Scalable Prediction of Information Cascades over Arbitrary Time Horizons. - Daniel Haimovich; Dima Karamshuk; Thomas J. Leeper; Evgeniy Riabenko; Milan Vojnovic (CoRR, 2020)

CUT: Controllable Unsupervised Text Simplification. - Oleg Kariuk; Dima Karamshuk (CoRR, 2020)

Bandits for Online Calibration: An Application to Content Moderation on Social Media Platforms. - 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; et al. (CoRR, 2022)

Online Learning with Sublinear Best-Action Queries. - Matteo Russo 002; Andrea Celli; Riccardo Colini-Baldeschi; Federico Fusco; Daniel Haimovich; Dima Karamshuk; Stefano Leonardi 001; Niek Tax (NeurIPS, 2024)

On the Convergence of Loss and Uncertainty-based Active Learning Algorithms. - Daniel Haimovich; Dima Karamshuk; Fridolin Linder; Niek Tax; Milan Vojnovic (NeurIPS, 2024)