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Spotlights
Guangneng Hu · Ke Li · Aviral Kumar · Phi Vu Tran · Samuel G. Fadel · Rita Kuznetsova · Bong-Nam Kang · Behrouz Haji Soleimani · Jinwon An · Nathan de Lara · Anjishnu Kumar · Tillman Weyde · Melanie Weber · Kristen Altenburger · Saeed Amizadeh · Xiaoran Xu · Yatin Nandwani · Yang Guo · Maria Pacheco · William Fedus · Guillaume Jaume · Yuka Yoneda · Yunpu Ma · Yunsheng Bai · Berk Kapicioglu · Maximilian Nickel · Fragkiskos Malliaros · Beier Zhu · Aleksandar Bojchevski · Joshua Joseph · Gemma Roig · Esma Balkir · Xander Steenbrugge
Author Information
Guangneng Hu (HKUST)
a 3rd year PhD candidate in CSE at HKUST
Ke Li (UC Berkeley)
Aviral Kumar (UC Berkeley)
Phi Vu Tran (Booz Allen Hamilton)
Machine Learning Scientist
Samuel G. Fadel (University of Campinas)
Rita Kuznetsova (Moscow Institute of Physics and Technology, Antiplagiat Company)
Bong-Nam Kang (POSTECH)
Behrouz Haji Soleimani (Dalhousie University)
Jinwon An (Seoul National University)
Nathan de Lara (Télécom ParisTech)
Anjishnu Kumar (Amazon)
Tillman Weyde (City, University of London)
Melanie Weber (Princeton University)
Kristen Altenburger (Stanford University)
Saeed Amizadeh (Microsoft)
Xiaoran Xu (Hulu)
Yatin Nandwani (Indian Institute Of Technology Delhi)
Yang Guo (University of Wisconsin Madison)
Maria Pacheco (Purdue University)
William Fedus (MILA/Google Brain)
Guillaume Jaume (EPFL/IBM Research)
Yuka Yoneda (The Institute of Scientific and Industrial Research, Osaka University)
Yunpu Ma (Ludwig Maximilian University of Munich & Siemens CT)
Yunsheng Bai (University of California, Los Angeles)
Berk Kapicioglu (OccamzRazor)
Maximilian Nickel (Facebook AI Research)
Fragkiskos Malliaros (CentraleSupelec, University of Paris-Saclay)
Beier Zhu (Tsinghua University)
Aleksandar Bojchevski (Technical University of Munich)
Joshua Joseph (Massachusetts Institute of Technology)
Gemma Roig (SUTD)
Esma Balkir (University of Edinburgh)
Xander Steenbrugge (UGent)
More from the Same Authors
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2021 : HiRID-ICU-Benchmark --- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data »
Hugo Yèche · Rita Kuznetsova · Marc Zimmermann · Matthias Hüser · Xinrui Lyu · Martin Faltys · Gunnar Rätsch -
2021 Spotlight: Revisiting ResNets: Improved Training and Scaling Strategies »
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2021 : Data Sharing without Rewards in Multi-Task Offline Reinforcement Learning »
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2021 : Should I Run Offline Reinforcement Learning or Behavioral Cloning? »
Aviral Kumar · Joey Hong · Anikait Singh · Sergey Levine -
2021 : DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization »
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2022 : Mixed-Membership Community Detection via Line Graph Curvature »
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2022 : Exploring the Long-Term Generalization of Counting Behavior in RNNs »
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2022 : Best of Both Worlds: Towards Adversarial Robustness with Transduction and Rejection »
