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2020 – today
- 2020
[j2]Grace Bang, Guy Barash, Ryan Beal, Jacques Calì, Mauricio Castillo-Effen, Xin Cynthia Chen, Niyati Chhaya, Rachel Cummings, Rohan Dhoopar, Sebastijan Dumancic, Huáscar Espinoza, Eitan Farchi, Ferdinando Fioretto, Raquel Fuentetaja
, Christopher William Geib, Odd Erik Gundersen, José Hernández-Orallo, Xiaowei Huang, Kokil Jaidka, Sarah Keren, Seokhwan Kim, Michel Galley, Xiaomo Liu, Tyler Lu, Zhiqiang Ma, Richard Mallah, John A. McDermid, Martin Michalowski, Reuth Mirsky, Seán Ó hÉigeartaigh, Deepak Ramachandran, Javier Segovia-Aguas, Onn Shehory, Arash Shaban-Nejad, Vered Shwartz, Siddharth Srivastava, Kartik Talamadupula, Jian Tang, Pascal Van Hentenryck, Dell Zhang, Jian Zhang:
The Association for the Advancement of Artificial Intelligence 2020 Workshop Program. AI Mag. 41(4): 100-114 (2020)- [j1]Natraj Raman, Grace Bang, Armineh Nourbakhsh:
Mapping ESG Trends by Distant Supervision of Neural Language Models. Mach. Learn. Knowl. Extr. 2(4): 453-468 (2020) - [c4]Chong Wang, Lisa Kim, Grace Bang, Himani Singh, Russell Kociuba, Steven Pomerville, Xiaomo Liu:
Discovery News: A Generic Framework for Financial News Recommendation. AAAI 2020: 13390-13395 - [c3]Antony Papadimitriou, Urjitkumar Patel, Lisa Kim, Grace Bang, Azadeh Nematzadeh, Xiaomo Liu:
A multi-faceted approach to large scale financial forecasting. ICAIF 2020: 5:1-5:8 - [c2]Zhiqiang Ma, Chong Wang, Grace Bang, Xiaomo Liu:
Utilization of deep learning to mine insights from earning calls for stock price movement predictions. ICAIF 2020: 38:1-38:8 - [i3]Zhiqiang Ma, Grace Bang, Chong Wang, Xiaomo Liu:
Towards Earnings Call and Stock Price Movement. CoRR abs/2009.01317 (2020)
2010 – 2019
- 2019
- [c1]Natraj Raman, Grace Bang, Azadeh Nematzadeh:
MultiGraph Attention Network for analyzing Company Relations. ICCPR 2019: 426-433 - [i2]Armineh Nourbakhsh, Grace Bang:
A framework for anomaly detection using language modeling, and its applications to finance. CoRR abs/1908.09156 (2019) - [i1]Azadeh Nematzadeh, Grace Bang, Xiaomo Liu, Zhiqiang Ma:
Empirical Study on Detecting Controversy in Social Media. CoRR abs/1909.01093 (2019)
Coauthor Index
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