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Panel
Virginia Smith · Michele Covell · Daniel Severo · Christopher Schroers
Author Information
Virginia Smith (Carnegie Mellon University)
Michele Covell (Google, Inc)
Daniel Severo (University of Toronto)
Christopher Schroers (Disney Research|Studios)
More from the Same Authors
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2021 : Your Dataset is a Multiset and You Should Compress it Like One »
Daniel Severo · James Townsend · Ashish Khisti · Alireza Makhzani · Karen Ullrich -
2022 : Differentially Private Adaptive Optimization with Delayed Preconditioners »
Tian Li · Manzil Zaheer · Ken Liu · Sashank Reddi · H. Brendan McMahan · Virginia Smith -
2022 : Differentially Private Adaptive Optimization with Delayed Preconditioners »
Tian Li · Manzil Zaheer · Ken Liu · Sashank Reddi · H. Brendan McMahan · Virginia Smith -
2022 : Motley: Benchmarking Heterogeneity and Personalization in Federated Learning »
Shanshan Wu · Tian Li · Zachary Charles · Yu Xiao · Ken Liu · Zheng Xu · Virginia Smith -
2022 : Bitrate-Constrained DRO: Beyond Worst Case Robustness To Unknown Group Shifts »
Amrith Setlur · Don Dennis · Benjamin Eysenbach · Aditi Raghunathan · Chelsea Finn · Virginia Smith · Sergey Levine -
2022 : Action Matching: A Variational Method for Learning Stochastic Dynamics from Samples »
Kirill Neklyudov · Daniel Severo · Alireza Makhzani -
2022 : To Federate or Not To Federate: Incentivizing Client Participation in Federated Learning »
Yae Jee Cho · Divyansh Jhunjhunwala · Tian Li · Virginia Smith · Gauri Joshi -
2022 Poster: On Privacy and Personalization in Cross-Silo Federated Learning »
Ken Liu · Shengyuan Hu · Steven Wu · Virginia Smith -
2022 Poster: Adversarial Unlearning: Reducing Confidence Along Adversarial Directions »
Amrith Setlur · Benjamin Eysenbach · Virginia Smith · Sergey Levine -
2021 : Your Dataset is a Multiset and You Should Compress it Like One »
Daniel Severo · James Townsend · Ashish Khisti · Alireza Makhzani · Karen Ullrich -
2021 : Q&A with A/Professor Virginia Smith »
Virginia Smith -
2021 : Keynote Talk: Fair or Robust: Addressing Competing Constraints in Federated Learning (Virginia Smith) »
Virginia Smith -
2021 Poster: Two Sides of Meta-Learning Evaluation: In vs. Out of Distribution »
Amrith Setlur · Oscar Li · Virginia Smith -
2021 Poster: On Large-Cohort Training for Federated Learning »
Zachary Charles · Zachary Garrett · Zhouyuan Huo · Sergei Shmulyian · Virginia Smith -
2021 Poster: Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing »
Mikhail Khodak · Renbo Tu · Tian Li · Liam Li · Maria-Florina Balcan · Virginia Smith · Ameet Talwalkar -
2020 Tutorial: (Track1) Federated Learning and Analytics: Industry Meets Academia Q&A »
Peter Kairouz · Brendan McMahan · Virginia Smith -
2020 Tutorial: (Track1) Federated Learning and Analytics: Industry Meets Academia »
Brendan McMahan · Virginia Smith · Peter Kairouz -
2019 Workshop: Workshop on Federated Learning for Data Privacy and Confidentiality »
Lixin Fan · Jakub Konečný · Yang Liu · Brendan McMahan · Virginia Smith · Han Yu -
2019 Poster: Deep Generative Video Compression »
Salvator Lombardo · JUN HAN · Christopher Schroers · Stephan Mandt -
2018 : Prof. Virginia Smith »
Virginia Smith