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Ying Zhang

Similarity Reasoning and Filtration for Image-Text Matching


Jan 05, 2021
Haiwen Diao, Ying Zhang, Lin Ma, Huchuan Lu

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* 14 pages, 8 figures, Accepted by AAAI2021 
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Infusing Multi-Source Knowledge with Heterogeneous Graph Neural Network for Emotional Conversation Generation


Dec 09, 2020
Yunlong Liang, Fandong Meng, Ying Zhang, Jinan Xu, Yufeng Chen, Jie Zhou

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* Accepted at AAAI 2021, Code:https://github.com/XL2248/HGNN 
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SF-GRASS: Solver-Free Graph Spectral Sparsification


Aug 17, 2020
Ying Zhang, Zhiqiang Zhao, Zhuo Feng

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Consensus-Aware Visual-Semantic Embedding for Image-Text Matching


Jul 17, 2020
Haoran Wang, Ying Zhang, Zhong Ji, Yanwei Pang, Lin Ma

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* Accepted by ECCV 2020, Code is publicly available at: https://github.com/BruceW91/CVSE 
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GoGNN: Graph of Graphs Neural Network for Predicting Structured Entity Interactions


May 12, 2020
Hanchen Wang, Defu Lian, Ying Zhang, Lu Qin, Xuemin Lin

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* Accepted by IJCAI 2020 
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Binarized Graph Neural Network


Apr 19, 2020
Hanchen Wang, Defu Lian, Ying Zhang, Lu Qin, Xiangjian He, Yiguang Lin, Xuemin Lin

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Machine learning on DNA-encoded libraries: A new paradigm for hit-finding


Jan 31, 2020
Kevin McCloskey, Eric A. Sigel, Steven Kearnes, Ling Xue, Xia Tian, Dennis Moccia, Diana Gikunju, Sana Bazzaz, Betty Chan, Matthew A. Clark, John W. Cuozzo, Marie-Aude Guié, John P. Guilinger, Christelle Huguet, Christopher D. Hupp, Anthony D. Keefe, Christopher J. Mulhern, Ying Zhang, Patrick Riley

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Nonasymptotic estimates for Stochastic Gradient Langevin Dynamics under local conditions in nonconvex optimization


Oct 17, 2019
Ying Zhang, Ă–mer Deniz Akyildiz, Theodoros Damoulas, Sotirios Sabanis

* 19 pages 
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Task-Oriented Conversation Generation Using Heterogeneous Memory Networks


Sep 25, 2019
Zehao Lin, Xinjing Huang, Feng Ji, Haiqing Chen, Ying Zhang

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* Accepted as a long paper at EMNLP-IJCNLP 2019 
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Improving Captioning for Low-Resource Languages by Cycle Consistency


Aug 21, 2019
Yike Wu, Shiwan Zhao, Jia Chen, Ying Zhang, Xiaojie Yuan, Zhong Su

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* Published in ICME 2019 
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On stochastic gradient Langevin dynamics with dependent data streams: the fully non-convex case


May 30, 2019
Ngoc Huy Chau, Éric Moulines, Miklos Rásonyi, Sotirios Sabanis, Ying Zhang


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Voiceprint recognition of Parkinson patients based on deep learning


Dec 17, 2018
Zhijing Xu, Juan Wang, Ying Zhang, Xiangjian He

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* 10 pages,4 figures 
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Fashion-Gen: The Generative Fashion Dataset and Challenge


Jul 30, 2018
Negar Rostamzadeh, Seyedarian Hosseini, Thomas Boquet, Wojciech Stokowiec, Ying Zhang, Christian Jauvin, Chris Pal

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Quaternion Convolutional Neural Networks for End-to-End Automatic Speech Recognition


Jun 20, 2018
Titouan Parcollet, Ying Zhang, Mohamed Morchid, Chiheb Trabelsi, Georges Linarès, Renato De Mori, Yoshua Bengio

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* Accepted at INTERSPEECH 2018 
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Medical Concept Embedding with Time-Aware Attention


Jun 06, 2018
Xiangrui Cai, Jinyang Gao, Kee Yuan Ngiam, Beng Chin Ooi, Ying Zhang, Xiaojie Yuan

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* 7 pages. IJCAI-ECAI-2018 
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Online Product Quantization


Mar 24, 2018
Donna Xu, Ivor W. Tsang, Ying Zhang

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* To appear in IEEE Transactions on Knowledge and Data Engineering (DOI: 10.1109/TKDE.2018.2817526) 
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IDEL: In-Database Entity Linking with Neural Embeddings


Mar 13, 2018
Torsten Kilias, Alexander Löser, Felix A. Gers, Richard Koopmanschap, Ying Zhang, Martin Kersten

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* This manuscript is a preprint for a paper submitted to VLDB2018 
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Deep Complex Networks


Feb 25, 2018
Chiheb Trabelsi, Olexa Bilaniuk, Ying Zhang, Dmitriy Serdyuk, Sandeep Subramanian, JoĂŁo Felipe Santos, Soroush Mehri, Negar Rostamzadeh, Yoshua Bengio, Christopher J Pal

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FashionBrain Project: A Vision for Understanding Europe's Fashion Data Universe


Oct 26, 2017
Alessandro Checco, Gianluca Demartini, Alexander Loeser, Ines Arous, Mourad Khayati, Matthias Dantone, Richard Koopmanschap, Svetlin Stalinov, Martin Kersten, Ying Zhang

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Deep Mutual Learning


Jun 01, 2017
Ying Zhang, Tao Xiang, Timothy M. Hospedales, Huchuan Lu

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* 10 pages, 4 figures 
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Fully Distributed and Asynchronized Stochastic Gradient Descent for Networked Systems


Apr 13, 2017
Ying Zhang

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Recurrent Neural Networks With Limited Numerical Precision


Feb 26, 2017
Joachim Ott, Zhouhan Lin, Ying Zhang, Shih-Chii Liu, Yoshua Bengio

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* NIPS 2016 EMDNN Workshop paper, condensed version of arXiv:1608.06902 
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Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks


Jan 10, 2017
Ying Zhang, Mohammad Pezeshki, Philemon Brakel, Saizheng Zhang, Cesar Laurent Yoshua Bengio, Aaron Courville

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End-to-End Data Visualization by Metric Learning and Coordinate Transformation


Dec 27, 2016
Lilei Zheng, Ying Zhang, Stefan Duffner, Khalid Idrissi, Christophe Garcia, Atilla Baskurt

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* 17 pages, 9 figures 
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On Multiplicative Integration with Recurrent Neural Networks


Nov 12, 2016
Yuhuai Wu, Saizheng Zhang, Ying Zhang, Yoshua Bengio, Ruslan Salakhutdinov

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* 10 pages, 2 figures; To appear in NIPS2016 
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Professor Forcing: A New Algorithm for Training Recurrent Networks


Oct 27, 2016
Alex Lamb, Anirudh Goyal, Ying Zhang, Saizheng Zhang, Aaron Courville, Yoshua Bengio

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* NIPS 2016 Accepted Paper 
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Theano: A Python framework for fast computation of mathematical expressions


May 09, 2016
The Theano Development Team, Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermueller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre-Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Mélanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian Goodfellow, Matt Graham, Caglar Gulcehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrancois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert T. McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang

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* 19 pages, 5 figures 
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Batch Normalized Recurrent Neural Networks


Oct 05, 2015
César Laurent, Gabriel Pereyra, Philémon Brakel, Ying Zhang, Yoshua Bengio

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