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of 7
pro vyhledávání: '"Wen, Ruofeng"'
Amazon Customer Service provides real-time support for millions of customer contacts every year. While bot-resolver helps automate some traffic, we still see high demand for human agents, also called subject matter experts (SMEs). Customers outreach
Externí odkaz:
http://arxiv.org/abs/2209.05278
Autor:
Wen, Ruofeng
We developed a machine learning approach that quantifies multiple aspects of the success or values in Customer Service contacts, at anytime during the interaction. Specifically, the value/reward function regarding to the turn-level behaviors across h
Externí odkaz:
http://arxiv.org/abs/2011.06395
Autor:
Wen, Ruofeng, Torkkola, Kari
We introduce a new category of multivariate conditional generative models and demonstrate its performance and versatility in probabilistic time series forecasting and simulation. Specifically, the output of quantile regression networks is expanded fr
Externí odkaz:
http://arxiv.org/abs/1907.10697
We propose a framework for general probabilistic multi-step time series regression. Specifically, we exploit the expressiveness and temporal nature of Sequence-to-Sequence Neural Networks (e.g. recurrent and convolutional structures), the nonparametr
Externí odkaz:
http://arxiv.org/abs/1711.11053
Autor:
Kulkarni, Shilpa, Koller, Antonius, Mani, Kartik M., Wen, Ruofeng, Alfieri, Alan, Saha, Subhrajit, Wang, Jian, Patel, Purvi, Bandeira, Nuno, Guha, Chandan, Chen, Emily I.
Publikováno v:
In International Journal of Radiation Oncology, Biology, Physics 1 November 2016 96(3):566-577
Akademický článek
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Publikováno v:
Journal of Probability & Statistics; 2012, p1-19, 19p, 2 Diagrams, 3 Charts