1 code implementation • 17 Dec 2022 • Kevin Kuo, Pratiksha Thaker, Mikhail Khodak, John Nguyen, Daniel Jiang, Ameet Talwalkar, Virginia Smith
In this work, we perform the first systematic study on the effect of noisy evaluation in federated hyperparameter tuning.
no code implementations • 13 Oct 2020 • Kevin Kuo, Anthony Ostuni, Elizabeth Horishny, Michael J. Curry, Samuel Dooley, Ping-Yeh Chiang, Tom Goldstein, John P. Dickerson
Inspired by these advances, in this paper, we extend techniques for approximating auctions using deep learning to address concerns of fairness while maintaining high revenue and strong incentive guarantees.
no code implementations • WS 2020 • Kevin Kuo, Marine Carpuat
However, the Bi-LSTM models lag behind the best performing systems in the shared task.
no code implementations • 31 Mar 2020 • Pin-Chu Yang, Mohammed Al-Sada, Chang-Chieh Chiu, Kevin Kuo, Tito Pradhono Tomo, Kanata Suzuki, Nelson Yalta, Kuo-Hao Shu, Tetsuya OGATA
Although numerous robots have been developed, less have focused on otaku-culture or on embodying the anime character figurine.
Action Generation Cultural Vocal Bursts Intensity Prediction +1
3 code implementations • 24 Mar 2020 • Kevin Kuo, Daniel Lupton
Machine learning methods have garnered increasing interest among actuaries in recent years.
1 code implementation • 5 Mar 2020 • Kevin Kuo
We introduce an individual claims forecasting framework utilizing Bayesian mixture density networks that can be used for claims analytics tasks such as case reserving and triaging.
3 code implementations • 5 Dec 2019 • Kevin Kuo
One of the impediments in advancing actuarial research and developing open source assets for insurance analytics is the lack of realistic publicly available datasets.
3 code implementations • 24 Apr 2018 • Kevin Kuo
We propose a novel approach for loss reserving based on deep neural networks.