Fridolin Linder

Researcher, Meta

Joined

February 2024

Names

Fridolin Linder (Preferred)

Emails

****@meta.com (Confirmed)

****@gmail.com

Personal Links

Google Scholar

DBLP

ORCID

Career & Education History

Researcher

Meta (meta.com)

2022 – Present

Researcher

Siemens Corporate Research (siemens.com)

2019 – 2022

Postdoc

New York University (nyu.edu)

2018 – 2019

Advisors, Relations & Conflicts

PhD Advisor

Bruce Desmarais

2012 – 2018

Expertise

computational social science

Present

multicalibration

Present

Publications

MCGrad: Multicalibration at Web Scale
Lorenzo Perini, Niek Tax, Daniel Haimovich, Fridolin Linder, Milan Vojnovic, Dima Karamshuk, Nastaran Okati, Pavlos Athanasios Apostolopoulos
- ACM SIGKDD Conference on Knowledge Discovery and Data Mining
- Readers: Everyone
Measuring multi-calibration
Ido Guy, Daniel Haimovich, Fridolin Linder, Nastaran Okati, Lorenzo Perini, Niek Tax, Mark Tygert
- CoRR 2025
- Readers: Everyone
On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
Daniel Haimovich, Dima Karamshuk, Fridolin Linder, Niek Tax, Milan Vojnovic
- NeurIPS 2024 poster
- Readers: Everyone
On the Convergence of Loss and Uncertainty-based Active Learning Algorithms
Daniel Haimovich, Dima Karamshuk, Fridolin Linder, Niek Tax, Milan Vojnovic
- NeurIPS 2024
- Readers: Everyone
On the convergence of loss and uncertainty-based active learning algorithms
Daniel Haimovich, Dima Karamshuk, Fridolin Linder, Niek Tax, Milan Vojnovic
- CoRR 2023
- Readers: Everyone
edarf: Exploratory Data Analysis using Random Forests
Zachary M. Jones, Fridolin Linder
- J. Open Source Softw. 2016
- Readers: Everyone
Privacy Protection for Natural Language: Neural Generative Models for Synthetic Text Data
Alexander G. Ororbia II, Fridolin Linder, Joshua Snoke
- CoRR 2016
- Readers: Everyone

Fridolin Linder

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

MCGrad: Multicalibration at Web Scale

Measuring multi-calibration

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

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

On the convergence of loss and uncertainty-based active learning algorithms

edarf: Exploratory Data Analysis using Random Forests

Privacy Protection for Natural Language: Neural Generative Models for Synthetic Text Data

Co-Authors