Nils Palumbo · Yang Guo · Xi Wu · Jiefeng Chen · Yingyu Liang · Somesh Jha -
2022 Workshop: 3rd Offline Reinforcement Learning Workshop: Offline RL as a "Launchpad" »
Aviral Kumar · Rishabh Agarwal · Aravind Rajeswaran · Wenxuan Zhou · George Tucker · Doina Precup · Aviral Kumar -
2022 Poster: A Solver-free Framework for Scalable Learning in Neural ILP Architectures »
Yatin Nandwani · Rishabh Ranjan · - Mausam · Parag Singla -
2021 : Speaker Intro »
Aviral Kumar · George Tucker -
2021 : Speaker Intro »
Aviral Kumar · George Tucker -
2021 : Speaker Intro »
Rishabh Agarwal · Aviral Kumar -
2021 : Speaker Intro »
Rishabh Agarwal · Aviral Kumar -
2021 Workshop: Offline Reinforcement Learning »
Rishabh Agarwal · Aviral Kumar · George Tucker · Justin Fu · Nan Jiang · Doina Precup · Aviral Kumar -
2021 : Opening Remarks »
Rishabh Agarwal · Aviral Kumar -
2021 : Gotta Go Fast with Score-Based Generative Models »
Alexia Jolicoeur-Martineau · Ke Li · Rémi Piché-Taillefer · Tal Kachman · Ioannis Mitliagkas -
2021 : DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization Q&A »
Aviral Kumar · Rishabh Agarwal · Tengyu Ma · Aaron Courville · George Tucker · Sergey Levine -
2021 : DR3: Value-Based Deep Reinforcement Learning Requires Explicit Regularization »
Aviral Kumar · Rishabh Agarwal · Tengyu Ma · Aaron Courville · George Tucker · Sergey Levine -
2021 Poster: Robustness of Graph Neural Networks at Scale »
Simon Geisler · Tobias Schmidt · Hakan Şirin · Daniel Zügner · Aleksandar Bojchevski · Stephan Günnemann -
2021 Poster: COMBO: Conservative Offline Model-Based Policy Optimization »
Tianhe Yu · Aviral Kumar · Rafael Rafailov · Aravind Rajeswaran · Sergey Levine · Chelsea Finn -
2021 Poster: Conservative Data Sharing for Multi-Task Offline Reinforcement Learning »
Tianhe Yu · Aviral Kumar · Yevgen Chebotar · Karol Hausman · Sergey Levine · Chelsea Finn -
2021 Poster: Variational Model Inversion Attacks »
Kuan-Chieh Wang · YAN FU · Ke Li · Ashish Khisti · Richard Zemel · Alireza Makhzani -
2021 Poster: Why Generalization in RL is Difficult: Epistemic POMDPs and Implicit Partial Observability »
Dibya Ghosh · Jad Rahme · Aviral Kumar · Amy Zhang · Ryan Adams · Sergey Levine -
2021 Poster: Revisiting ResNets: Improved Training and Scaling Strategies »
Irwan Bello · William Fedus · Xianzhi Du · Ekin Dogus Cubuk · Aravind Srinivas · Tsung-Yi Lin · Jonathon Shlens · Barret Zoph -
2020 : Design-Bench: Benchmarks for Data-Driven Offline Model-Based Optimization »
Brandon Trabucco · Aviral Kumar · XINYANG GENG · Sergey Levine -
2020 : Conservative Objective Models: A Simple Approach to Effective Model-Based Optimization »
Brandon Trabucco · Aviral Kumar · XINYANG GENG · Sergey Levine -
2020 : Panel »
Emma Brunskill · Nan Jiang · Nando de Freitas · Finale Doshi-Velez · Sergey Levine · John Langford · Lihong Li · George Tucker · Rishabh Agarwal · Aviral Kumar -
2020 Workshop: Offline Reinforcement Learning »
Aviral Kumar · Rishabh Agarwal · George Tucker · Lihong Li · Doina Precup · Aviral Kumar -
2020 : Introduction »
Aviral Kumar · George Tucker · Rishabh Agarwal -
