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Author Information
Clement Canonne (Stanford University)
Kwang-Sung Jun (U of Arizona)
Seth Neel (University of Pennsylvania)
PhD student in statistics studying fairness and privacy in learning. Advised by Aaron Roth and Michael Kearns.
Di Wang (State University of New York at Buffalo)
Giuseppe Vietri (University of Minnesota)
Liwei Song (Princeton University)
Jonathan Lebensold (McGill University)
Huanyu Zhang (Cornell University)
Lovedeep Gondara (Simon Fraser University)
Ang Li (Duke University)
FatemehSadat Mireshghallah (University of California San Diego)
Jinshuo Dong (University of Pennsylvania)
Anand D Sarwate (Rutgers, The State University of New Jersey)
Antti Koskela (University of Helsinki)
Joonas Jälkö (Aalto University)
Matt Kusner (University of Oxford)
Dingfan Chen (cispa- Helmholtz Center for Information Security)
Mi Jung Park (MPI-IS Tuebingen)
Ashwin Machanavajjhala (Duke)
Jayashree Kalpathy-Cramer (MGH/Harvard Medical School)
Vitaly Feldman (Google Brain)
Andrew Tomkins (Google)
Hai Phan (New Jersey Institute of Technology)
Hossein Esfandiari (University of Maryland)
Mimansa Jaiswal (University of Michigan)
I am a 3rd year PhD student in computer science at University of Michigan. I work with natural language and speech processing for social application domain (affect, emotion, empathy). My work is mostly focussed on distribution robustness (domain variability, confounding variables, annotation paradigms), interpretation (error analysis, understanding why a model predicts a particular class, when is it successful/wrong?) and privacy & security (black box adversarial examples, mitigating demographic variable/membership leakage).
Mrinank Sharma (University of Oxford)
Jeff Druce (Charles River Analytics)
Casey Meehan (University of California, San Diego)
Zhengli Zhao (UCI, Google Brain)
Zhengli Zhao is a Computer Science PhD student at UC Irvine, concentrating on deep learning in natural language processing and computer vision.
Hsiang Hsu (Harvard University)
I am Hsiang Hsu, a Harvard Ph.D. student working with Flavio Calmon, and also a Meta Fellow. My research interests lie in promoting the interpretability of representations, improving privacy and fairness, and understanding prediction uncertainty in machine learning. I believe these are important issues in modern machine learning when trying to deploy the models in practice.
Davis Railsback (University of Washington)
Abraham Flaxman (University of Washington)
Julius Adebayo (MIT)
Aleksandra Korolova (University of Southern California)
Jiaming Xu (University of Illinois at Urbana Champaign)
Naoise Holohan (IBM Research - Ireland)
Samyadeep Basu (University of Maryland)
Matthew Joseph (University of Pennsylvania)
My Thai (University of Florida)
Xiaoqian Yang (Duke University)
Ellen Vitercik (Carnegie Mellon University)
Michael Hutchinson (University of Oxford)
Hi I'm Michael, a first year DPhil student at Oxford under the supervision of Yee Whye Teh and Max Welling. I'm interested in Probabalistic Machine Leanring in general, with a specific interests in distributed learning, generative modelling and uncertianty at a functional level.
Chenghong Wang (Duke University)
Gregory Yauney (Cornell University)
Yuchao Tao (Duke University)
Chao Jin (Institute for Infocomm Research, A*STAR)
Si Kai Lee (RIKEN AIP)
Audra McMillan (Northeastern/Boston University)
Rauf Izmailov (Perspecta Labs)
Jiayi Guo (Tsinghua University)
Siddharth Swaroop (University of Cambridge)
Tribhuvanesh Orekondy (Max Planck Institute for Informatics)
Hadi Esmaeilzadeh (University of California, San Diego)
Kevin Procopio (Charles River Analytics)
Alkis Polyzotis (Google)
Jafar Mohammadi (Nokia Bell Labs)
I am a researcher in Bell Labs in Stuttgart, Germany. My current research focus is on applications of machine learning in PHY and MAC communications layers. Before joining Nokia Bell Labs, I was a postdoctoral researcher at Rutgers university working on distributed machine learning problems with differential privacy. During his PhD I have worked on information theory and resource allocation optimisation problems for wireless communications.
