no code implementations • 2 Sep 2021 • Gurmeet Manku, James Lee-Thorp, Bhargav Kanagal, Joshua Ainslie, Jingchen Feng, Zach Pearson, Ebenezer Anjorin, Sudeep Gandhe, Ilya Eckstein, Jim Rosswog, Sumit Sanghai, Michael Pohl, Larry Adams, D. Sivakumar
The dialog understanding system consists of a deep-learned Contextual Language Understanding module, which interprets user utterances, and a primarily rules-based Dialog-State Tracker (DST), which updates the dialog state and formulates search requests intended for the fulfillment engine.
no code implementations • 16 Oct 2020 • Goran Zuzic, Di Wang, Aranyak Mehta, D. Sivakumar
In this paper, we focus on the AdWords problem, which is a classical online budgeted matching problem of both theoretical and practical significance.
no code implementations • 25 Sep 2019 • Goran Zuzic, Di Wang, Aranyak Mehta, D. Sivakumar
To answer this question, we draw insights from classic results in game theory, analysis of algorithms, and online learning to introduce a novel framework.
no code implementations • ICLR 2019 • Weiwei Kong, Christopher Liaw, Aranyak Mehta, D. Sivakumar
This paper introduces a novel framework for learning algorithms to solve online combinatorial optimization problems.