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2020 – today
- 2024
[i5]Matteo Russo
, Andrea Celli, Riccardo Colini-Baldeschi, Federico Fusco, Daniel Haimovich, Dima Karamshuk, Stefano Leonardi, Niek Tax:
Online Learning with Sublinear Best-Action Queries. CoRR abs/2407.16355 (2024)- 2023
- [i4]Daniel Haimovich, Dima Karamshuk, Fridolin Linder, Niek Tax, Milan Vojnovic:
On the convergence of loss and uncertainty-based active learning algorithms. CoRR abs/2312.13927 (2023) - 2022
- [i3]Vashist Avadhanula, Omar Abdul Baki, Hamsa Bastani, Osbert Bastani, Caner Gocmen, Daniel Haimovich, Darren Hwang, Dima Karamshuk, Thomas J. Leeper, Jiayuan Ma, Gregory Macnamara, Jake Mullett, Christopher Palow, Sung Park, Varun S. Rajagopal, Kevin Schaeffer, Parikshit Shah, Deeksha Sinha, Nicolás Stier Moses, Peng Xu:
Bandits for Online Calibration: An Application to Content Moderation on Social Media Platforms. CoRR abs/2211.06516 (2022) - 2020
- [i2]Daniel Haimovich, Dima Karamshuk, Thomas J. Leeper, Evgeniy Riabenko, Milan Vojnovic:
Scalable Prediction of Information Cascades over Arbitrary Time Horizons. CoRR abs/2009.02092 (2020) - [i1]Oleg Kariuk, Dima Karamshuk:
CUT: Controllable Unsupervised Text Simplification. CoRR abs/2012.01936 (2020)
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