On the Identifiability of Parameters in the Population Stratification Problem: A Worst-Case Analysis. - Behrooz Tahmasebi; Abolfazl S. Motahari; Mohammad Ali Maddah-Ali (ISIT, 2018)

Genome-Wide Association Studies: Information Theoretic Limits of Reliable Learning. - Behrooz Tahmasebi; Mohammad Ali Maddah-Ali; Abolfazl S. Motahari (ISIT, 2018)

Information Theory of Mixed Population Genome-Wide Association Studies. - Behrooz Tahmasebi; Mohammad Ali Maddah-Ali; Seyed Abolfazl Motahari (ITW, 2018)

Information theoretic limits of learning of the causal features in a linear model. - Behrooz Tahmasebi; Mohammad Ali Maddah-Ali; Seyed Abolfazl Motahari (IWCIT, 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 Hossein Khalaj (IEEE J. Sel. Areas Commun., 2018)

Private Sequential Function Computation. - Behrooz Tahmasebi; Mohammad Ali Maddah-Ali (ISIT, 2019)

Private Function Computation. - Behrooz Tahmasebi; Mohammad Ali Maddah-Ali (ISIT, 2020)

Counting Substructures with Higher-Order Graph Neural Networks: Possibility and Impossibility Results. - Behrooz Tahmasebi; Stefanie Jegelka (CoRR, 2020)

The Capacity of Associated Subsequence Retrieval. - Behrooz Tahmasebi; Mohammad Ali Maddah-Ali; Seyed Abolfazl Motahari (IEEE Trans. Inf. Theory, 2021)

The Power of Recursion in Graph Neural Networks for Counting Substructures. - Behrooz Tahmasebi; Derek Lim; Stefanie Jegelka (AISTATS, 2023)

The Exact Sample Complexity Gain from Invariances for Kernel Regression. - Behrooz Tahmasebi; Stefanie Jegelka (NeurIPS, 2023)

The Exact Sample Complexity Gain from Invariances for Kernel Regression on Manifolds. - Behrooz Tahmasebi; Stefanie Jegelka (CoRR, 2023)

Sample Complexity Bounds for Estimating Probability Divergences under Invariances. - Behrooz Tahmasebi; Stefanie Jegelka (ICML, 2024)

A Universal Class of Sharpness-Aware Minimization Algorithms. - Behrooz Tahmasebi; Ashkan Soleymani; Dara Bahri; Stefanie Jegelka; Patrick Jaillet (ICML, 2024)

Coded Computing for Resilient Distributed Computing: A Learning-Theoretic Framework. - Parsa Moradi; Behrooz Tahmasebi; Mohammad Ali Maddah-Ali (NeurIPS, 2024)

Coded Computing: A Learning-Theoretic Framework. - Parsa Moradi; Behrooz Tahmasebi; Mohammad Ali Maddah-Ali (CoRR, 2024)

A Robust Kernel Statistical Test of Invariance: Detecting Subtle Asymmetries. - Ashkan Soleymani; Behrooz Tahmasebi; Stefanie Jegelka; Patrick Jaillet (AISTATS, 2025)

Regularity in Canonicalized Models: A Theoretical Perspective. - Behrooz Tahmasebi; Stefanie Jegelka (AISTATS, 2025)

Generalization Bounds for Canonicalization: A Comparative Study with Group Averaging. - Behrooz Tahmasebi; Stefanie Jegelka (ICLR, 2025)

Learning with Exact Invariances in Polynomial Time. - Ashkan Soleymani; Behrooz Tahmasebi; Stefanie Jegelka; Patrick Jaillet (CoRR, 2025)