Nitin Agrawal (University of Oxford)
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2019 : Break / Poster Session 1 »
Antonia Marcu · Yao-Yuan Yang · Pascale Gourdeau · Chen Zhu · Thodoris Lykouris · Jianfeng Chi · Mark Kozdoba · Arjun Nitin Bhagoji · Xiaoxia Wu · Jay Nandy · Michael T Smith · Bingyang Wen · Yuege Xie · Konstantinos Pitas · Suprosanna Shit · Maksym Andriushchenko · Dingli Yu · Gaël Letarte · Misha Khodak · Hussein Mozannar · Chara Podimata · James Foulds · Yizhen Wang · Huishuai Zhang · Ondrej Kuzelka · Alexander Levine · Nan Lu · Zakaria Mhammedi · Paul Viallard · Diana Cai · Lovedeep Gondara · James Lucas · Yasaman Mahdaviyeh · Aristide Baratin · Rishi Bommasani · Alessandro Barp · Andrew Ilyas · Kaiwen Wu · Jens Behrmann · Omar Rivasplata · Amir Nazemi · Aditi Raghunathan · Will Stephenson · Sahil Singla · Akhil Gupta · YooJung Choi · Yannic Kilcher · Clare Lyle · Edoardo Manino · Andrew Bennett · Zhi Xu · Niladri Chatterji · Emre Barut · Flavien Prost · Rodrigo Toro Icarte · Arno Blaas · Chulhee Yun · Sahin Lale · YiDing Jiang · Tharun Kumar Reddy Medini · Ashkan Rezaei · Alexander Meinke · Stephen Mell · Gary Kazantsev · Shivam Garg · Aradhana Sinha · Vishnu Lokhande · Geovani Rizk · Han Zhao · Aditya Kumar Akash · Jikai Hou · Ali Ghodsi · Matthias Hein · Tyler Sypherd · Yichen Yang · Anastasia Pentina · Pierre Gillot · Antoine Ledent · Guy Gur-Ari · Noah MacAulay · Tianzong Zhang -
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2019 : Poster Session »
Nathalie Baracaldo · Seth Neel · Tuyen Le · Dan Philps · Suheng Tao · Sotirios Chatzis · Toyo Suzumura · Wei Wang · WENHANG BAO · Solon Barocas · Manish Raghavan · Samuel Maina · Reginald Bryant · Kush Varshney · Skyler D. Speakman · Navdeep Gill · Nicholas Schmidt · Kevin Compher · Naveen Sundar Govindarajulu · Vivek Sharma · Praneeth Vepakomma · Tristan Swedish · Jayashree Kalpathy-Cramer · Ramesh Raskar · Shihao Zheng · Mykola Pechenizkiy · Marco Schreyer · Li Ling · Chirag Nagpal · Robert Tillman · Manuela Veloso · Hanjie Chen · Xintong Wang · Michael Wellman · Matthew van Adelsberg · Ben Wood · Hans Buehler · Mahmoud Mahfouz · Antonios Alexos · Megan Shearer · Antigoni Polychroniadou · Lucia Larise Stavarache · Dmitry Efimov · Johnston P Hall · Yukun Zhang · Emily Diana · Sumitra Ganesh · Vineeth Ravi · · Swetasudha Panda · Xavier Renard · Matthew Jagielski · Yonadav Shavit · Joshua Williams · Haoran Wei · Shuang (Sophie) Zhai · Xinyi Li · Hongda Shen · Daiki Matsunaga · Jaesik Choi · Alexis Laignelet · Batuhan Guler · Jacobo Roa Vicens · Ajit Desai · Jonathan Aigrain · Robert Samoilescu -
2019 : Lunch break and poster »
Felix Sattler · Khaoula El Mekkaoui · Neta Shoham · Cheng Hong · Florian Hartmann · Boyue Li · Daliang Li · Sebastian Caldas Rivera · Jianyu Wang · Kartikeya Bhardwaj · Tribhuvanesh Orekondy · YAN KANG · Dashan Gao · Mingshu Cong · Xin Yao · Songtao Lu · JIAHUAN LUO · Shicong Cen · Peter Kairouz · Yihan Jiang · Tzu Ming Hsu · Aleksei Triastcyn · Yang Liu · Ahmed Khaled Ragab Bayoumi · Zhicong Liang · Boi Faltings · Seungwhan Moon · Suyi Li · Tao Fan · Tianchi Huang · Chunyan Miao · Hang Qi · Matthew Brown · Lucas Glass · Junpu Wang · Wei Chen · Radu Marculescu · tomer avidor · Xueyang Wu · Mingyi Hong · Ce Ju · John Rush · Ruixiao Zhang · Youchi ZHOU · Françoise Beaufays · Yingxuan Zhu · Lei Xia -
