Alaa Maalouf
Postdoctoral Associate
Room
32-377
I am a Postdoctoral Researcher at the Computer Science and Artificial Intelligence Laboratory (CSAIL), Massachusetts Institute of Technology (MIT), with Prof. Daniela Rus.
In my research, I focus on increasing the efficiency of machine/deep learning models and algorithms, by suggesting (provable) model/data compression techniques, or by proposing new efficient algorithms and architectures.
Related Links
Last updated Dec 18 '23
Related Links
Publications
Maalouf, Alaa and Jubran, Ibrahim and Feldman, Dan
Fast and accurate least-mean-squares solvers
Advances in Neural Information Processing Systems, 2019
Tukan, Murad and Maalouf, Alaa and Feldman, Dan
Coresets for near-convex functions
Advances in Neural Information Processing Systems, 2020
Jubran, Ibrahim and Maalouf, Alaa and Feldman, Dan
Overview of accurate coresets
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2021
Maalouf, Alaa and Statman, Adiel and Feldman, Dan
Tight sensitivity bounds for smaller coresets
Proceedings of the 26th ACM SIGKDD international conference on knowledge discovery & data mining
Jubran, Ibrahim and Tukan, Murad and Maalouf, Alaa and Feldman, Dan
Sets clustering
International Conference on Machine Learning, 2020
Liebenwein, Lucas and Maalouf, Alaa and Feldman, Dan and Rus, Daniela
Compressing neural networks: Towards determining the optimal layer-wise decomposition
Advances in Neural Information Processing Systems, 2021
Tukan, Murad and Maalouf, Alaa and Weksler, Matan and Feldman, Dan
No fine-tuning, no cry: Robust svd for compressing deep networks
Sensors, 2021
Maalouf, Alaa and Jubran, Ibrahim and Tukan, Murad and Feldman, Dan
Coresets for the average case error for finite query sets
Sensors, 2021
Maalouf, Alaa and Lang, Harry and Rus, Daniela and Feldman, Dan
Deep Learning meets Projective Clustering
International Conference on Learning Representations 2020
Jubran, Ibrahim and Maalouf, Alaa and Kimmel, Ron and Feldman, Dan
Provably Approximated Point Cloud Registration
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021
Maalouf, Alaa and Eini, Gilad and Mussay, Ben and Feldman, Dan and Osadchy, Margarita
A unified approach to coreset learning
IEEE Transactions on Neural Networks and Learning Systems, 2022
Maalouf, Alaa and Tukan, Murad and Price, Eric and Kane, Daniel M and Feldman, Dan
Coresets for Data Discretization and Sine Wave Fitting
International Conference on Artificial Intelligence and Statistics 2020
Tukan, Murad and Maalouf, Alaa and Feldman, Dan and Poranne, Roi
Obstacle Aware Sampling for Path Planning
arXiv preprint arXiv:2203.04075, 2022
Maalouf, Alaa and Jubran, Ibrahim and Feldman, Dan
Fast and accurate least-mean-squares solvers for high dimensional data
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2022
Tukan, Murad and Mualem, Loay and Maalouf, Alaa
Pruning neural networks via coresets and convex geometry: Towards no assumptions
arXiv preprint arXiv:2209.08554, 2022
Maalouf, Alaa and Gurfinkel, Yotam and Diker, Barak and Gal, Oren and Rus, Daniela and Feldman, Dan
Deep Learning on Home Drone: Searching for the Optimal Architecture
arXiv preprint arXiv:2209.11064, 2022
Maalouf, Alaa and Jubran, Ibrahim and Feldman, Dan
Introduction to Coresets: Approximated Mean
arXiv preprint arXiv:2111.03046, 2021