Sets Clustering. - Ibrahim Jubran; Murad Tukan; Alaa Maalouf; Dan Feldman (ICML, 2020)

Coresets for Near-Convex Functions. - Murad Tukan; Alaa Maalouf; Dan Feldman (NeurIPS, 2020)

Faster PAC Learning and Smaller Coresets via Smoothed Analysis. - Alaa Maalouf; Ibrahim Jubran; Murad Tukan; Dan Feldman (CoRR, 2020)

Compressed Deep Networks: Goodbye SVD, Hello Robust Low-Rank Approximation. - Murad Tukan; Alaa Maalouf; Matan Weksler; Dan Feldman (CoRR, 2020)

Coresets for the Average Case Error for Finite Query Sets. - Alaa Maalouf; Ibrahim Jubran; Murad Tukan; Dan Feldman (Sensors, 2021)

No Fine-Tuning, No Cry: Robust SVD for Compressing Deep Networks. - Murad Tukan; Alaa Maalouf; Matan Weksler; Dan Feldman (Sensors, 2021)

On coresets for support vector machines. - Murad Tukan; Cenk Baykal; Dan Feldman; Daniela Rus (Theor. Comput. Sci., 2021)

Coresets for Data Discretization and Sine Wave Fitting. - Alaa Maalouf; Murad Tukan; Eric Price 001; Daniel M. Kane; Dan Feldman (AISTATS, 2022)

New Coresets for Projective Clustering and Applications. - Murad Tukan; Xuan Wu 002; Samson Zhou; Vladimir Braverman; Dan Feldman (AISTATS, 2022)

Obstacle Aware Sampling for Path Planning. - Murad Tukan; Alaa Maalouf; Dan Feldman; Roi Poranne (IROS, 2022)

Pruning Neural Networks via Coresets and Convex Geometry: Towards No Assumptions. - Murad Tukan; Loay Mualem; Alaa Maalouf (NeurIPS, 2022)

AutoCoreset: An Automatic Practical Coreset Construction Framework. - Alaa Maalouf; Murad Tukan; Vladimir Braverman; Daniela Rus (ICML, 2023)

Provable Data Subset Selection For Efficient Neural Networks Training. - Murad Tukan; Samson Zhou; Alaa Maalouf; Daniela Rus; Vladimir Braverman; Dan Feldman (ICML, 2023)

On the Size and Approximation Error of Distilled Datasets. - Alaa Maalouf; Murad Tukan; Noel Loo; Ramin M. Hasani; Mathias Lechner; Daniela Rus (NeurIPS, 2023)

An Efficient Drifters Deployment Strategy to Evaluate Water Current Velocity Fields. - Murad Tukan; Eli Biton; Roee Diamant (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)

On the Size and Approximation Error of Distilled Sets. - Alaa Maalouf; Murad Tukan; Noel Loo; Ramin M. Hasani; Mathias Lechner; Daniela Rus (CoRR, 2023)

Dataset Distillation Meets Provable Subset Selection. - Murad Tukan; Alaa Maalouf; Margarita Osadchy (CoRR, 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)

Bridging the Gap between General and Down-Closed Convex Sets in Submodular Maximization. - Loay Mualem; Murad Tukan; Moran Feldman (IJCAI, 2024)

Practical 0.385-Approximation for Submodular Maximization Subject to a Cardinality Constraint. - Murad Tukan; Loay Mualem; Moran Feldman (NeurIPS, 2024)