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Shuangjia Zheng · Arnav Kapur · Umar Asif · Eyal Rozenberg · Cyprien Gilet · Oleksii Sidorov · Yogesh Kumar · Tom Van Steenkiste · William Boag · David Ouyang · Paul Jaeger · Sheng Liu · Aparna Balagopalan · Deepta Rajan · Marta Skreta · Nikhil Pattisapu · Jann Goschenhofer · Viraj Prabhu · Di Jin · Laura-Jayne Gardiner · Irene Li · sriram kumar · Qiyuan Hu · Mehul Motani · Justin Lovelace · Usman Roshan · Lucy Lu Wang · Ilya Valmianski · Hyeonwoo Lee · Sunil Mallya · Elias Chaibub Neto · Jonas Kemp · Marie Charpignon · Amber Nigam · Wei-Hung Weng · Sabri Boughorbel · Alexis Bellot · Lovedeep Gondara · Haoran Zhang · Taha Bahadori · John Zech · Rulin Shao · Edward Choi · Laleh Seyyed-Kalantari · Emily Aiken · Ioana Bica · Yiqiu Shen · Kieran Chin-Cheong · Subhrajit Roy · Ioana Baldini · So Yeon Min · Dirk Deschrijver · Pekka Marttinen · Damian Pascual Ortiz · Supriya Nagesh · Niklas Rindtorff · Andriy Mulyar · Katharina Hoebel · Martha Shaka · Pierre Machart · Leon Gatys · Nathan Ng · Matthias Hüser · Devin Taylor · Dennis Barbour · Natalia Martinez · Clara McCreery · Benjamin Eyre · Vivek Natarajan · Ren Yi · Ruibin Ma · Chirag Nagpal · Nan Du · Chufan Gao · Anup Tuladhar · Sam Shleifer · Jason Ren · Pouria Mashouri · Ming Yang Lu · Farideh Bagherzadeh-Khiabani · Olivia Choudhury · Maithra Raghu · Scott Fleming · Mika Jain · GUO YANG · Alena Harley · Stephen Pfohl · Elisabeth Rumetshofer · Alex Fedorov · Saloni Dash · Jacob Pfau · Sabina Tomkins · Colin Targonski · Michael Brudno · Xinyu Li · Yiyang Yu · Nisarg Patel -
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2019 Poster: Graph Agreement Models for Semi-Supervised Learning »
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2019 Poster: Locally Private Gaussian Estimation »
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2019 Poster: Capacity Bounded Differential Privacy »
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2018 : Poster Session »
Phillipp Schoppmann · Patrick Yu · Valerie Chen · Travis Dick · Marc Joye · Ningshan Zhang · Frederik Harder · Olli Saarikivi · Théo Ryffel · Yunhui Long · Théo JOURDAN · Di Wang · Antonio Marcedone · Negev Shekel Nosatzki · Yatharth A Dubey · Antti Koskela · Peter Bloem · Aleksandra Korolova · Martin Bertran · Hao Chen · Galen Andrew · Natalia Martinez · Janardhan Kulkarni · Jonathan Passerat-Palmbach · Guillermo Sapiro · Amrita Roy Chowdhury -
2018 : Lunch »
