Dan Feldman

According to our database, Dan Feldman authored at least 105 papers between 2006 and 2023.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of two.

2023

Least-Mean-Squares Coresets for Infinite Streams.

Vladimir Braverman, Dan Feldman, Harry Lang, Daniela Rus, Adiel Statman

IEEE Trans. Knowl. Data Eng., September, 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

Affective Polarization in Social Networks.

Dan Feldman, Ashwin Rao, Zihao He, Kristina Lerman

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

Deep Learning on Home Drone: Searching for the Optimal Architecture.

Alaa Maalouf, Yotam Gurfinkel, Barak Diker, Oren Gal, Daniela Rus, Dan Feldman

Proceedings of the IEEE International Conference on Robotics and Automation, 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

2022

Data-Independent Structured Pruning of Neural Networks via Coresets.

Ben Mussay, Dan Feldman, Samson Zhou, Vladimir Braverman, Margarita Osadchy

IEEE Trans. Neural Networks Learn. Syst., 2022

Aligning Points to Lines: Provable Approximations.

Ibrahim Jubran, Dan Feldman

IEEE Trans. Knowl. Data Eng., 2022

Sensitivity-Informed Provable Pruning of Neural Networks.

Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman, Daniela Rus

SIAM J. Math. Data Sci., 2022

Fast and Accurate Least-Mean-Squares Solvers for High Dimensional Data.

Alaa Maalouf, Ibrahim Jubran, Dan Feldman

IEEE Trans. Pattern Anal. Mach. Intell., 2022

Coreset for Line-Sets Clustering.

Sagi Lotan, Ernesto Evgeniy Sanches Shayda, Dan Feldman

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

Newton-PnP: Real-time Visual Navigation for Autonomous Toy-Drones.

Ibrahim Jubran, Fares Fares, Yuval Alfassi, Firas Ayoub, Dan Feldman

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

Generic Coreset for Scalable Learning of Monotonic Kernels: Logistic Regression, Sigmoid and more.

Elad Tolochinsky, Ibrahim Jubran, Dan Feldman

Proceedings of the International Conference on Machine Learning, 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

Overview of accurate coresets.

Ibrahim Jubran, Alaa Maalouf, Dan Feldman

WIREs Data Mining Knowl. Discov., 2021

Artificial Intelligence for Modeling Complex Systems: Taming the Complexity of Expert Models to Improve Decision Making.

Yolanda Gil, Daniel Garijo, Deborah Khider, Craig A. Knoblock, Varun Ratnakar, Maximiliano Osorio, Hernán Vargas, Minh Pham, Jay Pujara, Basel Shbita, Binh Vu, Yao-Yi Chiang, Dan Feldman, Yijun Lin, Hayley Song, Vipin Kumar, Ankush Khandelwal, Michael S. Steinbach, Kshitij Tayal, Shaoming Xu, Suzanne A. Pierce, Lissa Pearson, Daniel Hardesty-Lewis, Ewa Deelman, Rafael Ferreira da Silva, Rajiv Mayani, Armen R. Kemanian, Yuning Shi, Lorne Leonard, Scott D. Peckham, Maria Stoica, Kelly M. Cobourn, Zeya Zhang, Christopher J. Duffy, Lele Shu

ACM Trans. Interact. Intell. Syst., 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

Introduction to Coresets: Approximated Mean.

Alaa Maalouf, Ibrahim Jubran, Dan Feldman

CoRR, 2021

A Unified Approach to Coreset Learning.

Alaa Maalouf, Gilad Eini, Ben Mussay, Dan Feldman, Margarita Osadchy

CoRR, 2021

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

Lucas Liebenwein, Alaa Maalouf, Oren Gal, Dan Feldman, Daniela Rus

CoRR, 2021

Low-Regret Active learning.

Cenk Baykal, Lucas Liebenwein, Dan Feldman, Daniela Rus

CoRR, 2021

Provably Approximated ICP.

Ibrahim Jubran, Alaa Maalouf, Ron Kimmel, Dan Feldman

CoRR, 2021

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

Lucas Liebenwein, Alaa Maalouf, Dan Feldman, Daniela Rus

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Coresets for Decision Trees of Signals.

Ibrahim Jubran, Ernesto Evgeniy Sanches Shayda, Ilan Newman, Dan Feldman

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Resolving battery status and customer matching to create 24/7 drones based advertisement system.

Jeryes Danial, Yosi Ben-Asher, Dan Feldman

Proceedings of the Fifth IEEE International Conference on Robotic Computing, 2021

Deep Learning meets Projective Clustering.

