Kayhan Behdin
About me
I received my B.Sc. in Electrical Engineering from Sharif University of Technology, Tehran, Iran, in 2019. I joined MIT as a PhD student in operation research in 2019. I've been working under the supervision of Prof. Rahul Mazumder since then. I was an AI/ML Engineering Intern at LinkedIn Corporation from June 2022 through August 2022, and from May 2023 through August 2023.
Research
My research interests include
Recent Publications
K. Behdin, A. Acharya, A. Gupta, S. Keerthi and R. Mazumder "QuantEase: Optimization-based Quantization for Language Models – An Efficient and Intuitive Algorithm ", Preprint, 2023. [arxiv]
K. Behdin, W. Chen and R. Mazumder "Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives ", Preprint, 2023. [arxiv]
K. Behdin and R. Mazumder "On Statistical Properties of Sharpness-Aware Minimization:
Provable Guarantees ", Preprint, 2023. [arxiv]
G. Loewinger, K. Behdin, K. T. Kishida, G. Parmigiani, R. Mazumder "Multi-Task Learning for Sparsity Pattern Heterogeneity: A Discrete Optimization Approach ", Preprint, 2022. [arxiv]
K. Behdin, Q. Song, A. Gupta, D. Durfee, A. Acharya, S. Keerthi, R. Mazumder "Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization ", NeurIPS OPT Workshop, 2022. [Paper]
K. Behdin and R. Mazumder " Sparse PCA: A New Scalable Estimator Based On Integer Programming ", Preprint, 2021. [arxiv]
K. Behdin and R. Mazumder " Archetypal Analysis for Sparse Nonnegative Matrix Factorization: Robustness Under Misspecification ", Preprint, 2021. [arxiv]
Google Scholar.
Full list of publications.
CV (Sep 23).
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