Andrew Hard

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All published works

Action	Title	Year	Authors
+ PDF Chat	Learning from straggler clients in federated learning	2024	Andrew Hard Antonious M. Girgis Ehsan Amid Sean Augenstein Lara McConnaughey Rajiv Mathews Rohan Anil
+	Jointly Learning from Decentralized (Federated) and Centralized Data to Mitigate Distribution Shift	2021	Sean Augenstein Andrew Hard Kurt Partridge Rajiv Mathews
+	A Field Guide to Federated Optimization	2021	Jianyu Wang Zachary Charles Zheng Xu Gauri Joshi H. Brendan McMahan Blaise Agüera y Arcas Maruan Al-Shedivat Galen Andrew Salman Avestimehr Katharine Daly
+ PDF Chat	Training Keyword Spotting Models on Non-IID Data with Federated Learning	2020	Andrew Hard Kurt Partridge Cameron Nguyen Niranjan Subrahmanya Aishanee Shah Pai Zhu Ignacio López Moreno Rajiv Mathews
+	Training Keyword Spotting Models on Non-IID Data with Federated Learning	2020	Andrew Hard Kurt Partridge Cameron Nguyen Niranjan Subrahmanya Aishanee Shah Pai Zhu Ignacio López Moreno Rajiv Mathews
+	Federated Learning for Mobile Keyboard Prediction	2018	Andrew Hard Chloé Kiddon Daniel Ramage Françoise Beaufays Hubert Eichner K. Praveen Kumar Rao Rajiv Mathews Sean Augenstein

Common Coauthors

Coauthor	Papers Together
Rajiv Mathews	5
Sean Augenstein	3
Kurt Partridge	3
Pai Zhu	2
Antonious M. Girgis	2
Aishanee Shah	2
Ignacio López Moreno	2
Hubert Eichner	2
Niranjan Subrahmanya	2
Cameron Nguyen	2
Weikang Song	1
Zachary Charles	1
Peter Richtárik	1
Galen Andrew	1
H. Brendan McMahan	1
Samuel Horváth	1
Blaise Agüera y Arcas	1
Sebastian U. Stich	1
Mahdi Soltanolkotabi	1
Jakub Konečný	1
Alex Ingerman	1
Ehsan Amid	1
Mehryar Mohri	1
Tara Javidi	1
Peter Kairouz	1
Chloé Kiddon	1
Gauri Joshi	1
Shanshan Wu	1
Lara McConnaughey	1
Wennan Zhu	1
Zhouyuan Huo	1
Daniel Ramage	1
Martin Jaggi	1
Sashank J. Reddi	1
Suhas Diggavi	1
Honglin Yuan	1
Filip Hanzely	1
Sanmi Koyejo	1
H. Jerry Qi	1
Jianyu Wang	1
Mi Zhang	1
Hongyi Wang	1
Chen Zhu	1
Chunxiang Zheng	1
Luyang Liu	1
Zheng Xu	1
Tian Li	1
Tong Zhang	1
Manzil Zaheer	1
Ananda Theertha Suresh	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Federated Learning for Mobile Keyboard Prediction	2018	Andrew Hard Chloé Kiddon Daniel Ramage Françoise Beaufays Hubert Eichner K. Praveen Kumar Rao Rajiv Mathews Sean Augenstein	4
+	On the Convergence of FedAvg on Non-IID Data	2019	Xiang Li Kaixuan Huang Wenhao Yang Shusen Wang Zhihua Zhang	3
+	Federated Learning with Non-IID Data	2018	Yue Zhao Meng Li Liangzhen Lai Naveen Suda Damon Civin Vikas Chandra	3
+	Federated Learning for Emoji Prediction in a Mobile Keyboard	2019	Françoise Beaufays K. Praveen Kumar Rao Rajiv Mathews Swaroop Ramaswamy	3
+	Measuring the Effects of Non-Identical Data Distribution for Federated Visual Classification	2019	Harry Chia-Hung Hsu Hang Qi Matthew A. Brown	3
+	Applied Federated Learning: Improving Google Keyboard Query Suggestions	2018	Timothy T. Yang Galen Andrew Hubert Eichner Haicheng Sun Wei Li Nicholas Kong Daniel Ramage Françoise Beaufays	3
