Nearest Neighbor Classifiers over Incomplete Information: From Certain Answers to Certain Predictions

May 12, 2020
Bojan Karlaš, Peng Li, Renzhi Wu, Nezihe Merve Gürel, Xu Chu, Wentao Wu, Ce Zhang


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Control, Generate, Augment: A Scalable Framework for Multi-Attribute Text Generation

Apr 30, 2020
Giuseppe Russo, Nora Hollenstein, Claudiu Musat, Ce Zhang


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Improving BERT with Self-Supervised Attention

Apr 29, 2020
Xiaoyu Kou, Yaming Yang, Yujing Wang, Ce Zhang, Yiren Chen, Yunhai Tong, Yan Zhang, Jing Bai


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TrueBranch: Metric Learning-based Verification of Forest Conservation Projects

Apr 21, 2020
Simona Santamaria, David Dao, Björn Lütjens, Ce Zhang

* *Authors have contributed equally. Published as Spotlight Presentation at ICLR 2020 Workshop on Tackling Climate Change with Machine Learning 

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Provable Robust Learning Based on Transformation-Specific Smoothing

Mar 20, 2020
Linyi Li, Maurice Weber, Xiaojun Xu, Luka Rimanic, Tao Xie, Ce Zhang, Bo Li

* Corrected typos in Appendix 

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RAB: Provable Robustness Against Backdoor Attacks

Mar 19, 2020
Maurice Weber, Xiaojun Xu, Bojan Karlas, Ce Zhang, Bo Li


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End-to-end Robustness for Sensing-Reasoning Machine Learning Pipelines

Mar 06, 2020
Zhuolin Yang, Zhikuan Zhao, Hengzhi Pei, Boxin Wang, Bojan Karlas, Ji Liu, Heng Guo, Bo Li, Ce Zhang

* 43 pages, 9 figures 

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A Robust Imbalanced SAR Image Change Detection Approach Based on Deep Difference Image and PCANet

Mar 03, 2020
Xinzheng Zhang, Hang Su, Ce Zhang, Peter M. Atkinson, Xiaoheng Tan, Xiaoping Zeng, Xin Jian

* 5 pages, 4 figures 

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Two-Phase Object-Based Deep Learning for Multi-temporal SAR Image Change Detection

Jan 17, 2020
Xinzheng Zhang, Guo Liu, Ce Zhang, Peter M Atkinson, Xiaoheng Tan, Xin Jian, Xichuan Zhou, Yongming Li


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TextNAS: A Neural Architecture Search Space tailored for Text Representation

Dec 23, 2019
Yujing Wang, Yaming Yang, Yiren Chen, Jing Bai, Ce Zhang, Guinan Su, Xiaoyu Kou, Yunhai Tong, Mao Yang, Lidong Zhou


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Data Science through the looking glass and what we found there

Dec 19, 2019
Fotis Psallidas, Yiwen Zhu, Bojan Karlas, Matteo Interlandi, Avrilia Floratou, Konstantinos Karanasos, Wentao Wu, Ce Zhang, Subru Krishnan, Carlo Curino, Markus Weimer


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Support Vector Machine Classifier via $L_{0/1}$ Soft-Margin Loss

Dec 16, 2019
Huajun Wang, Yuanhai Shao, Shenglong Zhou, Ce Zhang, Naihua Xiu


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ZuCo 2.0: A Dataset of Physiological Recordings During Natural Reading and Annotation

Dec 02, 2019
Nora Hollenstein, Marius Troendle, Ce Zhang, Nicolas Langer


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An Empirical and Comparative Analysis of Data Valuation with Scalable Algorithms

Nov 17, 2019
Ruoxi Jia, Xuehui Sun, Jiacen Xu, Ce Zhang, Bo Li, Dawn Song


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DocParser: Hierarchical Structure Parsing of Document Renderings

Nov 05, 2019
Johannes Rausch, Octavio Martinez, Fabian Bissig, Ce Zhang, Stefan Feuerriegel


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CogniVal: A Framework for Cognitive Word Embedding Evaluation

Oct 29, 2019
Nora Hollenstein, Antonio de la Torre, Nicolas Langer, Ce Zhang

* accepted at CoNLL 2019 

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An Anatomy of Graph Neural Networks Going Deep via the Lens of Mutual Information: Exponential Decay vs. Full Preservation

Oct 22, 2019
Nezihe Merve Gürel, Hansheng Ren, Yujing Wang, Hui Xue, Yaming Yang, Ce Zhang

* 19 pages, 6 figures, 6 tables 

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Lossy Image Compression with Recurrent Neural Networks: from Human Perceived Visual Quality to Classification Accuracy

Oct 08, 2019
Maurice Weber, Cedric Renggli, Helmut Grabner, Ce Zhang


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Efficient Task-Specific Data Valuation for Nearest Neighbor Algorithms

Sep 11, 2019
Ruoxi Jia, David Dao, Boxin Wang, Frances Ann Hubis, Nezihe Merve Gurel, Bo Li, Ce Zhang, Costas J. Spanos, Dawn Song

* PVLDB, 12(11): 1610-1623, 2019 

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$\texttt{DeepSqueeze}$: Decentralization Meets Error-Compensated Compression

Aug 03, 2019
Hanlin Tang, Xiangru Lian, Shuang Qiu, Lei Yuan, Ce Zhang, Tong Zhang, Ji Liu


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$\texttt{DeepSqueeze}$: Parallel Stochastic Gradient Descent with Double-Pass Error-Compensated Compression

Jul 17, 2019
Hanlin Tang, Xiangru Lian, Shuang Qiu, Lei Yuan, Ce Zhang, Tong Zhang, Ji Liu


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Quantitative Overfitting Management for Human-in-the-loop ML Application Development with ease.ml/meter

Jun 06, 2019
Frances Ann Hubis, Wentao Wu, Ce Zhang


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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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