Murad Tukan

According to our database, Murad Tukan authored at least 21 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Practical 0.385-Approximation for Submodular Maximization Subject to a Cardinality Constraint.

Murad Tukan, Loay Mualem, Moran Feldman

CoRR, 2024

Bridging the Gap between General and Down-Closed Convex Sets in Submodular Maximization.

Loay Mualem, Murad Tukan, Moran Feldman

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2023

ORBSLAM3-Enhanced Autonomous Toy Drones: Pioneering Indoor Exploration.

Murad Tukan, Fares Fares, Yotam Grufinkle, Ido Talmor, Loay Mualem, Vladimir Braverman, Dan Feldman

CoRR, 2023

Dataset Distillation Meets Provable Subset Selection.

Murad Tukan, Alaa Maalouf, Margarita Osadchy

CoRR, 2023

On the Size and Approximation Error of Distilled Sets.

Alaa Maalouf, Murad Tukan, Noel Loo, Ramin M. Hasani, Mathias Lechner, Daniela Rus

CoRR, 2023

Provable Data Subset Selection For Efficient Neural Network Training.

Murad Tukan, Samson Zhou, Alaa Maalouf, Daniela Rus, Vladimir Braverman, Dan Feldman

CoRR, 2023

An Efficient Drifters Deployment Strategy to Evaluate Water Current Velocity Fields.

Murad Tukan, Eli Biton, Roee Diamant

CoRR, 2023

On the Size and Approximation Error of Distilled Datasets.

Alaa Maalouf, Murad Tukan, Noel Loo, Ramin M. Hasani, Mathias Lechner, Daniela Rus

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Provable Data Subset Selection For Efficient Neural Networks Training.

Murad Tukan, Samson Zhou, Alaa Maalouf, Daniela Rus, Vladimir Braverman, Dan Feldman

Proceedings of the International Conference on Machine Learning, 2023

AutoCoreset: An Automatic Practical Coreset Construction Framework.

Alaa Maalouf, Murad Tukan, Vladimir Braverman, Daniela Rus

Proceedings of the International Conference on Machine Learning, 2023

2022

Pruning Neural Networks via Coresets and Convex Geometry: Towards No Assumptions.

Murad Tukan, Loay Mualem, Alaa Maalouf

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Obstacle Aware Sampling for Path Planning.

Murad Tukan, Alaa Maalouf, Dan Feldman, Roi Poranne

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

New Coresets for Projective Clustering and Applications.

Murad Tukan, Xuan Wu, Samson Zhou, Vladimir Braverman, Dan Feldman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

Coresets for Data Discretization and Sine Wave Fitting.

Alaa Maalouf, Murad Tukan, Eric Price, Daniel M. Kane, Dan Feldman

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

On coresets for support vector machines.

Murad Tukan, Cenk Baykal, Dan Feldman, Daniela Rus

Theor. Comput. Sci., 2021

No Fine-Tuning, No Cry: Robust SVD for Compressing Deep Networks.

Murad Tukan, Alaa Maalouf, Matan Weksler, Dan Feldman

Sensors, 2021

Coresets for the Average Case Error for Finite Query Sets.

Alaa Maalouf, Ibrahim Jubran, Murad Tukan, Dan Feldman

Sensors, 2021

2020

Compressed Deep Networks: Goodbye SVD, Hello Robust Low-Rank Approximation.

Murad Tukan, Alaa Maalouf, Matan Weksler, Dan Feldman

CoRR, 2020

Faster PAC Learning and Smaller Coresets via Smoothed Analysis.

Alaa Maalouf, Ibrahim Jubran, Murad Tukan, Dan Feldman

CoRR, 2020

Coresets for Near-Convex Functions.

Murad Tukan, Alaa Maalouf, Dan Feldman

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Sets Clustering.

Ibrahim Jubran, Murad Tukan, Alaa Maalouf, Dan Feldman

Proceedings of the 37th International Conference on Machine Learning, 2020