Daniel Haimovich

According to our database, Daniel Haimovich authored at least 12 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Unbiased Prevalence Estimation with Multicalibrated LLMs.

Fridolin Linder, Thomas J. Leeper, Daniel Haimovich, Niek Tax, Lorenzo Perini, Milan Vojnovic

CoRR, April, 2026

On the Convergence of Multicalibration Gradient Boosting.

Daniel Haimovich, Fridolin Linder, Lorenzo Perini, Niek Tax, Milan Vojnovic

CoRR, February, 2026

Billion-Scale Graph Foundation Models.

Maya Bechler-Speicher, Yoel Gottlieb, Andrey Isakov, David Abensur, Ami Tavory, Daniel Haimovich, Ido Guy, Udi Weinsberg

CoRR, February, 2026

MCGrad: Multicalibration at Web Scale.

Niek Tax, Lorenzo Perini, Fridolin Linder, Daniel Haimovich, Dima Karamshuk, Nastaran Okati, Milan Vojnovic, Pavlos Athanasios Apostolopoulos

Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1, 2026

2025

Multicalibration yields better matchings.

Riccardo Colini-Baldeschi, Simone Di Gregorio, Simone Fioravanti, Federico Fusco, Ido Guy, Daniel Haimovich, Stefano Leonardi, Fridolin Linder, Lorenzo Perini, Matteo Russo, Niek Tax

CoRR, November, 2025

Measuring multi-calibration.

Ido Guy, Daniel Haimovich, Fridolin Linder, Nastaran Okati, Lorenzo Perini, Niek Tax, Mark Tygert

CoRR, June, 2025

2024

On the Convergence of Loss and Uncertainty-based Active Learning Algorithms.

Daniel Haimovich, Dima Karamshuk, Fridolin Linder, Niek Tax, Milan Vojnovic

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Online Learning with Sublinear Best-Action Queries.

Matteo Russo, Andrea Celli, Riccardo Colini-Baldeschi, Federico Fusco, Daniel Haimovich, Dima Karamshuk, Stefano Leonardi, Niek Tax

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

2022

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, Christopher Palow, Sung Park, Varun S. Rajagopal, Kevin Schaeffer, Parikshit Shah, Deeksha Sinha, Nicolás Stier Moses, Peng Xu

CoRR, 2022

2021

Popularity Prediction for Social Media over Arbitrary Time Horizons.

Daniel Haimovich, Dmytro Karamshuk, Thomas J. Leeper, Evgeniy Riabenko, Milan Vojnovic

Proc. VLDB Endow., 2021

2020

Weights and Methodology Brief for the COVID-19 Symptom Survey by University of Maryland and Carnegie Mellon University, in Partnership with Facebook.

Neta Barkay, Curtiss Cobb, Roee Eilat, Tal Galili, Daniel Haimovich, Sarah LaRocca, Katherine Morris, Tal Sarig

CoRR, 2020

Scalable Prediction of Information Cascades over Arbitrary Time Horizons.

Daniel Haimovich, Dima Karamshuk, Thomas J. Leeper, Evgeniy Riabenko, Milan Vojnovic

CoRR, 2020