I am a Ph.D. student in Electrical and Computer Engineering at UC Santa Barbara, where I am fortunate to be advised by Prof. Christos Thrampoulidis. My research interests are broadly in statistical learning theory, optimization and high-dimensional statistics.

Email :  myfirstname at ucsb.edu

 Recent News

• (Mar 24) Our work on the dynamics of multi-head attention is accepted at TMLR. Congrats to co-authors!

• (Feb 24) Happy to have presented our work at ITA.

• (Feb 24) I recieved the dissertation fellowship from the ECE department at UCSB.

• (Jan 24) "Generalization and Stability of Neural Networks with Minimal Width" is accepted (pending minor revision) in JMLR!

• (Nov 23) Happy to be a Top Reviewer of NeurIPS 2023.

• (Oct 23) New preprint on the attention mechanism.  

• (Jun 23) Our paper on Asymptotic Behavior of Adversarial Training is accepted at IEEE Transactions on Neural Networks and Learning Systems.

• (Jun 23) Two papers are accepted at ICML workshop on High-dimensional Learning Dynamics.

• (Mar 23) Excited about our recent paper achieving minimum width for optimal generalization in interpolating neural networks.

• (Jan 23) Our paper "On Generalization of Decentralized Learning with Separable Data" is accepted at AISTATS 2023.

• (Nov 22) Our paper on "Fast Convergence in Learning Two-layer Neural Networks with Separable Data" is accepted at AAAI 2023.

• (Nov 22) I will present my paper on "decentralized learning with separable data" in the NeurIPS OPT22 Workshop on Optimization for Machine Learning.

Research

link to my google scholar profile.

• On the Optimization and Generalization of Multi-head Attention [arXiv]

P. Deora*,  R. Ghaderi*,  H. Taheri*,  C. Thrampoulidis

Preprint 

• Generalization and Stability of Interpolating Neural Networks with Minimal Width [arXiv]

H. Taheri, C. Thrampoulidis

     Accepted to appear (pending minor revision) at the Journal of Machine Learning Research (JMLR)

• Asymptotic Behavior of Adversarial Training in Binary Linear Classification [arXiv]

H. Taheri, R. Pedarsani, C. Thrampoulidis

IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS).

Short version appeared in ISIT, 2022.

• On Generalization of Decentralized Learning with Separable Data [arXiv]

H. Taheri, C. Thrampoulidis

International Conference on Artificial Intelligence and Statistics (AISTATS), 2023

• Fast Convergence in Learning Two-layer Neural Networks with Separable Data [arXiv]

H. Taheri, C. Thrampoulidis

AAAI Conference on Artificial Intelligence (AAAI), 2023

• Fundamental limits of ridge-regularized empirical risk minimization in high dimensions [arXiv]

H. Taheri, R. Pedarsani, C. Thrampoulidis

International Conference on Artificial Intelligence and Statistics (AISTATS), 2021. 

• Quantized Decentralized Stochastic Learning over Directed Graphs [arXiv]

 H. Taheri, A. Mokhtari, H. Hassani, R. Pedarsani

International Conference on Machine Learning (ICML), 2020.

•  Sharp Asymptotics and Optimal Performance for Inference in Binary Models [arXiv]

H. Taheri, R. Pedarsani, C. Thrampoulidis

International Conference on Artificial Intelligence and Statistics (AISTATS), 2020. 

A longer version of this paper merged with a paper from ISIT appeared in the journal Entropy.

• Sharp guarantees for solving random equations with one-bit information [pdf]

H. Taheri, R. Pedarsani, C. Thrampoulidis

Allerton Conference on Communication, Control, and Computing, 2019.

• Robust and communication-efficient collaborative learning [arXiv]

A. Reisizadeh, H. Taheri, A. Mokhtari, H. Hassani, R. Pedarsani

Neural Information Processing Systems (NeurIPS), 2019.

Education

• Electrical and Computer Engineering,  Ph. D. , (2018-present)

   UC Santa Barbara, CA, USA

• Electrical Engineering and Mathematics, B. Sc. , (2013-2018)

          Sharif University of Technology, Tehran, Iran

Teaching Assistant

• Machine Learning, at Sharif University, EE department

• Abstract Algebra, at Sharif University, Math department

• Engineering Mathematics, at Sharif University, EE department

• Principles of Electrical Engineering, at Sharif University, EE department

• Signal Analysis, at UC Santa Barbara, ECE department