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Author Information
Felix Sattler (Fraunhofer HHI)
Khaoula El Mekkaoui (Aalto university)
Neta Shoham (Edgify)
Cheng Hong (Alibaba Group)
Florian Hartmann (Google Research)
Boyue Li (Carnegie Mellon University)
Daliang Li (Harvard University)
Sebastian Caldas Rivera (Carnegie Mellon University)
Jianyu Wang (Carnegie Mellon University)
Kartikeya Bhardwaj (Arm Inc.)
Tribhuvanesh Orekondy (Max Planck Institute for Informatics)
YAN KANG (Webank)
Dashan Gao (Hong Kong University of Science and Technology)
Mingshu Cong (The University of Hong Kong)
Xin Yao (Tsinghua University)
Songtao Lu (University of Minnesota Twin Cities)
JIAHUAN LUO (South China University of Technology)
Shicong Cen (Carnegie Mellon University)
Peter Kairouz (Google)
Peter Kairouz is a Google Research Scientist working on decentralized, privacy-preserving, and robust machine learning algorithms. Prior to Google, his research largely focused on building decentralized technologies for anonymous broadcasting over complex networks, understanding the fundamental trade-off between differential privacy and utility of learning algorithms, and leveraging state-of-the-art deep generative models for data-driven privacy and fairness.
Yihan Jiang (University of Washington Seattle)
Tzu Ming Hsu (MIT)
Aleksei Triastcyn (EPFL)
Yang Liu (Tencent)
Ahmed Khaled Ragab Bayoumi (Cairo University)
Zhicong Liang (Hong Kong University of Science and Technology)
Boi Faltings (EPFL)
Seungwhan Moon (Carnegie Mellon University)
Suyi Li (The Hong Kong University of Science and Technology)
Tao Fan (Webank)
Tianchi Huang (Tsinghua University)
Chunyan Miao (Nanyang Technological University)
Hang Qi (Google)
Matthew Brown (Google Research)
Lucas Glass (IQVIA)
Junpu Wang (University of Pennsylvania)
I am a theoretical physicist. Now I am working on various topics in machine learning and deep learning.
Wei Chen (Carnegie Mellon University)
Radu Marculescu (Carnegie Mellon University)
tomer avidor (edgify)
Xueyang Wu (The Hong Kong University of Science and Technology)
Mingyi Hong (University of Minnesota)
Ce Ju (WeBank Co., Ltd.)
John Rush (Google)
I come from a pure mathematics background, formerly a harmonic analyst and mathematical physicist. I transferred to machine learning on the software side after grad school, and joined Google in 2018, working on federated learning. I am a main author of TensorFlow Federated; ask me about it!
Ruixiao Zhang (Tsinghua university)
Youchi ZHOU (WeBank)
Françoise Beaufays (Google)
Françoise Beaufays is a Principal Scientist at Google, where she leads a team of engineers and researchers working on speech recognition and mobile keyboard input. Her area of expertise covers deep learning, language modeling and other technologies related to natural language processing, with a recent focus on privacy-preserving on-device learning. Françoise studied Mechanical and Electrical Engineering in Brussels, Belgium. She holds a PhD in Electrical Engineering and a PhD minor in Italian Literature, both from Stanford Uni
Yingxuan Zhu (Futurewei Technologies)
Lei Xia (Intel china)
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2021 Poster: Pointwise Bounds for Distribution Estimation under Communication Constraints »
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Clement Canonne · Kwang-Sung Jun · Seth Neel · Di Wang · Giuseppe Vietri · Liwei Song · Jonathan Lebensold · Huanyu Zhang · Lovedeep Gondara · Ang Li · FatemehSadat Mireshghallah · Jinshuo Dong · Anand D Sarwate · Antti Koskela · Joonas Jälkö · Matt Kusner · Dingfan Chen · Mi Jung Park · Ashwin Machanavajjhala · Jayashree Kalpathy-Cramer · · Vitaly Feldman · Andrew Tomkins · Hai Phan · Hossein Esfandiari · Mimansa Jaiswal · Mrinank Sharma · Jeff Druce · Casey Meehan · Zhengli Zhao · Hsiang Hsu · Davis Railsback · Abraham Flaxman · · Julius Adebayo · Aleksandra Korolova · Jiaming Xu · Naoise Holohan · Samyadeep Basu · Matthew Joseph · My Thai · Xiaoqian Yang · Ellen Vitercik · Michael Hutchinson · Chenghong Wang · Gregory Yauney · Yuchao Tao · Chao Jin · Si Kai Lee · Audra McMillan · Rauf Izmailov · Jiayi Guo · Siddharth Swaroop · Tribhuvanesh Orekondy · Hadi Esmaeilzadeh · Kevin Procopio · Alkis Polyzotis · Jafar Mohammadi · Nitin Agrawal -
