Behrooz Tahmasebi
Hello! I'm a Ph.D. student in EECS at MIT and a student member of CSAIL. My advisor is Prof. Stefanie Jegelka. Previously, I studied at Sharif University of Technology.
I'm interested in learning with graphs/manifolds/invariances, deep learning (geometry, optimization), and Large Language Models (LLMs) foundations.
CV: click here
Email: bzt at mit dot edu
Manuscripts under Review:
Note: authors denoted with * contributed equally.
• A Robust Kernel Statistical Test of Invariance: Detecting Subtle Asymmetries [preprint]
Ashkan Soleymani*, Behrooz Tahmasebi*, Stefanie Jegelka, Patrick Jaillet
preprint (submitted), 2024
• Learning with Exact Invariances in Polynomial Time [preprint]
Ashkan Soleymani*, Behrooz Tahmasebi*, Stefanie Jegelka, Patrick Jaillet
preprint (submitted), 2024
• Generalization Bounds for Canonicalization: A Comparative Study with Group Averaging [preprint]
Behrooz Tahmasebi, Stefanie Jegelka
preprint (submitted), 2024
• Regularity in Canonicalized Models: A Theoretical Perspective [preprint]
Behrooz Tahmasebi, Stefanie Jegelka
preprint (submitted), 2024
Published Papers:
• Coded Computing for Resilient Distributed Computing: A Learning-Theoretic Framework [arXiv]
Parsa Moradi, Behrooz Tahmasebi, Mohammad Ali Maddah-Ali
NeurIPS 2024
• A Universal Class of Sharpness-Aware Minimization Algorithms [arXiv]
Behrooz Tahmasebi, Ashkan Soleymani, Dara Bahri, Stefanie Jegelka, Patrick Jaillet
ICML 2024
Best Paper Award, workshop on High-dimensional Learning Dynamics
(HiLD) at ICML 2024
• Sample Complexity Bounds for Estimating
Probability Divergences under Invariances [arXiv]
Behrooz Tahmasebi, Stefanie Jegelka
ICML 2024
• The Exact Sample Complexity Gain from
Invariances for Kernel Regression [arXiv]
Behrooz Tahmasebi, Stefanie Jegelka
NeurIPS 2023, Spotlight (top 3.6% of submissions)
• The Power of Recursion in
Graph Neural Networks for Counting Substructures [Conference Link]
Behrooz Tahmasebi, Derek Lim, Stefanie Jegelka
AISTATS 2023, Oral (top 1.9% of submissions)
• The Capacity of Associated Subsequence Retrieval [Journal Link]
Behrooz Tahmasebi, Mohammad Ali Maddah-Ali, and Seyed Abolfazl Motahari
IEEE Transactions on Information Theory, 2021
• Private Function Computation
Behrooz Tahmasebi, Mohammad Ali Maddah-Ali
IEEE International Symposium on Information Theory (ISIT), 2020
• Private Sequential Function Computation [arXiv]
Behrooz Tahmasebi, Mohammad Ali Maddah-Ali
IEEE International Symposium on Information Theory (ISIT), 2019
• Information Theory of Mixed Population Genome-Wide Association Studies
Behrooz Tahmasebi, Mohammad Ali Maddah-Ali, Seyed Abolfazl Motahari
IEEE Information Theory Workshop (ITW), 2018
• Genome-Wide Association Studies: Information Theoretic Limits of Reliable Learning
Behrooz Tahmasebi, Mohammad Ali Maddah-Ali, Seyed Abolfazl Motahari
IEEE International Symposium on Information Theory (ISIT), 2018
• Optimum Transmission Delay for Function Computation in NFV-Based Networks: The Role of Network Coding and Redundant Computing
Behrooz Tahmasebi, Mohammad Ali Maddah-Ali, Saeedeh Parsaeefard, Babak Khalaj,
IEEE Journal on Selected Areas in Communications (JSAC), 2018
• On the Identifiability of Finite Mixtures of Finite Product Measures
Behrooz Tahmasebi, Seyed Abolfazl Motahari, Mohammad Ali Maddah-Ali
Manuscript, 2018