Alaa Maalouf, Harry Lang, Daniela Rus, Dan Feldman

Proceedings of the 9th International Conference on Learning Representations, 2021

Provably Approximated Point Cloud Registration.

Ibrahim Jubran, Alaa Maalouf, Ron Kimmel, Dan Feldman

Proceedings of the 2021 IEEE/CVF International Conference on Computer Vision, 2021

Efficient Coreset Constructions via Sensitivity Sampling.

Vladimir Braverman, Dan Feldman, Harry Lang, Adiel Statman, Samson Zhou

Proceedings of the Asian Conference on Machine Learning, 2021

2020

Core-sets: An updated survey.

Dan Feldman

WIREs Data Mining Knowl. Discov., 2020

Turning Big Data Into Tiny Data: Constant-Size Coresets for k-Means, PCA, and Projective Clustering.

Dan Feldman, Melanie Schmidt, Christian Sohler

SIAM J. Comput., 2020

Autonomous Toy Drone via Coresets for Pose Estimation.

Soliman Nasser, Ibrahim Jubran, Dan Feldman

Sensors, 2020

Secure k-ish Nearest Neighbors Classifier.

Hayim Shaul, Dan Feldman, Daniela Rus

Proc. Priv. Enhancing Technol., 2020

Real-time EEG classification via coresets for BCI applications.

Eitan Netzer, Alex Frid, Dan Feldman

Eng. Appl. Artif. Intell., 2020

Faster Projective Clustering Approximation of Big Data.

Adiel Statman, Liat Rozenberg, Dan Feldman

CoRR, 2020

Introduction to Core-sets: an Updated Survey.

Dan Feldman

CoRR, 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

Sparse Coresets for SVD on Infinite Streams.

Vladimir Braverman, Dan Feldman, Harry Lang, Daniela Rus, Adiel Statman

CoRR, 2020

k-Means: Outliers-Resistant Clustering+++.

Adiel Statman, Liat Rozenberg, Dan Feldman

Algorithms, 2020

Sphere Fitting with Applications to Machine Tracking.

Dror Epstein, Dan Feldman

Algorithms, 2020

Deterministic Coresets for k-Means of Big Sparse Data †.

Artem Barger, Dan Feldman

Algorithms, 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

Tight Sensitivity Bounds For Smaller Coresets.

Alaa Maalouf, Adiel Statman, Dan Feldman

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

Sets Clustering.

Ibrahim Jubran, Murad Tukan, Alaa Maalouf, Dan Feldman

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

Data-Independent Neural Pruning via Coresets.

Ben Mussay, Margarita Osadchy, Vladimir Braverman, Samson Zhou, Dan Feldman

Proceedings of the 8th International Conference on Learning Representations, 2020

Provable Filter Pruning for Efficient Neural Networks.

Lucas Liebenwein, Cenk Baykal, Harry Lang, Dan Feldman, Daniela Rus

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

Secure Data Retrieval on the Cloud: Homomorphic Encryption meets Coresets.

Adi Akavia, Dan Feldman, Hayim Shaul

IACR Trans. Cryptogr. Hardw. Embed. Syst., 2019

Position Estimation of Moving Objects: Practical Provable Approximation.

Jeryes Danial, Dan Feldman, Ariel Hutterer

IEEE Robotics Autom. Lett., 2019

Introduction to Coresets: Accurate Coresets.

Ibrahim Jubran, Alaa Maalouf, Dan Feldman

CoRR, 2019

SiPPing Neural Networks: Sensitivity-informed Provable Pruning of Neural Networks.

Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman, Daniela Rus

CoRR, 2019

On Activation Function Coresets for Network Pruning.

Ben Mussay, Samson Zhou, Vladimir Braverman, Dan Feldman

CoRR, 2019

Coresets for Gaussian Mixture Models of Any Shape.

Dan Feldman, Zahi Kfir, Xuan Wu

CoRR, 2019

Provable Approximations for Constrained $\ell_p$ Regression.

Ibrahim Jubran, David Cohn, Dan Feldman

CoRR, 2019

Finding Patterns in Signals Using Lossy Text Compression.

Liat Rozenberg, Sagi Lotan, Dan Feldman

Algorithms, 2019

Deterministic Coresets for Stochastic Matrices with Applications to Scalable Sparse PageRank.

Harry Lang, Cenk Baykal, Najib Abu Samra, Tony Tannous, Dan Feldman, Daniela Rus

Proceedings of the Theory and Applications of Models of Computation, 2019

k-Means Clustering of Lines for Big Data.