2020 : Invited Talk 6: Learning a robust classifier in hyperbolic space »
Melanie Weber -
2020 Poster: Riemannian Continuous Normalizing Flows »
Emile Mathieu · Maximilian Nickel -
2020 Poster: Robust large-margin learning in hyperbolic space »
Melanie Weber · Manzil Zaheer · Ankit Singh Rawat · Aditya Menon · Sanjiv Kumar -
2020 Poster: One Solution is Not All You Need: Few-Shot Extrapolation via Structured MaxEnt RL »
Saurabh Kumar · Aviral Kumar · Sergey Levine · Chelsea Finn -
2020 Tutorial: (Track3) Offline Reinforcement Learning: From Algorithm Design to Practical Applications »
Sergey Levine · Aviral Kumar -
2019 : Posters »
Timo Denk · Ioannis Androutsopoulos · Oleg Bakhteev · Mohamed Kane · Petar Stojanov · Seunghyun Park · Bharat Mamidibathula · Kostiantyn Liepieshov · Johannes Höhne · Song Feng · Zikri Bayraktar · Kehinde Aruleba · ALEKSANDR OGALTSOV · Rita Kuznetsova · Paul Bennett · Saghar Hosseini · Kshtij Fadnis · Luis Lastras · Mehrdad Jabbarzadeh Gangeh · Christian Reisswig · Emad Elwany · Ilias Chalkidis · Jonathan DeGange · Kaixuan Zhang · Luke de Oliveira · Muhammed Koçyiğit · Haoyu Dong · Vera Liao · Wonseok Hwang -
2019 : Contributed Talk #3 MEMENTO: Further Progress Through Forgetting »
William Fedus -
2019 : Poster Spotlights B (13 posters) »
Alberto Camacho · Chris Percy · Vaishak Belle · Beliz Gunel · Toryn Klassen · Tillman Weyde · Mohamed Ghalwash · Siddhant Arora · León Illanes · Jonathan Raiman · Qing Wang · Alexander Lew · So Yeon Min -
2019 : Poster Session »
Rishav Chourasia · Yichong Xu · Corinna Cortes · Chien-Yi Chang · Yoshihiro Nagano · So Yeon Min · Benedikt Boecking · Phi Vu Tran · Kamyar Ghasemipour · Qianggang Ding · Shouvik Mani · Vikram Voleti · Rasool Fakoor · Miao Xu · Kenneth Marino · Lisa Lee · Volker Tresp · Jean-Francois Kagy · Marvin Zhang · Barnabas Poczos · Dinesh Khandelwal · Adrien Bardes · Evan Shelhamer · Jiacheng Zhu · Ziming Li · Xiaoyan Li · Dmitrii Krasheninnikov · Ruohan Wang · Mayoore Jaiswal · Emad Barsoum · Suvansh Sanjeev · Theeraphol Wattanavekin · Qizhe Xie · Sifan Wu · Yuki Yoshida · David Kanaa · Sina Khoshfetrat Pakazad · Mehdi Maasoumy -
2019 : Posters and Coffee »
Sameer Kumar · Tomasz Kornuta · Oleg Bakhteev · Hui Guan · Xiaomeng Dong · Minsik Cho · Sören Laue · Theodoros Vasiloudis · Andreea Anghel · Erik Wijmans · Zeyuan Shang · Oleksii Kuchaiev · Ji Lin · Susan Zhang · Ligeng Zhu · Beidi Chen · Vinu Joseph · Jialin Ding · Jonathan Raiman · Ahnjae Shin · Vithursan Thangarasa · Anush Sankaran · Akhil Mathur · Martino Dazzi · Markus Löning · Darryl Ho · Emanuel Zgraggen · Supun Nakandala · Tomasz Kornuta · Rita Kuznetsova -
2019 : Coffee Break & Poster Session »
Samia Mohinta · Andrea Agostinelli · Alexandra Moringen · Jee Hang Lee · Yat Long Lo · Wolfgang Maass · Blue Sheffer · Colin Bredenberg · Benjamin Eysenbach · Liyu Xia · Stratis Markou · Jan Lichtenberg · Pierre Richemond · Tony Zhang · JB Lanier · Baihan Lin · William Fedus · Glen Berseth · Marta Sarrico · Matthew Crosby · Stephen McAleer · Sina Ghiassian · Franz Scherr · Guillaume Bellec · Darjan Salaj · Arinbjörn Kolbeinsson · Matthew Rosenberg · Jaehoon Shin · Sang Wan Lee · Guillermo Cecchi · Irina Rish · Elias Hajek -
