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Comfetch: Federated Learning of Large Networks on Memory-Constrained Clients via Sketching


Sep 17, 2021
Tahseen Rabbani, Brandon Feng, Yifan Yang, Arjun Rajkumar, Amitabh Varshney, Furong Huang


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Practical and Fast Momentum-Based Power Methods


Aug 20, 2021
Tahseen Rabbani, Apollo Jain, Arjun Rajkumar, Furong Huang


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Datasets for Studying Generalization from Easy to Hard Examples


Aug 13, 2021
Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Arpit Bansal, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein


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Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability


Aug 03, 2021
Roman Levin, Manli Shu, Eitan Borgnia, Furong Huang, Micah Goldblum, Tom Goldstein


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Certified Defense via Latent Space Randomized Smoothing with Orthogonal Encoders


Aug 01, 2021
Huimin Zeng, Jiahao Su, Furong Huang


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Scaling-up Diverse Orthogonal Convolutional Networks with a Paraunitary Framework


Jun 16, 2021
Jiahao Su, Wonmin Byeon, Furong Huang


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Who Is the Strongest Enemy? Towards Optimal and Efficient Evasion Attacks in Deep RL


Jun 09, 2021
Yanchao Sun, Ruijie Zheng, Yongyuan Liang, Furong Huang


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Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks


Jun 08, 2021
Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Furong Huang, Uzi Vishkin, Micah Goldblum, Tom Goldstein


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Guided Hyperparameter Tuning Through Visualization and Inference


May 24, 2021
Hyekang Joo, Calvin Bao, Ishan Sen, Furong Huang, Leilani Battle


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Insta-RS: Instance-wise Randomized Smoothing for Improved Robustness and Accuracy


Mar 21, 2021
Chen Chen, Kezhi Kong, Peihong Yu, Juan Luque, Tom Goldstein, Furong Huang


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DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations


Mar 02, 2021
Eitan Borgnia, Jonas Geiping, Valeriia Cherepanova, Liam Fowl, Arjun Gupta, Amin Ghiasi, Furong Huang, Micah Goldblum, Tom Goldstein

* 11 pages, 5 figures 

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Are Adversarial Examples Created Equal? A Learnable Weighted Minimax Risk for Robustness under Non-uniform Attacks


Oct 24, 2020
Huimin Zeng, Chen Zhu, Tom Goldstein, Furong Huang


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Vulnerability-Aware Poisoning Mechanism for Online RL with Unknown Dynamics


Sep 02, 2020
Yanchao Sun, Furong Huang


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Adaptive Learning Rates with Maximum Variation Averaging


Jun 21, 2020
Chen Zhu, Yu Cheng, Zhe Gan, Furong Huang, Jingjing Liu, Tom Goldstein


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Using Wavelets and Spectral Methods to Study Patterns in Image-Classification Datasets


Jun 17, 2020
Roozbeh Yousefzadeh, Furong Huang


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Convolutional Tensor-Train LSTM for Spatio-temporal Learning


Mar 22, 2020
Jiahao Su, Wonmin Byeon, Furong Huang, Jan Kautz, Animashree Anandkumar

* Jiahao Su and Wonmin Byeon contributed equally to this work. 17 pages, 14 figures 

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Improving the Tightness of Convex Relaxation Bounds for Training Certifiably Robust Classifiers


Feb 22, 2020
Chen Zhu, Renkun Ni, Ping-yeh Chiang, Hengduo Li, Furong Huang, Tom Goldstein


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TempLe: Learning Template of Transitions for Sample Efficient Multi-task RL


Feb 16, 2020
Yanchao Sun, Xiangyu Yin, Furong Huang


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ARMA Nets: Expanding Receptive Field for Dense Prediction


Feb 15, 2020
Jiahao Su, Shiqi Wang, Furong Huang


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Understanding Generalization in Deep Learning via Tensor Methods


Jan 14, 2020
Jingling Li, Yanchao Sun, Jiahao Su, Taiji Suzuki, Furong Huang

* 9 pages (main paper), 42 pages (full version) 

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Can Agents Learn by Analogy? An Inferable Model for PAC Reinforcement Learning


Dec 21, 2019
Yanchao Sun, Furong Huang


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Sampling-Free Learning of Bayesian Quantized Neural Networks


Dec 06, 2019
Jiahao Su, Milan Cvitkovic, Furong Huang


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Label Smoothing and Logit Squeezing: A Replacement for Adversarial Training?


Oct 25, 2019
Ali Shafahi, Amin Ghiasi, Furong Huang, Tom Goldstein


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Understanding Generalization through Visualizations


Jul 16, 2019
W. Ronny Huang, Zeyad Emam, Micah Goldblum, Liam Fowl, Justin K. Terry, Furong Huang, Tom Goldstein

* 8 pages (excluding acknowledgments and references), 8 figures 

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SysML: The New Frontier of Machine Learning Systems


May 01, 2019
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Jennifer Chayes, Eric Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim Hazelwood, Furong Huang, Martin Jaggi, Kevin Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konečný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Aparna Lakshmiratan, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Murray, Kunle Olukotun, Dimitris Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar


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