OBTAIN: Real-Time Beat Tracking in Audio Signals. - Ali Mottaghi; Kayhan Behdin; Ashkan Esmaeili; Mohammadreza Heydari; Farrokh Marvasti (CoRR, 2017)

Transduction with Matrix Completion Using Smoothed Rank Function. - Ashkan Esmaeili; Kayhan Behdin; Mohammad Amin Fakharian; Farokh Marvasti (CoRR, 2018)

Recovering Quantized Data with Missing Information Using Bilinear Factorization and Augmented Lagrangian Method. - Ashkan Esmaeili; Kayhan Behdin; Sina Al-E.-Mohammad; Farokh Marvasti (CoRR, 2018)

Transductive multi-label learning from missing data using smoothed rank function. - Ashkan Esmaeili; Kayhan Behdin; Mohammad Amin Fakharian; Farokh Marvasti (Pattern Anal. Appl., 2020)

Missing Low-Rank and Sparse Decomposition Based on Smoothed Nuclear Norm. - Masoumeh Azghani; Ashkan Esmaeili; Kayhan Behdin; Farokh Marvasti (IEEE Trans. Circuits Syst. Video Technol., 2020)

Archetypal Analysis for Sparse Nonnegative Matrix Factorization: Robustness Under Misspecification. - Kayhan Behdin; Rahul Mazumder (CoRR, 2021)

Improved Deep Neural Network Generalization Using m-Sharpness-Aware Minimization. - Kayhan Behdin; Qingquan Song; Aman Gupta; David Durfee; Ayan Acharya; S. Sathiya Keerthi; Rahul Mazumder (CoRR, 2022)

GRAND-SLAMIN' Interpretable Additive Modeling with Structural Constraints. - Shibal Ibrahim; Gabriel Afriat; Kayhan Behdin; Rahul Mazumder (NeurIPS, 2023)

mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization. - Kayhan Behdin; Qingquan Song; Aman Gupta; Ayan Acharya; David Durfee; Borja Ocejo; S. Sathiya Keerthi; Rahul Mazumder (CoRR, 2023)

Sharpness-Aware Minimization: An Implicit Regularization Perspective. - Kayhan Behdin; Rahul Mazumder (CoRR, 2023)

Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives. - Kayhan Behdin; Wenyu Chen 003; Rahul Mazumder (CoRR, 2023)

QuantEase: Optimization-based Quantization for Language Models - An Efficient and Intuitive Algorithm. - Kayhan Behdin; Ayan Acharya; Aman Gupta; Sathiya Keerthi Selvaraj; Rahul Mazumder (CoRR, 2023)

End-to-end Feature Selection Approach for Learning Skinny Trees. - Shibal Ibrahim; Kayhan Behdin; Rahul Mazumder (AISTATS, 2024)

OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization. - Xiang Meng 004; Shibal Ibrahim; Kayhan Behdin; Hussein Hazimeh 001; Natalia Ponomareva 001; Rahul Mazumder (ICML, 2024)

ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models. - Xiang Meng 004; Kayhan Behdin; Haoyue Wang; Rahul Mazumder (NeurIPS, 2024)

Sparse NMF with Archetypal Regularization: Computational and Robustness Properties. - Kayhan Behdin; Rahul Mazumder (J. Mach. Learn. Res., 2024)

A unified framework for Sparse plus Low-Rank Matrix Decomposition for LLMs. - Mehdi Makni; Kayhan Behdin; Zheng Xu 002; Natalia Ponomareva 001; Rahul Mazumder (CPAL, 2025)

Efficient Algorithms for Leveraging LLMs for Generative and Predictive Recommender Systems. - Kayhan Behdin; Yun Dai; Gregory Dexter; Aman Gupta; Rahul Mazumder; Ankan Saha; Qingquan Song; Shao Tang; Sirou Zhu; Pin-Lun Hsu (WWW (Companion Volume), 2025)

HASSLE-free: A unified Framework for Sparse plus Low-Rank Matrix Decomposition for LLMs. - Mehdi Makni; Kayhan Behdin; Zheng Xu 002; Natalia Ponomareva 001; Rahul Mazumder (CoRR, 2025)

Efficient AI in Practice: Training and Deployment of Efficient LLMs for Industry Applications. - Kayhan Behdin; Yun Dai; Ata Fatahi Baarzi; Aman Gupta; Qingquan Song; Shao Tang; Hejian Sang; Gregory Dexter; Sirou Zhu; Siyu Zhu; Tejas Dharamsi; Maziar Sanjabi; et al. (CoRR, 2025)

An Optimization Framework for Differentially Private Sparse Fine-Tuning. - Mehdi Makni; Kayhan Behdin; Gabriel Afriat; Zheng Xu 002; Sergei Vassilvitskii; Natalia Ponomareva 001; Hussein Hazimeh 001; Rahul Mazumder (CoRR, 2025)

BP-Seg: A graphical model approach to unsupervised and non-contiguous text segmentation using belief propagation. - Fengyi Li; Kayhan Behdin; Natesh Pillai; Xiaofeng Wang; Zhipeng Wang; Ercan Yildiz (CoRR, 2025)