Hong Yu · Bhanu Pratap Singh Rawat · Arijit Ukil · Waheeda Saib · Jekaterina Novikova · John Hughes · Yuhui Zhang · Rahul V · Mi Jung Kim · Babak Taati · Hariharan Ravishankar · Harry Clifford · Hirofumi Kobayashi · Babak Taati · Keyang Xu · Yen-Chi Cheng · Timothy Cannings · Jayashree Kalpathy-Cramer · Jayashree Kalpathy-Cramer · Parinaz Sobhani · Kimis Perros · Wei-Hung Weng · Yordan Raykov · Lars Lorch · Mengqi Jin · Xue Teng · Michael Ferlaino · Marek Rei · Cédric Beaulac · Aman Verma · Sebastian Keller · Edmond Cunningham · Luc Evers · Victor Rodriguez · Vipul Satone · Dianbo Liu · Angeline Yasodhara · Geoff Tison · Ligin Solamen · Bryan He · Rahul Ladhania · Yipeng Shi · Md Nafiz Hamid · Pouria Mashouri · Woochan Hwang · Sejin Park · Xu Chen · Rachneet Kaur · Davis Blalock · Holly Wiberg · Parminder Bhatia · Kezi Yu · RUMENG LI · Jun Sakuma · Charles Ding · Aaron Babier · Yong Cai · A Pratap · Luke O'Connor · Allen Nie · Martin Kang · Ian Covert · Xun Wang · Zelun Luo · Serena Yeung · William Boag · Kazuki Tachikawa · Mary Saltz · Owen Lahav · Edward Lee · Eric Teasley · Michael Kamp · Nirmesh Patel · Vishwali Mhasawade · Maxim Samarin · Ryo Uchimido · Farzad Khalvati · Francisco Cruz · Laura Symul · Zaid Nabulsi · Mads Mihailescu · Rosalind Picard -
2018 : Poster session: Contributed papers »
Michael Cvitkovic · Arijit Patra · Yunpeng Li · RAHMAN BANYA SAFF SANYA · Guanghua Chi · Benjamin Huynh · Hamed Alemohammad · Simón Ramírez Amaya · Nazmus Saquib · Jade Abbott · Teo de Campos · Viraj Prabhu · Alvaro Riascos · Hafte Abera · praney dubey · Tanushyam Chattopadhyay · Hsiang Hsu · Mayank Jain · Kartikeya Bhardwaj · Gabriel Cadamuro · Bradley Gram-Hansen · Georg Dorffner -
2018 : Contributed talk 1: Privacy Amplification by Iteration »
Vitaly Feldman -
2018 : Poster Session (All Posters) »
Artemiy Margaritov · Ravichandra Addanki · Hamidreza Mahyar · GUO ZHANG · avani wildani · Hadi Esmaeilzadeh · Dmitrii Ustiugov · Shaileshh Bojja Venkatakrishnan · Fabian Ruffy Varga · adit bhardwaj · Tatiana Shpeisman -
2018 Workshop: Machine Learning for Molecules and Materials »
José Miguel Hernández-Lobato · Klaus-Robert Müller · Brooks Paige · Matt Kusner · Stefan Chmiela · Kristof Schütt -
2018 Workshop: Critiquing and Correcting Trends in Machine Learning »
Thomas Rainforth · Matt Kusner · Benjamin Bloem-Reddy · Brooks Paige · Rich Caruana · Yee Whye Teh -
2018 Poster: Empirical Risk Minimization in Non-interactive Local Differential Privacy Revisited »
Di Wang · Marco Gaboardi · Jinhui Xu -
2018 Poster: The Everlasting Database: Statistical Validity at a Fair Price »
Blake Woodworth · Vitaly Feldman · Saharon Rosset · Nati Srebro -
2018 Poster: Sanity Checks for Saliency Maps »
Julius Adebayo · Justin Gilmer · Michael Muelly · Ian Goodfellow · Moritz Hardt · Been Kim -
2018 Poster: Generalization Bounds for Uniformly Stable Algorithms »
Vitaly Feldman · Jan Vondrak -
2018 Spotlight: Sanity Checks for Saliency Maps »
Julius Adebayo · Justin Gilmer · Michael Muelly · Ian Goodfellow · Moritz Hardt · Been Kim -
2018 Spotlight: Generalization Bounds for Uniformly Stable Algorithms »
Vitaly Feldman · Jan Vondrak -
2018 Poster: Local Differential Privacy for Evolving Data »
Matthew Joseph · Aaron Roth · Jonathan Ullman · Bo Waggoner -
2018 Poster: Differentially Private Testing of Identity and Closeness of Discrete Distributions »
Jayadev Acharya · Ziteng Sun · Huanyu Zhang -
2018 Spotlight: Local Differential Privacy for Evolving Data »
Matthew Joseph · Aaron Roth · Jonathan Ullman · Bo Waggoner -
