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Coffee Break & Poster Session 1
Yan Zhang · Jonathon Hare · Adam Prugel-Bennett · Po Leung · Patrick Flaherty · Pitchaya Wiratchotisatian · Alessandro Epasto · Silvio Lattanzi · Sergei Vassilvitskii · Morteza Zadimoghaddam · Theja Tulabandhula · Fabian Fuchs · Adam Kosiorek · Ingmar Posner · William Hang · Anna Goldie · Sujith Ravi · Azalia Mirhoseini · Yuwen Xiong · Mengye Ren · Renjie Liao · Raquel Urtasun · Haici Zhang · Michele Borassi · Shengda Luo · Andrew Trapp · Geoffroy Dubourg-Felonneau · Yasmeen Kussad · Christopher Bender · Manzil Zaheer · Junier Oliva · Michał Stypułkowski · Maciej Zieba · Austin Dill · Chun-Liang Li · Songwei Ge · Eunsu Kang · Oiwi Parker Jones · Kelvin Ka Wing Wong · Joshua Payne · Yang Li · Azade Nazi · Erkut Erdem · Aykut Erdem · Kevin O'Connor · Juan J Garcia · Maciej Zamorski · Jan Chorowski · Deeksha Sinha · Harry Clifford · John W Cassidy

Sat Dec 14 09:45 AM -- 10:30 AM (PST) @

Poster Session 1 Paper Titles & Authors:

Deep Set Prediction Networks. Yan Zhang, Jonathon Hare, Adam Prügel-Bennett

Deep Hyperedges: a Framework for Transductive and Inductive Learning on Hypergraphs. Joshua Payne

FSPool: Learning Set Representations with Featurewise Sort Pooling. Yan Zhang, Jonathon Hare, Adam Prügel-Bennett

Deep Learning Features Through Dictionary Learning with Improved Clustering for Image Classification. Shengda Luo, Alex Po Leung, Haici Zhang

Globally Optimal Model-based Clustering via Mixed Integer Nonlinear Programming. Patrick Flaherty, Pitchaya Wiratchotisatian, Andrew C. Trapp

Sliding Window Algorithms for k-Clustering Problems. Michele Borassi, Alessandro Epasto, Silvio Lattanzi, Sergei Vassilvitski, Morteza Zadimoghaddam

Optimized Recommendations When Customers Select Multiple Products. Prasoon Patidar, Deeksha Sinha, Theja Tulabandhula

Manipulating Person Videos with Natural Language. Levent Karacan, Mehmet Gunel, Aykut Erdem, Erkut Erdem

Permutation Invariance and Relational Reasoning in Multi-Object Tracking. Fabian B. Fuchs, Adam R. Kosiorek, Li Sun, Oiwi Parker Jones, Ingmar Posner.

Clustering by Learning to Optimize Normalized Cuts. Azade Nazi, Will Hang, Anna Goldie, Sujith Ravi, Azalia Mirhoseini

Deformable Filter Convolution for Point Cloud Reasoning. Yuwen Xiong, Mengye Ren, Renjie Liao, Kelvin Wong, Raquel Urtasun

Learning Embeddings from Cancer Mutation Sets for Classification Tasks. Geoffroy Dubourg-Felonneau, Yasmeen Kussad, Dominic Kirkham, John Cassidy, Harry W Clifford

Exchangeable Generative Models with Flow Scans. Christopher M. Bender, Kevin O'Connor, Yang Li, Juan Jose Garcia, Manzil Zaheer, Junier Oliva

Conditional Invertible Flow for Point Cloud Generation. Stypulkowski Michal, Zamorski Maciej, Zieba Maciej, Chorowski Jan

Getting Topology and Point Cloud Generation to Mesh. Austin Dill, Chun-Liang Li, Songwei Ge, Eunsu Kang

Distributed Balanced Partitioning and Applications in Large-scale Load Balancing. Aaron Archer, Kevin Aydin, MohammadHossein Bateni, Vahab Mirrokni, Aaron Schild, Ray Yang, Richard Zhuang

Author Information

Yan Zhang (University of Southampton)

Samsung @ Mila is hiring research scientists in an academic-style lab :)

Jonathon Hare (University of Southampton)
Adam Prugel-Bennett (apb@ecs.soton.ac.uk)
Po Leung (Macau University of Science and Technology)

I am an assistant professor at the Faculty of Information Technology of the Macau University of Science and Technology. I was a quantitative analyst in finance at Sentient Technologies from 2013 to 2015. I got my PhD in 2008 under Shaogang Gong in the Vision Group of the Department of Computer Science at Queen Mary, University of London. After my PhD studies, I became a postdoctoral researcher in machine learning working with Peter Auer in Austria. I was born in Hong Kong. I studied Information Technology (BSc) at the Department of Electronic Engineering of the City University of Hong Kong and astrophysics for my MPhil to work with KS Cheng and CS Pun at the Department of Physics at the University of Hong Kong.