Yair Marom, Dan Feldman

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Fast and Accurate Least-Mean-Squares Solvers.

Alaa Maalouf, Ibrahim Jubran, Dan Feldman

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

An intelligent interface for integrating climate, hydrology, agriculture, and socioeconomic models.

Daniel Garijo, Deborah Khider, Varun Ratnakar, Yolanda Gil, Ewa Deelman, Rafael Ferreira da Silva, Craig A. Knoblock, Yao-Yi Chiang, Minh Pham, Jay Pujara, Binh Vu, Dan Feldman, Rajiv Mayani, Kelly M. Cobourn, Christopher J. Duffy, Armen R. Kemanian, Lele Shu, Vipin Kumar, Ankush Khandelwal, Kshitij Tayal, Scott D. Peckham, Maria Stoica, Anna Dabrowski, Daniel Hardesty-Lewis, Suzanne A. Pierce

Proceedings of the 24th International Conference on Intelligent User Interfaces: Companion, 2019

Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds.

Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman, Daniela Rus

Proceedings of the 7th International Conference on Learning Representations, 2019

Streaming Coreset Constructions for M-Estimators.

Vladimir Braverman, Dan Feldman, Harry Lang, Daniela Rus

Proceedings of the Approximation, 2019

2018

Quadcopter Tracks Quadcopter via Real-Time Shape Fitting.

Dror Epstein, Dan Feldman

IEEE Robotics Autom. Lett., 2018

Secure Search via Multi-Ring Fully Homomorphic Encryption.

Adi Akavia, Dan Feldman, Hayim Shaul

IACR Cryptol. ePrint Arch., 2018

Minimizing Sum of Non-Convex but Piecewise log-Lipschitz Functions using Coresets.

Ibrahim Jubran, Dan Feldman

CoRR, 2018

Coresets For Monotonic Functions with Applications to Deep Learning.

Elad Tolochinsky, Dan Feldman

CoRR, 2018

Scalable Secure Computation of Statistical Functions with Applications to k-Nearest Neighbors.

Hayim Shaul, Dan Feldman, Daniela Rus

CoRR, 2018

Secure Search on Encrypted Data via Multi-Ring Sketch.

Adi Akavia, Dan Feldman, Hayim Shaul

Proceedings of the 2018 ACM SIGSAC Conference on Computer and Communications Security, 2018

2017

Training Gaussian Mixture Models at Scale via Coresets.

Mario Lucic, Matthew Faulkner, Andreas Krause, Dan Feldman

J. Mach. Learn. Res., 2017

Secure Search on the Cloud via Coresets and Sketches.

Adi Akavia, Dan Feldman, Hayim Shaul

CoRR, 2017

Cloud computing for big data analytics in the Process Control Industry.

Ephraim Goldin, Dan Feldman, George K. Georgoulas, Miguel Castaño, George Nikolakopoulos

Proceedings of the 25th Mediterranean Conference on Control and Automation, 2017

Coresets for differentially private k-means clustering and applications to privacy in mobile sensor networks.

Dan Feldman, Chongyuan Xiang, Ruihao Zhu, Daniela Rus

Proceedings of the 16th ACM/IEEE International Conference on Information Processing in Sensor Networks, 2017

Coresets for Vector Summarization with Applications to Network Graphs.

Dan Feldman, Sedat Ozer, Daniela Rus

Proceedings of the 34th International Conference on Machine Learning, 2017

Automatic alignment of geographic features in contemporary vector data and historical maps.

Weiwei Duan, Yao-Yi Chiang, Craig A. Knoblock, Vinil Jain, Dan Feldman, Johannes H. Uhl, Stefan Leyk

Proceedings of the 1st Workshop on Artificial Intelligence and Deep Learning for Geographic Knowledge Discovery, 2017

2016

New Frameworks for Offline and Streaming Coreset Constructions.

Vladimir Braverman, Dan Feldman, Harry Lang

CoRR, 2016

<i>k</i>-Means for Streaming and Distributed Big Sparse Data.

Artem Barger, Dan Feldman

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Dimensionality Reduction of Massive Sparse Datasets Using Coresets.

Dan Feldman, Mikhail Volkov, Daniela Rus

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

iDiary: From GPS Signals to a Text- Searchable Diary.

Dan Feldman, Cynthia R. Sung, Andrew Sugaya, Daniela Rus

ACM Trans. Sens. Networks, 2015

Low-cost and Faster Tracking Systems Using Core-sets for Pose-Estimation.

Soliman Nasser, Ibrahim Jubran, Dan Feldman

CoRR, 2015

k-Means for Streaming and Distributed Big Sparse Data.

