Timezone: »
Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing
Ameet Talwalkar
Sat Jul 24 11:00 AM -- 11:25 AM (PDT) @
Author Information
Ameet Talwalkar (Carnegie Mellon University)
More from the Same Authors
-
2021 : Interpretable Machine Learning: Moving From Mythos to Diagnostics »
Valerie Chen · Jeffrey Li · Joon Kim · Gregory Plumb · Ameet Talwalkar -
2022 : SimpleSpot and Evaluating Systemic Errors using Synthetic Image Datasets »
Gregory Plumb · Nari Johnson · Ángel Alexander Cabrera · Marco Ribeiro · Ameet Talwalkar -
2022 : Perspectives on Incorporating Expert Feedback into Model Updates »
Valerie Chen · Umang Bhatt · Hoda Heidari · Adrian Weller · Ameet Talwalkar -
2023 : Where Does My Model Underperform?: A Human Evaluation of Slice Discovery Algorithms »
Nari Johnson · Ángel Alexander Cabrera · Gregory Plumb · Ameet Talwalkar -
2023 Oral: Cross-Modal Fine-Tuning: Align then Refine »
Junhong Shen · Liam Li · Lucio Dery · Corey Staten · Mikhail Khodak · Graham Neubig · Ameet Talwalkar -
2023 Poster: Cross-Modal Fine-Tuning: Align then Refine »
Junhong Shen · Liam Li · Lucio Dery · Corey Staten · Mikhail Khodak · Graham Neubig · Ameet Talwalkar -
2022 Poster: Sanity Simulations for Saliency Methods »
Joon Kim · Gregory Plumb · Ameet Talwalkar -
2022 Spotlight: Sanity Simulations for Saliency Methods »
Joon Kim · Gregory Plumb · Ameet Talwalkar -
2021 : Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing (Q&A) »
Ameet Talwalkar -
2020 Poster: FACT: A Diagnostic for Group Fairness Trade-offs »
Joon Kim · Jiahao Chen · Ameet Talwalkar -
2020 Poster: Explaining Groups of Points in Low-Dimensional Representations »
Gregory Plumb · Jonathan Terhorst · Sriram Sankararaman · Ameet Talwalkar -
2019 : ARUBA: Efficient and Adaptive Meta-Learning with Provable Guarantees (Ameet Talwalkar) »
Ameet Talwalkar -
2019 Workshop: Adaptive and Multitask Learning: Algorithms & Systems »
Maruan Al-Shedivat · Anthony Platanios · Otilia Stretcu · Jacob Andreas · Ameet Talwalkar · Rich Caruana · Tom Mitchell · Eric Xing -
2019 : Poster Session 1 (all papers) »
Matilde Gargiani · Yochai Zur · Chaim Baskin · Evgenii Zheltonozhskii · Liam Li · Ameet Talwalkar · Xuedong Shang · Harkirat Singh Behl · Atilim Gunes Baydin · Ivo Couckuyt · Tom Dhaene · Chieh Lin · Wei Wei · Min Sun · Orchid Majumder · Michele Donini · Yoshihiko Ozaki · Ryan P. Adams · Christian Geißler · Ping Luo · zhanglin peng · · Ruimao Zhang · John Langford · Rich Caruana · Debadeepta Dey · Charles Weill · Xavi Gonzalvo · Scott Yang · Scott Yak · Eugen Hotaj · Vladimir Macko · Mehryar Mohri · Corinna Cortes · Stefan Webb · Jonathan Chen · Martin Jankowiak · Noah Goodman · Aaron Klein · Frank Hutter · Mojan Javaheripi · Mohammad Samragh · Sungbin Lim · Taesup Kim · SUNGWOONG KIM · Michael Volpp · Iddo Drori · Yamuna Krishnamurthy · Kyunghyun Cho · Stanislaw Jastrzebski · Quentin de Laroussilhe · Mingxing Tan · Xiao Ma · Neil Houlsby · Andrea Gesmundo · Zalán Borsos · Krzysztof Maziarz · Felipe Petroski Such · Joel Lehman · Kenneth Stanley · Jeff Clune · Pieter Gijsbers · Joaquin Vanschoren · Felix Mohr · Eyke Hüllermeier · Zheng Xiong · Wenpeng Zhang · Wenwu Zhu · Weijia Shao · Aleksandra Faust · Michal Valko · Michael Y Li · Hugo Jair Escalante · Marcel Wever · Andrey Khorlin · Tara Javidi · Anthony Francis · Saurajit Mukherjee · Jungtaek Kim · Michael McCourt · Saehoon Kim · Tackgeun You · Seungjin Choi · Nicolas Knudde · Alexander Tornede · Ghassen Jerfel -
2019 Poster: Provable Guarantees for Gradient-Based Meta-Learning »
Nina Balcan · Mikhail Khodak · Ameet Talwalkar -
2019 Oral: Provable Guarantees for Gradient-Based Meta-Learning »
Nina Balcan · Mikhail Khodak · Ameet Talwalkar