Tahmasebi, Behrooz

14 publications

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

ICLR 2025 Generalization Bounds for Canonicalization: A Comparative Study with Group Averaging Behrooz Tahmasebi, Stefanie Jegelka

NeurIPS 2025 Geometric Algorithms for Neural Combinatorial Optimization with Constraints Nikolaos Karalias, Akbar Rafiey, Yifei Xu, Zhishang Luo, Behrooz Tahmasebi, Connie Jiang, Stefanie Jegelka

ICML 2025 Learning with Exact Invariances in Polynomial Time Ashkan Soleymani, Behrooz Tahmasebi, Stefanie Jegelka, Patrick Jaillet

AISTATS 2025 Regularity in Canonicalized Models: A Theoretical Perspective Behrooz Tahmasebi, Stefanie Jegelka

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

ICMLW 2024 A Universal Class of Sharpness-Aware Minimization Algorithms Behrooz Tahmasebi, Ashkan Soleymani, Dara Bahri, Stefanie Jegelka, Patrick Jaillet

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

ICML 2024 Sample Complexity Bounds for Estimating Probability Divergences Under Invariances Behrooz Tahmasebi, Stefanie Jegelka

NeurIPSW 2023 On Scale-Invariant Sharpness Measures Behrooz Tahmasebi, Ashkan Soleymani, Stefanie Jegelka, Patrick Jaillet

ICMLW 2023 Sample Complexity Bounds for Estimating the Wasserstein Distance Under Invariances Behrooz Tahmasebi, Stefanie Jegelka

NeurIPS 2023 The Exact Sample Complexity Gain from Invariances for Kernel Regression Behrooz Tahmasebi, Stefanie Jegelka

ICMLW 2023 The Exact Sample Complexity Gain from Invariances for Kernel Regression Behrooz Tahmasebi, Stefanie Jegelka

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