Improved deep neural network generalization using m-sharpness-aware minimization K Behdin, Q Song, A Gupta, D Durfee, A Acharya, S Keerthi, R Mazumder arXiv preprint arXiv:2212.04343, 2022 | 15* | 2022 |
Transductive multi-label learning from missing data using smoothed rank function A Esmaeili, K Behdin, MA Fakharian, F Marvasti Pattern Analysis and Applications 23 (3), 1225-1233, 2020 | 15* | 2020 |
Missing low-rank and sparse decomposition based on smoothed nuclear norm M Azghani, A Esmaeili, K Behdin, F Marvasti IEEE Transactions on Circuits and Systems for Video Technology 30 (6), 1550-1558, 2019 | 13 | 2019 |
OBTAIN: Real-Time Beat Tracking in Audio Signals A Mottaghi, K Behdin, A Esmaeili, M Heydari, F Marvasti ICOSP 2017, The workshop of ICCSIT 2017, Florence, Italy, 2017 | 13 | 2017 |
QuantEase: Optimization-based Quantization for Language Models K Behdin, A Acharya, A Gupta, Q Song, S Zhu, S Keerthi, R Mazumder arXiv e-prints, arXiv: 2309.01885, 2023 | 12* | 2023 |
On Statistical Properties of Sharpness-Aware Minimization: Provable Guarantees K Behdin, R Mazumder arXiv preprint arXiv:2302.11836, 2023 | 12* | 2023 |
Sparse PCA: A new scalable estimator based on integer programming K Behdin, R Mazumder arXiv preprint arXiv:2109.11142, 2021 | 7 | 2021 |
OSSCAR: One-Shot Structured Pruning in Vision and Language Models with Combinatorial Optimization X Meng, S Ibrahim, K Behdin, H Hazimeh, N Ponomareva, R Mazumder arXiv preprint arXiv:2403.12983, 2024 | 5 | 2024 |
GRAND-SLAMIN’Interpretable Additive Modeling with Structural Constraints S Ibrahim, G Afriat, K Behdin, R Mazumder Advances in Neural Information Processing Systems 36, 2024 | 4 | 2024 |
ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models X Meng, K Behdin, H Wang, R Mazumder arXiv preprint arXiv:2406.07831, 2024 | 3 | 2024 |
Sparse NMF with Archetypal Regularization: Computational and Robustness Properties K Behdin, R Mazumder Journal of Machine Learning Research 25, 2024 | 3* | 2024 |
Sparse Gaussian Graphical Models with Discrete Optimization: Computational and Statistical Perspectives K Behdin, W Chen, R Mazumder arXiv preprint arXiv:2307.09366, 2023 | 3 | 2023 |
Recovering quantized data with missing information using bilinear factorization and augmented Lagrangian method A Esmaeili, K Behdin, F Marvasti arXiv preprint arXiv:1810.03222, 2018 | 3 | 2018 |
End-to-end Feature Selection Approach for Learning Skinny Trees S Ibrahim, K Behdin, R Mazumder International Conference on Artificial Intelligence and Statistics, 2863-2871, 2024 | 1 | 2024 |
Differentially Private Best Subset Selection Via Integer Programming K Behdin, P Prastakos, R Mazumder Privacy Regulation and Protection in Machine Learning, 2024 | | 2024 |
Statistical Learning with Discrete Structures: Statistical and Computational Perspectives K Behdin Massachusetts Institute of Technology, 2024 | | 2024 |
Multi-Task Learning for Sparsity Pattern Heterogeneity: A Discrete Optimization Approach G Loewinger, K Behdin, KT Kishida, G Parmigiani, R Mazumder arXiv preprint arXiv:2212.08697, 2022 | | 2022 |
Multi-Task Learning for Sparsity Pattern Heterogeneity: Statistical and Computational Perspectives K Behdin, G Loewinger, KT Kishida, G Parmigiani, R Mazumder arXiv e-prints, arXiv: 2212.08697, 2022 | | 2022 |