2019 : Poster Spotlights A (23 posters) »
DongHa Bahn · Xiaoran Xu · Shih-Chieh Su · Daniel Cunnington · Wonseok Hwang · Sarthak Dash · Alberto Camacho · Theodoros Salonidis · Shiyang Li · Yuyu Zhang · Habibeh Naderi · Zhe Zeng · Pasha Khosravi · Pedro Colon-Hernandez · Dimitris Diochnos · David Windridge · Robin Manhaeve · Vaishak Belle · Brendan Juba · Naveen Sundar Govindarajulu · Joe Bockhorst -
2019 Poster: A Primal Dual Formulation For Deep Learning With Constraints »
Yatin Nandwani · Abhishek Pathak · Mausam · Parag Singla -
2019 Poster: Hyperbolic Graph Neural Networks »
Qi Liu · Maximilian Nickel · Douwe Kiela -
2019 Poster: Graph Normalizing Flows »
Jenny Liu · Aviral Kumar · Jimmy Ba · Jamie Kiros · Kevin Swersky -
2019 Poster: Certifiable Robustness to Graph Perturbations »
Aleksandar Bojchevski · Stephan Günnemann -
2019 Poster: Approximate Feature Collisions in Neural Nets »
Ke Li · Tianhao Zhang · Jitendra Malik -
2018 : Spotlights 2 »
Mausam · Ankit Anand · Parag Singla · Tarik Koc · Tim Klinger · Habibeh Naderi · Sungwon Lyu · Saeed Amizadeh · Kshitij Dwivedi · Songpeng Zu · Wei Feng · Balaraman Ravindran · Edouard Pineau · Abdulkadir Celikkanat · Deepak Venugopal -
2018 : Contributed Talk 3 »
Yunsheng Bai -
2018 : Poster Sessions and Lunch (Provided) »
Akira Utsumi · Alane Suhr · Ji Zhang · Ramon Sanabria · Kushal Kafle · Nicholas Chen · Seung Wook Kim · Aishwarya Agrawal · SRI HARSHA DUMPALA · Shikhar Murty · Pablo Azagra · Jean ROUAT · Alaaeldin Ali · · SUBBAREDDY OOTA · Angela Lin · Shruti Palaskar · Farley Lai · Amir Aly · Tingke Shen · Dianqi Li · Jianguo Zhang · Rita Kuznetsova · Jinwon An · Jean-Benoit Delbrouck · Tomasz Kornuta · Syed Ashar Javed · Christopher Davis · John Co-Reyes · Vasu Sharma · Sungwon Lyu · Ning Xie · Ankita Kalra · Huan Ling · Oleksandr Maksymets · Bhavana Mahendra Jain · Shun-Po Chuang · Sanyam Agarwal · Jerome Abdelnour · Yufei Feng · vincent albouy · Siddharth Karamcheti · Derek Doran · Roberta Raileanu · Jonathan Heek -
2017 : Poster Session (encompasses coffee break) »
Beidi Chen · Borja Balle · Daniel Lee · iuri frosio · Jitendra Malik · Jan Kautz · Ke Li · Masashi Sugiyama · Miguel A. Carreira-Perpinan · Ramin Raziperchikolaei · Theja Tulabandhula · Yung-Kyun Noh · Adams Wei Yu -
2017 : Fast k-Nearest Neighbor Search via Prioritized DCI »
Ke Li -
2017 : Learning Hierarchical Representations of Relational Data »
Maximilian Nickel -
2017 Poster: Do Deep Neural Networks Suffer from Crowding? »
Anna Volokitin · Gemma Roig · Tomaso Poggio -
2016 Workshop: Learning with Tensors: Why Now and How? »
Anima Anandkumar · Rong Ge · Yan Liu · Maximilian Nickel · Qi (Rose) Yu -
2015 Symposium: Brains, Minds and Machines »
Gabriel Kreiman · Tomaso Poggio · Maximilian Nickel -
2014 Poster: Reducing the Rank in Relational Factorization Models by Including Observable Patterns »
Maximilian Nickel · Xueyan Jiang · Volker Tresp -
2014 Spotlight: Reducing the Rank in Relational Factorization Models by Including Observable Patterns »
Maximilian Nickel · Xueyan Jiang · Volker Tresp