyen Kale · Tong Zhang
• 2023 Poster: LESS-VFL: Communication-Efficient Feature Selection for Vertical Federated Learning »
  Timothy Castiglia · Yi Zhou · Shiqiang Wang · Swanand Kadhe · Nathalie Baracaldo · Stacy Patterson
• 2022 Poster: Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data »
  Timothy Castiglia · Anirban Das · Shiqiang Wang · Stacy Patterson
• 2022 Poster: Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling »
  sajad khodadadian · PRANAY SHARMA · Gauri Joshi · Siva Maguluri
• 2022 Spotlight: Compressed-VFL: Communication-Efficient Learning with Vertically Partitioned Data »
  Timothy Castiglia · Anirban Das · Shiqiang Wang · Stacy Patterson
• 2022 Oral: Federated Reinforcement Learning: Linear Speedup Under Markovian Sampling »
  sajad khodadadian · PRANAY SHARMA · Gauri Joshi · Siva Maguluri
• 2022 Poster: Federated Minimax Optimization: Improved Convergence Analyses and Algorithms »
  PRANAY SHARMA · Rohan Panda · Gauri Joshi · Pramod K Varshney
• 2022 Spotlight: Federated Minimax Optimization: Improved Convergence Analyses and Algorithms »
  PRANAY SHARMA · Rohan Panda · Gauri Joshi · Pramod K Varshney
• 2021 : Parallel Quasi-concave set optimization: A new frontier that scales without needing submodularity »
  Ramesh Raskar · Praneeth Vepakomma
• 2021 : Closing Remarks »
  Shiqiang Wang · Nathalie Baracaldo · Olivia Choudhury · Gauri Joshi · Peter Richtarik · Praneeth Vepakomma · Han Yu
• 2021 : Industrial Panel »
  Nathalie Baracaldo · Shiqiang Wang · Peter Kairouz · Zheng Xu · Kshitiz Malik · Tao Zhang
• 2021 Workshop: International Workshop on Federated Learning for User Privacy and Data Confidentiality in Conjunction with ICML 2021 (FL-ICML'21) »
  Nathalie Baracaldo · Olivia Choudhury · Gauri Joshi · Peter Richtarik · Praneeth Vepakomma · Shiqiang Wang · Han Yu
• 2021 : Opening Remarks »
  Shiqiang Wang · Nathalie Baracaldo · Olivia Choudhury · Gauri Joshi · Peter Richtarik · Praneeth Vepakomma · Han Yu
• 2021 : Governance in FL: Providing AI Fairness and Accountability »
  Nathalie Baracaldo · Ali Anwar · Annie Abay
• 2021 Expo Talk Panel: Enterprise-Strength Federated Learning: New Algorithms, New Paradigms, and a Participant-Interactive Demonstration Session »
  Laura Wynter · Nathalie Baracaldo · Chaitanya Kumar · Parijat Dube · Mikhail Yurochkin · Theodoros Salonidis · Shiqiang Wang
• 2021 : Adaptive Federated Learning for Communication and Computation Efficiency (2021 IEEE Leonard Prize-winning work). »
  Shiqiang Wang
• 2020 : Opening remarks »
  Nathalie Baracaldo · Olivia Choudhury · Gauri Joshi · Ramesh Raskar · Shiqiang Wang · Han Yu
• 2020 Workshop: Federated Learning for User Privacy and Data Confidentiality »
  Nathalie Baracaldo · Olivia Choudhury · Olivia Choudhury · Gauri Joshi · Ramesh Raskar · Gauri Joshi · Shiqiang Wang · Han Yu
• 2019 Workshop: Coding Theory For Large-scale Machine Learning »
  Viveck Cadambe · Pulkit Grover · Dimitris Papailiopoulos · Gauri Joshi