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DeepQ Publications

At DeepQ publications, publication is highly encouraged. Writing high-quality technical papers helps one to organize ideas, and hence be more rigorous in both research and engineering.

Publication Spotlights:

  • Toward Personalized Treatment of Chronic Diseases – the CKD Case Study, Chih-Yang Chen, Chun-Nan Chou and I-Wen Wu, MM Health Workshop, 2017.

  • DeepQ Arrhythmia Database: A Large-Scale Dataset for Arrhythmia Detector Evaluation, Meng-Hsi Wu and Edward Chang, MM Health Workshop, 2017.

  • Artificial Intelligence in XPRIZE DeepQ Tricorder, Edward Chang, Meng-Hsi Wu, Kai-Fu Tang, Hao-Cheng Kao and Chun-Nan Chou, MM Health Workshop, 2017.

  • Aristo: An Augmented Reality Platform for Immersion and Interactivity, Zhongyang Zheng, Bo Wang, Yakun Wang, Shuang Yang, Zhongqian Dong Tianyang Yi, Cyrus Choi, Emily J. Chang, Edward Y. Chang, MM, 2017.

  • Distributed Training Large-Scale Deep Architectures, Mina Zou, et al., HTC Technical Report, 2017.

  • Representation Learning on Large and Small Data, J. Chou, et al., A book chapter in Big Data Analytics for Large-Scale Multimedia Search, Wiley & Sons (accepted), 2017.
     

  • CLKN: Cascaded Lucas-Kanade Networks for Image Alignment, Che-Han Chang, Chun-Nan Chou and Edward Y. Chang, Hawaii, CVPR, July 2017.
     

  • Inquire and Diagnose: Neural Symptom Checking Ensemble using Deep Reinforcement Learning, Kevin Tang, HaoCheng Kao, Jason Chou, and Edward Y. Chang, NIPS DeepRL Workshop, 2016.​
     

  • Mining Product Adopter Information from Online Reviews for Improving Product Recommendation, X. Zhao, J. Wang, Y. He, J-R Wen, Edward Chang, and X. Li,TKDD 10(3): 29:1-29:23 (2016).
     

  • Connecting Social Media to E-Commerce: Cold-Start Product Recommendation using Microblogging Information, Wayne Xin Zhao, Sui Li, Yulan He, Edward Chang, Ji-Rong Wen, and Xiaoming Li, IEEE Trans. Knowl. Data Eng. 28(5): 1147-1159 (2016).
     

  • A Probabilistic Lifestyle-Based Trajectory Model for Social Strength Inference from Human Trajectory Data, Wayne Xin Zhao, Ningnan Zhou, Wenhui Zhang, Ji-Rong Wen, Shan Wang, Edward Y. Chang:ACM Trans. Inf. Syst. 35(1): 8:1-8:28 (2016).
     

  • Tweet Timeline Generation with Determinantal Point Processes, Jin-ge Yao, Feifan Fan, Wayne Xin Zhao, Xiaojun Wan, Edward Chang, and Jianguo Xiao, Proceedings of AAAI, January 2016.
     

  • SpeeDO, Parallelizing Stochastic Gradient Descent for Deep Convolutional Neural Network, Zhongyang Zheng, Wenrui Jiang, Gang Wu, Cyrus Choi, and Edward Chang, NIPS Workshop on Learning Systems, December 2015.
     

  • Pan360: INS Assisted 360-Degree Panorama, Lun-Chen Chu, Andre Chen, Yuhsin Lin, Yu-Mei Chen, Scott Liao, and Edward Chang, ACM Multimedia Immersive Experience Workshop, October 2015.
     

  • Pan360: INS Assisted 360-Degree Panorama (demo Description) (best technical demo award), Yuhsin Lin, Yu-Mei Chen, Lun-Chen Chu, Andre Chen, Scott Liao, and Edward Chang, ACM Multimedia, October 2015.
     

  • Gaussian Processes for High-Dimensional Regression: A Method Based on Deep Neural Networks, Wenbing Huang, Deli Zhao, Fuchun Sun, Huaping Liu, and Edward Chang, IJCAI, July 2015.
     

  • Network Representation Learning with Rich Text Information, Cheng Yang, Zhiyuan Liu, Deli Zhao, Maosong Sun, and Edward Chang, IJCAI, July 2015.
     

  • A New Retraction for Accelerating the Riemannian Three-Factor Low-Rank Matrix Completion Algorithm, Zhizhong Li, Deli Zhao, Zhouchen Lin, and Edward Chang, CVPR, June 2015.
     

  • Transfer Representation Learning for Medical Image Analysis, Chuenkai Shie, Chung-Hisang Chuang, Chun-Nan Chou, Meng-Hsi Wu, and Edward Chang, HTC Technical Report, April 2015, IEEE EMBC, August 2015.
     

  • Exact Recoverability of Robust PCA via Outlier Pursuit with Tight Recovery Bounds, Hongyang Zhang, Zhouchen Lin, Chao Zhang, and Edward Chang, pp.3143-49, AAAI, January 2015.
     

  • Zeta Hull Pursuits: Learning Nonconvex Data Hulls, Yuanjun Xiong, Wei Liu, Deli Zhao, and Xiaoou Tang, Neural Information Processing Systems, NIPS, 2014.
     

  • Big Data, Small Footprint: The Design of a Low-Power Classifier for Detecting Transportation Modes, Meng-Chieh Yu, Tong Yu, Shao-Chen Wang, Chih-Jen Lin, and Edward Chang, Very Large Data Bases (VLDB), August 2014.
     

  • Distant Supervision for Relation Extraction with Matrix Completion, Miao Fan, Deli Zhao, Qiang Zhou, Zhiyuan Liu, Thomas Fang Zheng and Edward Chang,Association for Computational Linguistics (ACL), 2014.
     

  • A data-driven study of image feature extraction and fusion, Zhiyu Wang, Peng Cui, Fangtao Li, Edward Y. Chang, Shiqiang Yang, Inf. Sci. 281: 536-558 (2014)
     

  • Context-Aware Computing: Opportunities and Open IssuesEdward Chang, Very Large Data Bases (VLDB), August 2013.

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