no code implementations • 19 Jan 2022 • Joshua T. Vogelstein, Timothy Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal Burns, Kwame Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena Savonenko, Ian Phillips, Michael I. Miller, Rene Vidal, Jeremias Sulam, Adam Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish Thakor, Justus M Kebschull, Marilyn Albert, Jinchong Xu, Marshall Hussain Shuler, Brian Caffo, Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan, Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael Platt, Lyle Ungar, Leila Wehbe, Adam Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang
We call this 'retrospective learning'.
2 code implementations • ACL 2021 • Yanjun Gao, Ting-Hao, Huang, Rebecca J. Passonneau
On DeSSE, which has a more even balance of complex sentence types, our model achieves higher accuracy on the number of atomic sentences than an encoder-decoder baseline.
no code implementations • 28 Apr 2021 • Rajeev Rikhye, Quan Wang, Qiao Liang, Yanzhang He, Ding Zhao, Yiteng, Huang, Arun Narayanan, Ian McGraw
In this paper, we introduce a streaming keyphrase detection system that can be easily customized to accurately detect any phrase composed of words from a large vocabulary.
no code implementations • 25 Jan 2021 • Man Luo, Qinghua Guo, Ming Jin, Yonina C. Eldar, Defeng, Huang, Xiangming Meng
Sparse Bayesian learning (SBL) can be implemented with low complexity based on the approximate message passing (AMP) algorithm.
no code implementations • 24 Nov 2020 • Jihyeon Lee, Joseph Z. Xu, Kihyuk Sohn, Wenhan Lu, David Berthelot, Izzeddin Gur, Pranav Khaitan, Ke-Wei, Huang, Kyriacos Koupparis, Bernhard Kowatsch
To respond to disasters such as earthquakes, wildfires, and armed conflicts, humanitarian organizations require accurate and timely data in the form of damage assessments, which indicate what buildings and population centers have been most affected.
no code implementations • 16 Jun 2020 • Xiang Gao, Jennie Si, Yue Wen, Minhan Li, He, Huang
We are motivated by the real challenges presented in a human-robot system to develop new designs that are efficient at data level and with performance guarantees such as stability and optimality at systems level.
no code implementations • LREC 2018 • Sheng-Yeh Chen, Chao-Chun Hsu, Chuan-Chun Kuo, Ting-Hao, Huang, Lun-Wei Ku
A total of 29, 245 utterances from 2, 000 dialogues are labeled in EmotionLines.
no code implementations • 9 Feb 2017 • Chieh-Yang Huang, Ting-Hao, Huang, Lun-Wei Ku
Instant messaging is one of the major channels of computer mediated communication.
1 code implementation • NAACL 2016 • Ting-Hao, Huang, Francis Ferraro, Nasrin Mostafazadeh, Ishan Misra, Aishwarya Agrawal, Jacob Devlin, Ross Girshick, Xiaodong He, Pushmeet Kohli, Dhruv Batra, C. Lawrence Zitnick, Devi Parikh, Lucy Vanderwende, Michel Galley, Margaret Mitchell
We introduce the first dataset for sequential vision-to-language, and explore how this data may be used for the task of visual storytelling.
no code implementations • 4 Jan 2016 • Xiangming Meng, Sheng Wu, Linling Kuang, Defeng, Huang, Jianhua Lu
We consider the problem of recovering clustered sparse signals with no prior knowledge of the sparsity pattern.
no code implementations • EMNLP 2015 • Francis Ferraro, Nasrin Mostafazadeh, Ting-Hao, Huang, Lucy Vanderwende, Jacob Devlin, Michel Galley, Margaret Mitchell
Integrating vision and language has long been a dream in work on artificial intelligence (AI).