2018 Spotlight: Differentially Private Testing of Identity and Closeness of Discrete Distributions »
Jayadev Acharya · Ziteng Sun · Huanyu Zhang -
2017 : Poster session »
Uwe Naumann · Lane Schwartz · Richard Wei · Eric Meissner · Jeff Druce · Zeming Lin · Alex Pothen · Edward Yang -
2017 : Generating Natural Adversarial Examples »
Zhengli Zhao -
2017 : Strategic Classification from Revealed Preferences »
Jinshuo Dong -
2017 Workshop: Machine Learning for Molecules and Materials »
Kristof Schütt · Klaus-Robert Müller · Anatole von Lilienfeld · José Miguel Hernández-Lobato · Klaus-Robert Müller · Alan Aspuru-Guzik · Bharath Ramsundar · Matt Kusner · Brooks Paige · Stefan Chmiela · Alexandre Tkatchenko · Anatole von Lilienfeld · Koji Tsuda -
2017 Poster: Accuracy First: Selecting a Differential Privacy Level for Accuracy Constrained ERM »
Katrina Ligett · Seth Neel · Aaron Roth · Bo Waggoner · Steven Wu -
2017 Poster: Counterfactual Fairness »
Matt Kusner · Joshua Loftus · Chris Russell · Ricardo Silva -
2017 Oral: Counterfactual Fairness »
Matt Kusner · Joshua Loftus · Chris Russell · Ricardo Silva -
2017 Poster: Differentially Private Empirical Risk Minimization Revisited: Faster and More General »
Di Wang · Minwei Ye · Jinhui Xu -
2017 Poster: When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness »
Chris Russell · Matt Kusner · Joshua Loftus · Ricardo Silva -
2017 Tutorial: Differentially Private Machine Learning: Theory, Algorithms and Applications »
Kamalika Chaudhuri · Anand D Sarwate -
2016 : Vitaly Feldman »
Vitaly Feldman -
2016 Workshop: Adaptive Data Analysis »
Vitaly Feldman · Aaditya Ramdas · Aaron Roth · Adam Smith -
2016 Poster: Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back »
Vitaly Feldman -
2016 Oral: Generalization of ERM in Stochastic Convex Optimization: The Dimension Strikes Back »
Vitaly Feldman -
2016 Poster: Bi-Objective Online Matching and Submodular Allocations »
Hossein Esfandiari · Nitish Korula · Vahab Mirrokni -
2016 Poster: Sample Complexity of Automated Mechanism Design »
Maria-Florina Balcan · Tuomas Sandholm · Ellen Vitercik -
2016 Poster: Fairness in Learning: Classic and Contextual Bandits »
Matthew Joseph · Michael Kearns · Jamie Morgenstern · Aaron Roth -
2015 Workshop: Adaptive Data Analysis »
Adam Smith · Aaron Roth · Vitaly Feldman · Moritz Hardt -
2015 Poster: Generalization in Adaptive Data Analysis and Holdout Reuse »
Cynthia Dwork · Vitaly Feldman · Moritz Hardt · Toni Pitassi · Omer Reingold · Aaron Roth -
2015 Poster: Subsampled Power Iteration: a Unified Algorithm for Block Models and Planted CSP's »
Vitaly Feldman · Will Perkins · Santosh Vempala -
2014 Poster: Minimax-optimal Inference from Partial Rankings »
Bruce Hajek · Sewoong Oh · Jiaming Xu -
2013 Poster: Statistical Active Learning Algorithms »
Maria-Florina F Balcan · Vitaly Feldman -
2013 Poster: Auditing: Active Learning with Outcome-Dependent Query Costs »
Sivan Sabato · Anand D Sarwate · Nati Srebro -
2012 Poster: Near-optimal Differentially Private Principal Components »
Kamalika Chaudhuri · Anand D Sarwate · Kaushik Sinha