Artem Barger, Dan Feldman

CoRR, 2015

More Constraints, Smaller Coresets: Constrained Matrix Approximation of Sparse Big Data.

Dan Feldman, Tamir Tassa

Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

Fleye on the car: big data meets the internet of things.

Soliman Nasser, Andew Barry, Marek Doniec, Guy Peled, Guy Rosman, Daniela Rus, Mikhail Volkov, Dan Feldman

Proceedings of the 14th International Conference on Information Processing in Sensor Networks, 2015

Coresets for visual summarization with applications to loop closure.

Mikhail Volkov, Guy Rosman, Dan Feldman, John W. Fisher III, Daniela Rus

Proceedings of the IEEE International Conference on Robotics and Automation, 2015

2014

Coresets for k-Segmentation of Streaming Data.

Guy Rosman, Mikhail Volkov, Dan Feldman, John W. Fisher III, Daniela Rus

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Visual precis generation using coresets.

Rohan Paul, Dan Feldman, Daniela Rus, Paul Newman

Proceedings of the 2014 IEEE International Conference on Robotics and Automation, 2014

Smallest enclosing ball for probabilistic data.

Alexander Munteanu, Christian Sohler, Dan Feldman

Proceedings of the 30th Annual Symposium on Computational Geometry, 2014

2013

Learning Big (Image) Data via Coresets for Dictionaries.

Dan Feldman, Micha Feigin, Nir A. Sochen

J. Math. Imaging Vis., 2013

Turning big data into tiny data: Constant-size coresets for <i>k</i>-means, PCA and projective clustering.

Dan Feldman, Melanie Schmidt, Christian Sohler

Proceedings of the Twenty-Fourth Annual ACM-SIAM Symposium on Discrete Algorithms, 2013

K-robots clustering of moving sensors using coresets.

Dan Feldman, Stephanie Gil, Ross A. Knepper, Brian J. Julian, Daniela Rus

Proceedings of the 2013 IEEE International Conference on Robotics and Automation, 2013

2012

Data reduction for weighted and outlier-resistant clustering.

Dan Feldman, Leonard J. Schulman

Proceedings of the Twenty-Third Annual ACM-SIAM Symposium on Discrete Algorithms, 2012

Trajectory clustering for motion prediction.

Cynthia R. Sung, Dan Feldman, Daniela Rus

Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012

Communication coverage for independently moving robots.

Stephanie Gil, Dan Feldman, Daniela Rus

Proceedings of the 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2012

An effective coreset compression algorithm for large scale sensor networks.

Dan Feldman, Andrew Sugaya, Daniela Rus

Proceedings of the 11th International Conference on Information Processing in Sensor Networks (co-located with CPS Week 2012), 2012

The single pixel GPS: learning big data signals from tiny coresets.

Dan Feldman, Cynthia R. Sung, Daniela Rus

Proceedings of the SIGSPATIAL 2012 International Conference on Advances in Geographic Information Systems (formerly known as GIS), 2012

2011

A unified framework for approximating and clustering data.

Dan Feldman, Michael Langberg

Proceedings of the 43rd ACM Symposium on Theory of Computing, 2011

From High Definition Image to Low Space Optimization.

Micha Feigin, Dan Feldman, Nir A. Sochen

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2011

Scalable Training of Mixture Models via Coresets.

Dan Feldman, Matthew Faulkner, Andreas Krause

Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011

2010

Coresets and their applications

Dan Feldman

PhD thesis, 2010

Coresets and Sketches for High Dimensional Subspace Approximation Problems.

Dan Feldman, Morteza Monemizadeh, Christian Sohler, David P. Woodruff

Proceedings of the Twenty-First Annual ACM-SIAM Symposium on Discrete Algorithms, 2010

2009

Private coresets.

Dan Feldman, Amos Fiat, Haim Kaplan, Kobbi Nissim

Proceedings of the 41st Annual ACM Symposium on Theory of Computing, 2009

2007

A PTAS for k-means clustering based on weak coresets.

Dan Feldman, Morteza Monemizadeh, Christian Sohler

Proceedings of the 23rd ACM Symposium on Computational Geometry, 2007

Bi-criteria linear-time approximations for generalized k-mean/median/center.

Dan Feldman, Amos Fiat, Micha Sharir, Danny Segev

Proceedings of the 23rd ACM Symposium on Computational Geometry, 2007

2006

Coresets forWeighted Facilities and Their Applications.

Dan Feldman, Amos Fiat, Micha Sharir

Proceedings of the 47th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2006), 2006