Mark S. Squillante

Distinguished Research Staff Member, Mathematical Sciences Department, IBM Research

Joined

July 2019

Names

Mark S. Squillante

Emails

****@us.ibm.com (Confirmed)

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Career & Education History

Distinguished Research Staff Member

Mathematical Sciences Department, IBM Research (us.ibm.com)

Present

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Expertise

No areas of expertise listed

Publications

Distributionally Robust Regularization of Sparse Integer Programming Trained Learning Models
Sanjeeb Dash, Soumyadip Ghosh, Joao Goncalves, Mark S. Squillante
- NeurIPS 2025 Workshop MLxOR
- Readers: Everyone
Theoretical Analysis on the Generalization Power of Overfitted Transfer Learning
Peizhong Ju, Sen Lin, Mark S. Squillante, Yingbin Liang, Ness Shroff
- Submitted to ICLR 2024
- Readers: Everyone
Topological data analysis on noisy quantum computers
Ismail Yunus Akhalwaya, Shashanka Ubaru, Kenneth L. Clarkson, Mark S. Squillante, Vishnu Jejjala, Yang-Hui He, Kugendran Naidoo, Vasileios Kalantzis, Lior Horesh
- ICLR 2024 oral
- Readers: Everyone
A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization
Songtao Lu, Siliang Zeng, Xiaodong Cui, Mark S. Squillante, Lior Horesh, Brian Kingsbury, Jia Liu, Mingyi Hong
- Published: 31 Oct 2022, Last Modified: 24 Oct 2022
- NeurIPS 2022 Accept
- Readers: Everyone
Efficient Generalization with Distributionally Robust Learning
Soumyadip Ghosh, Mark S. Squillante, Ebisa D. Wollega
- Published: 09 Nov 2021, Last Modified: 05 May 2023
- NeurIPS 2021 Poster
- Readers: Everyone
PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach
Lily Weng, Pin-Yu Chen, Lam M. Nguyen, Mark S. Squillante, Akhilan Boopathy, Ivan V. Oseledets, Luca Daniel
- 2019 (modified: 11 Nov 2022)
- ICML 2019
- Readers: Everyone
Optimal crawling strategies for web search engines
Joel L. Wolf, Mark S. Squillante, Philip S. Yu, Jay Sethuraman, L. Ozsen
- 2002 (modified: 12 Nov 2022)
- WWW 2002
- Readers: Everyone

Co-Authors

View all 32 co-authors

Mark S. Squillante

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

Distributionally Robust Regularization of Sparse Integer Programming Trained Learning Models

Theoretical Analysis on the Generalization Power of Overfitted Transfer Learning

Topological data analysis on noisy quantum computers

A Stochastic Linearized Augmented Lagrangian Method for Decentralized Bilevel Optimization

Efficient Generalization with Distributionally Robust Learning

PROVEN: Verifying Robustness of Neural Networks with a Probabilistic Approach

Optimal crawling strategies for web search engines

Co-Authors