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Xingyou Song · Puneet Mangla · David Salinas · Zhenxun Zhuang · Leo Feng · Shell Xu Hu · Raul Puri · Wesley Maddox · Aniruddh Raghu · Prudencio Tossou · Mingzhang Yin · Ishita Dasgupta · Kangwook Lee · Ferran Alet · Zhen Xu · Jörg Franke · James Harrison · Jonathan Warrell · Guneet Dhillon · Arber Zela · Xin Qiu · Julien Niklas Siems · Russell Mendonca · Louis Schlessinger · Jeffrey Li · Georgiana Manolache · Debojyoti Dutta · Lucas Glass · Abhishek Singh · Gregor Koehler -
2019 : TBD »
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2019 Poster: Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels »
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2019 Poster: ZO-AdaMM: Zeroth-Order Adaptive Momentum Method for Black-Box Optimization »
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2018 : Poster Session I »
Aniruddh Raghu · Daniel Jarrett · Kathleen Lewis · Elias Chaibub Neto · Nicholas Mastronarde · Shazia Akbar · Chun-Hung Chao · Henghui Zhu · Seth Stafford · Luna Zhang · Jen-Tang Lu · Changhee Lee · Adityanarayanan Radhakrishnan · Fabian Falck · Liyue Shen · Daniel Neil · Yusuf Roohani · Aparna Balagopalan · Brett Marinelli · Hagai Rossman · Sven Giesselbach · Jose Javier Gonzalez Ortiz · Edward De Brouwer · Byung-Hoon Kim · Rafid Mahmood · Tzu Ming Hsu · Antonio Ribeiro · Rumi Chunara · Agni Orfanoudaki · Kristen Severson · Mingjie Mai · Sonali Parbhoo · Albert Haque · Viraj Prabhu · Di Jin · Alena Harley · Geoffroy Dubourg-Felonneau · Xiaodan Hu · Maithra Raghu · Jonathan Warrell · Nelson Johansen · Wenyuan Li · Marko Järvenpää · Satya Narayan Shukla · Sarah Tan · Vincent Fortuin · Beau Norgeot · Yi-Te Hsu · Joel H Saltz · Veronica Tozzo · Andrew Miller · Guillaume Ausset · Azin Asgarian · Francesco Paolo Casale · Antoine Neuraz · Bhanu Pratap Singh Rawat · Turgay Ayer · Xinyu Li · Mehul Motani · Nathaniel Braman · Laetitia M Shao · Adrian Dalca · Hyunkwang Lee · Emma Pierson · Sandesh Ghimire · Yuji Kawai · Owen Lahav · Anna Goldenberg · Denny Wu · Pavitra Krishnaswamy · Colin Pawlowski · Arijit Ukil · Yuhui Zhang -
2018 : Posters (all accepted papers) + Break »
Jianyu Wang · Denis Gudovskiy · Ziheng Jiang · Michael Kaufmann · Andreea Anghel · James Bradbury · Nikolas Ioannou · Nitin Agrawal · Emma Tosch · Gyeongin Yu · Keno Fischer · Jarrett Revels · Giuseppe Siracusano · Yaoqing Yang · Jeff Johnson · Yang You · Hector Yuen · Chris Ying · Honglei Liu · Nikoli Dryden · Xiangxi Mo · Yangzihao Wang · Amit Juneja · Micah Smith · Qian Yu · pramod gupta · Deepak Narayanan · Keshav Santhanam · Tim Capes · Abdul Dakkak · Norman Mu · Ke Deng · Liam Li · Joao Carreira · Luis Remis · Deepti Raghavan · Una-May O'Reilly · Amanpreet Singh · Mahmoud (Mido) Assran · Eugene Wu · Eytan Bakshy · Jinliang Wei · Michael Innes · Viral Shah · Haibin Lin · Conrad Sanderson · Ryan Curtin · Marcus Edel -
2018 Poster: Nonparametric Density Estimation under Adversarial Losses »
Shashank Singh · Ananya Uppal · Boyue Li · Chun-Liang Li · Manzil Zaheer · Barnabas Poczos -
2018 Poster: Multi-Agent Reinforcement Learning via Double Averaging Primal-Dual Optimization »
Hoi-To Wai · Zhuoran Yang · Zhaoran Wang · Mingyi Hong -
2018 Poster: Deepcode: Feedback Codes via Deep Learning »
Hyeji Kim · Yihan Jiang · Sreeram Kannan · Sewoong Oh · Pramod Viswanath -
2018 Poster: 3D-Aware Scene Manipulation via Inverse Graphics »
Shunyu Yao · Tzu Ming Hsu · Jun-Yan Zhu · Jiajun Wu · Antonio Torralba · Bill Freeman · Josh Tenenbaum -
2017 Poster: Predictive State Recurrent Neural Networks »
Carlton Downey · Ahmed Hefny · Byron Boots · Geoffrey Gordon · Boyue Li -
2015 : Multimodal Transfer Deep Learning with Applications in Audio-Visual Recognition »
Seungwhan Moon -
2015 : Accepted Orals and Spotlights »
Seungwhan Moon · George Trigeorgis · Goker Erdogan · Tadahiro Taniguchi -
2015 Poster: Secure Multi-party Differential Privacy »
Peter Kairouz · Sewoong Oh · Pramod Viswanath -
2014 Poster: Extremal Mechanisms for Local Differential Privacy »
Peter Kairouz · Sewoong Oh · Pramod Viswanath