+	Adam: A Method for Stochastic Optimization	2014	Diederik P. Kingma Jimmy Ba	3
+ PDF Chat	Deep Learning with Differential Privacy	2016	Martı́n Abadi Andy Chu Ian Goodfellow H. Brendan McMahan Ilya Mironov Kunal Talwar Li Zhang	3
+	Practical Secure Aggregation for Federated Learning on User-Held Data	2016	Kallista Bonawitz Vladimir Ivanov Ben Kreuter Antonio Marcedone H. Brendan McMahan Sarvar Patel Daniel Ramage Aaron Segal Karn Seth	2
+	A Cascade Architecture for Keyword Spotting on Mobile Devices	2017	Alexander Gruenstein Raziel Álvarez Chris Thornton Mohammadali Ghodrat	2
+	SCAFFOLD: Stochastic Controlled Averaging for Federated Learning	2019	Sai Praneeth Karimireddy Satyen Kale Mehryar Mohri Sashank J. Reddi Sebastian U. Stich Ananda Theertha Suresh	2
+ PDF Chat	Streaming End-to-end Speech Recognition for Mobile Devices	2019	Yanzhang He Tara N. Sainath Rohit Prabhavalkar Ian McGraw Raziel Álvarez Ding Zhao David Rybach Anjuli Kannan Yonghui Wu Ruoming Pang	2
+ PDF Chat	Federated Learning for Keyword Spotting	2019	David Leroy Alice Coucke Thibaut Lavril Thibault Gisselbrecht Joseph Dureau	2
+	Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning	2020	Sai Praneeth Karimireddy Martin Jaggi Satyen Kale Mehryar Mohri Sashank J. Reddi Sebastian U. Stich Ananda Theertha Suresh	2
+	LEAF: A Benchmark for Federated Settings	2018	Sebastian Caldas Peter Wu Li Tian Jakub Konečný H. Brendan McMahan Virginia Smith Ameet Talwalkar	2
+ PDF Chat	Learning to Detect Keyword Parts and Whole by Smoothed Max Pooling	2020	Hyunjin Park Patrick Violette Niranjan Subrahmanya	2
+	Generative Models for Effective ML on Private, Decentralized Datasets.	2019	Sean Augenstein H. Brendan McMahan Daniel Ramage Swaroop Ramaswamy Peter Kairouz Mingqing Chen Rajiv Mathews Blaise Agüera y Arcas	2
+ PDF Chat	Specaugment on Large Scale Datasets	2020	Daniel Park Yu Zhang Chung‐Cheng Chiu Youzheng Chen Bo Li William Chan Quoc V. Le Yonghui Wu	2
+	Learning Differentially Private Recurrent Language Models	2017	H. Brendan McMahan Daniel Ramage Kunal Talwar Li Zhang	2
+	Distilling the Knowledge in a Neural Network	2015	Geoffrey E. Hinton Oriol Vinyals Jay B. Dean	2
+ PDF Chat	Lessons from Building Acoustic Models with a Million Hours of Speech	2019	Sree Hari Krishnan Parthasarathi Nikko Ström	2
+ PDF Chat	SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition	2019	Daniel Park William Chan Yu Zhang Chung‐Cheng Chiu Barret Zoph Ekin D. Cubuk Quoc V. Le	2
+	Training Keyword Spotting Models on Non-IID Data with Federated Learning	2020	Andrew Hard Kurt Partridge Cameron Nguyen Niranjan Subrahmanya Aishanee Shah Pai Zhu Ignacio López Moreno Rajiv Mathews	2
+	Some methods of speeding up the convergence of iteration methods	1964	B. T. Polyak	2
+	Federated Learning of N-Gram Language Models	2019	Mingqing Chen Ananda Theertha Suresh Rajiv Mathews Adeline Wong Cyril Allauzen Françoise Beaufays Michael Riley	2
+	Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation	2014	Kyunghyun Cho Bart van Merriënboer Çaǧlar Gülçehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk Yoshua Bengio	1
