Alaa Maalouf

Orcid: 0000-0002-3800-9460

According to our database1, Alaa Maalouf authored at least 33 papers between 2019 and 2024.

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Bibliography

2024
<i>Follow Anything:</i> Open-Set Detection, Tracking, and Following in Real-Time.
IEEE Robotics Autom. Lett., 2024

2023
Drive Anywhere: Generalizable End-to-end Autonomous Driving with Multi-modal Foundation Models.
CoRR, 2023

Follow Anything: Open-set detection, tracking, and following in real-time.
CoRR, 2023

Dataset Distillation Meets Provable Subset Selection.
CoRR, 2023

On the Size and Approximation Error of Distilled Sets.
CoRR, 2023

Provable Data Subset Selection For Efficient Neural Network Training.
CoRR, 2023


On the Size and Approximation Error of Distilled Datasets.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deep Learning on Home Drone: Searching for the Optimal Architecture.
Proceedings of the IEEE International Conference on Robotics and Automation, 2023

Provable Data Subset Selection For Efficient Neural Networks Training.
Proceedings of the International Conference on Machine Learning, 2023

AutoCoreset: An Automatic Practical Coreset Construction Framework.
Proceedings of the International Conference on Machine Learning, 2023

2022
MDL-BOOST: Constructing Efficient Machine/Deep Learning Systems via Data and Model Compression.
PhD thesis, 2022

Fast and Accurate Least-Mean-Squares Solvers for High Dimensional Data.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Pruning Neural Networks via Coresets and Convex Geometry: Towards No Assumptions.
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.
Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

Coresets for Data Discretization and Sine Wave Fitting.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021
Overview of accurate coresets.
WIREs Data Mining Knowl. Discov., 2021

No Fine-Tuning, No Cry: Robust SVD for Compressing Deep Networks.
Sensors, 2021

Coresets for the Average Case Error for Finite Query Sets.
Sensors, 2021

Introduction to Coresets: Approximated Mean.
CoRR, 2021

A Unified Approach to Coreset Learning.
CoRR, 2021

Compressing Neural Networks: Towards Determining the Optimal Layer-wise Decomposition.
CoRR, 2021

Provably Approximated ICP.
CoRR, 2021

Compressing Neural Networks: Towards Determining the Optimal Layer-wise Decomposition.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Deep Learning meets Projective Clustering.
Proceedings of the 9th International Conference on Learning Representations, 2021

Provably Approximated Point Cloud Registration.
Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

2020
Compressed Deep Networks: Goodbye SVD, Hello Robust Low-Rank Approximation.
CoRR, 2020

Faster PAC Learning and Smaller Coresets via Smoothed Analysis.
CoRR, 2020

Coresets for Near-Convex Functions.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Tight Sensitivity Bounds For Smaller Coresets.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

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

2019
Introduction to Coresets: Accurate Coresets.
CoRR, 2019

Fast and Accurate Least-Mean-Squares Solvers.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019


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