Kayhan Behdin

Publications (2021-)

1. 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]

2. K. Behdin, W. Chen and R. Mazumder "Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives ", Preprint, 2023. [arxiv]

3. K. Behdin and R. Mazumder "On Statistical Properties of Sharpness-Aware Minimization: Provable Guarantees ", Preprint, 2023. [arxiv]

4. 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], [CRAN], [R package]

5. 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]

6. K. Behdin and R. Mazumder " Sparse PCA: A New Scalable Estimator Based On Integer Programming ", Preprint, 2021. [arxiv], [Code]

7. K. Behdin and R. Mazumder " Archetypal Analysis for Sparse Nonnegative Matrix Factorization: Robustness Under Misspecification ", Preprint, 2021. [arxiv], [Code]

Publications (-2020)

1. A. Esmaeili, K. Behdin, M. A. Fakharian and F. Marvasti " Transductive Multi-label Learning From Missing Data Using Smoothed Rank Function ", Pattern Analysis and Applications, 2020. [Paper]

2. M. Azghani, A. Esmaeili, K. Behdin and F. Marvasti " Missing Low-Rank and Sparse Decomposition Based on Smoothed Nuclear Norm ", IEEE Transactions on Circuits and Systems for Video Technology, 2019. [Paper]