+	Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks	2017	Chelsea Finn Pieter Abbeel Sergey Levine	1
+	Differentially Private Empirical Risk Minimization.	2011	Kamalika Chaudhuri Claire Monteleoni Anand D. Sarwate	1
+	Mobile Keyboard Input Decoding with Finite-State Transducers	2017	Tom Ouyang David Rybach Françoise Beaufays Michael Riley	1
+	Distributed Learning for Cooperative Inference.	2017	Angelia Nedić Alex Olshevsky César A. Uribe	1
+ PDF Chat	Deep Learning Face Attributes in the Wild	2015	Ziwei Liu Ping Luo Xiaogang Wang Xiaoou Tang	1
+	Federated Learning: Strategies for Improving Communication Efficiency	2016	Jakub Konečný H. Brendan McMahan Felix X. Yu Peter Richtárik Ananda Theertha Suresh Dave Bacon	1
+	Federated Optimization: Distributed Machine Learning for On-Device Intelligence	2016	Jakub Konečný H. Brendan McMahan Daniel Ramage Peter Richtárik	1
+ PDF Chat	Fairness through awareness	2012	Cynthia Dwork Moritz Hardt Toniann Pitassi Omer Reingold Richard S. Zemel	1
+	Equality of Opportunity in Supervised Learning	2016	Moritz Hardt Eric Price Nathan Srebro	1
+ PDF Chat	Parallel Restarted SGD with Faster Convergence and Less Communication: Demystifying Why Model Averaging Works for Deep Learning	2019	Hao Yu Sen Yang Shenghuo Zhu	1
+	AIDE: Fast and Communication Efficient Distributed Optimization	2016	Sashank J. Reddi Jakub Konečný Peter Richtárik Barnabás Póczos Alexander J. Smola	1
+	Local Privacy and Statistical Minimax Rates	2013	John C. Duchi Michael I. Jordan Martin J. Wainwright	1
+ PDF Chat	LSTM: A Search Space Odyssey	2016	Klaus Greff Rupesh K. Srivastava Jan Koutník Bas R. Steunebrink Jürgen Schmidhuber	1
+	Cooperative SGD: A unified Framework for the Design and Analysis of Communication-Efficient SGD Algorithms	2018	Jianyu Wang Gauri Joshi	1
+	Parallel SGD: When does averaging help?	2016	Jian Zhang Christopher De Ioannis Mitliagkas Christopher Ré	1
+	Gradient methods for minimizing composite functions	2012	Yu. Nesterov	1
+	On First-Order Meta-Learning Algorithms.	2018	Alex Nichol Joshua Achiam John Schulman	1
+	Sparsified SGD with Memory	2018	Sebastian U. Stich Jean-Baptiste Cordonnier Martin Jaggi	1
+	Training Deep Nets with Sublinear Memory Cost	2016	Tianqi Chen Bing Xu Chiyuan Zhang Carlos Guestrin	1
+	Reptile: a Scalable Metalearning Algorithm	2018	Alex Nichol John Schulman	1
+	Revisiting Distributed Synchronous SGD	2017	Jianmin Chen Rajat Monga Samy Bengio Rafał Józefowicz	1
+	A generic framework for privacy preserving deep learning	2018	Théo Ryffel Andrew Trask Morten Dahl Bobby Wagner Jason Mancuso Daniel Rueckert Jonathan Passerat‐Palmbach	1
+	Parallel training of DNNs with Natural Gradient and Parameter Averaging	2014	Daniel Povey Xiaohui Zhang Sanjeev Khudanpur	1
+	Private federated learning on vertically partitioned data via entity resolution and additively homomorphic encryption	2017	Stephen Hardy Wilko Henecka Hamish Ivey-Law Richard Nock Giorgio Patrini Guillaume Smith Brian Thorne	1