Patrick Flaherty (University of Massachusetts, Amherst)
Pitchaya Wiratchotisatian (Worcester Polytechnic Institute)
Alessandro Epasto (Google)
Alessandro Epasto

I am a staff research scientist at Google, New York working in the Google Research Algorithms and Optimization team lead by Vahab Mirrokni. I received a Ph.D in computer science from Sapienza University of Rome, where I was advised by Professor Alessandro Panconesi and supported by the Google Europe Ph.D. Fellowship in Algorithms, 2011. I was also a post-doc at the department of computer science of Brown University in Providence (RI), USA where I was advised by Professor Eli Upfal. My research interests include algorithmic problems in machine learning and data mining, in particular in the areas of clustering, privacy, and large scale graphs analysis.

Silvio Lattanzi (Google Research)
Sergei Vassilvitskii (Google)
Morteza Zadimoghaddam (Google Research)
Theja Tulabandhula (University of Illinois Chicago)

Theja is a researcher working in the areas of reinforcement, online and deep machine learning with applications to transportation, retail and other fields. He received his combined bachelors and masters degree in electrical engineering with honors from Indian Institute of Technology, Kharagpur, in 2009. There, he was awarded the Prime Minister of India Gold medal for getting the highest GPA among all dual degree students. He received his Ph.D. degree in 2014, in electrical engineering and computer science at the Massachusetts Institute of Technology (MIT), Cambridge. There, he was a Xerox-MIT fellow and a Science and Technology Fulbright scholar. Please visit http://www.theja.org/ for more information!

Fabian Fuchs (University of Oxford)
Fabian Fuchs

I am a Research Scientist at DeepMind and part of their Science team. After an undergrad in physics, I did my PhD at the Applied AI lab (A2I), supervised by Professor Ingmar Posner. In 2020, I did a research sabbatical at the BCAI collaborating with Max Welling’s lab at the University of Amsterdam.

Adam Kosiorek (University of Oxford)
Ingmar Posner (Oxford University)
William Hang (Stanford University)
Anna Goldie (Google Brain / Stanford)
Sujith Ravi (Google Research)
Azalia Mirhoseini (Google Brain)
Yuwen Xiong (Uber ATG / University of Toronto)
Mengye Ren (University of Toronto)
Renjie Liao (University of Toronto)
Raquel Urtasun (Uber ATG)
Haici Zhang (Macau University of Science and Technology)
Michele Borassi (Google Switzerland GmbH)
Shengda Luo (Macau University of Science and Technology)
Andrew Trapp (Worcester Polytechnic Institute)
Geoffroy Dubourg-Felonneau (Cambridge Cancer Genomics)
Yasmeen Kussad (Lancaster University)

I am a fresh MSc Data Science graduate with a concentration in unsupervised deep learning. I am interested in the social applications of the developing machine learning methods.

Christopher Bender (The University of North Carolina)
Manzil Zaheer (Google)
Junier Oliva (UNC - Chapel Hill)
Michał Stypułkowski (Tooploox Sp. z o.o.)
Maciej Zieba (Wroclaw University of Science and Technology, Tooploox)
Austin Dill (Carnegie Mellon University)
Chun-Liang Li (Carnegie Mellon University)
Songwei Ge (Carnegie Mellon University)
Eunsu Kang (Carnegie Mellon University)
Oiwi Parker Jones (University of Oxford)
Kelvin Ka Wing Wong (University of Toronto / Uber ATG)
Joshua Payne (Stanford University)

I'm an undergraduate studying Mathematical and Computational Science and Mathematics at Stanford University, as well as a research intern at IBM Research, where I received the prestigious Inventor Plateau for filing 4+ patents related to digital identity and deep learning on graphs. My academic interests include statistical learning for graphs and hypergraphs and quantum computing, and I'm currently considering Ph.D. programs in computer science.

Yang Li (UNC-Chapel Hill)
Azade Nazi (Google)
Erkut Erdem (Hacettepe University)
Aykut Erdem (Hacettepe University)
Kevin O'Connor (University of North Carolina, Chapel Hill)

PhD Student in Statistics at UNC Chapel Hill. My interests include optimal transport, machine learning methods for sets and statistical learning theory.

Juan J Garcia (University of North Carolina at Chapel Hill)
Maciej Zamorski (Wrocław University of Science and Technology / Tooploox)
Jan Chorowski (University of Wroclaw)
Deeksha Sinha (Massachusetts Institute of Technology)
Harry Clifford (Cambridge Cancer Genomics)
John W Cassidy (Cambridge Cancer Genomics)

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