Dan Feldman

ORCID

Publication Activity (10 Years)

Years Active: 2006-2024
Publications (10 Years): 101

Top Venues

Publications

Alaa Maalouf, Gilad Eini, Ben Mussay, Dan Feldman, Margarita Osadchy
A Unified Approach to Coreset Learning. IEEE Trans. Neural Networks Learn. Syst. 35 (5) (2024)
Alaa Maalouf, Yotam Gurfinkel, Barak Diker, Oren Gal, Daniela Rus, Dan Feldman
Deep Learning on Home Drone: Searching for the Optimal Architecture. ICRA (2023)
Vladimir Braverman, Dan Feldman, Harry Lang, Daniela Rus, Adiel Statman
Least-Mean-Squares Coresets for Infinite Streams. IEEE Trans. Knowl. Data Eng. 35 (9) (2023)
Murad Tukan, Samson Zhou, Alaa Maalouf, Daniela Rus, Vladimir Braverman, Dan Feldman
Provable Data Subset Selection For Efficient Neural Network Training. CoRR (2023)
Dan Feldman, Ashwin Rao, Zihao He, Kristina Lerman
Affective Polarization in Social Networks. CoRR (2023)
Murad Tukan, Samson Zhou, Alaa Maalouf, Daniela Rus, Vladimir Braverman, Dan Feldman
Provable Data Subset Selection For Efficient Neural Networks Training. ICML (2023)
Murad Tukan, Fares Fares, Yotam Grufinkle, Ido Talmor, Loay Mualem, Vladimir Braverman, Dan Feldman
ORBSLAM3-Enhanced Autonomous Toy Drones: Pioneering Indoor Exploration. CoRR (2023)
Alaa Maalouf, Ibrahim Jubran, Dan Feldman
Fast and Accurate Least-Mean-Squares Solvers for High Dimensional Data. IEEE Trans. Pattern Anal. Mach. Intell. 44 (12) (2022)
Murad Tukan, Alaa Maalouf, Dan Feldman, Roi Poranne
Obstacle Aware Sampling for Path Planning. CoRR (2022)
Murad Tukan, Alaa Maalouf, Dan Feldman, Roi Poranne
Obstacle Aware Sampling for Path Planning. IROS (2022)
Ben Mussay, Dan Feldman, Samson Zhou, Vladimir Braverman, Margarita Osadchy
Data-Independent Structured Pruning of Neural Networks via Coresets. IEEE Trans. Neural Networks Learn. Syst. 33 (12) (2022)
Alaa Maalouf, Murad Tukan, Eric Price, Daniel M. Kane, Dan Feldman
Coresets for Data Discretization and Sine Wave Fitting. AISTATS (2022)
Murad Tukan, Xuan Wu, Samson Zhou, Vladimir Braverman, Dan Feldman
New Coresets for Projective Clustering and Applications. AISTATS (2022)
Sagi Lotan, Ernesto Evgeniy Sanches Shayda, Dan Feldman
Coreset for Line-Sets Clustering. NeurIPS (2022)
Murad Tukan, Xuan Wu, Samson Zhou, Vladimir Braverman, Dan Feldman
New Coresets for Projective Clustering and Applications. CoRR (2022)
Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman, Daniela Rus
Sensitivity-Informed Provable Pruning of Neural Networks. SIAM J. Math. Data Sci. 4 (1) (2022)
Elad Tolochinsky, Ibrahim Jubran, Dan Feldman
Generic Coreset for Scalable Learning of Monotonic Kernels: Logistic Regression, Sigmoid and more. ICML (2022)
Ibrahim Jubran, Fares Fares, Yuval Alfassi, Firas Ayoub, Dan Feldman
Newton-PnP: Real-time Visual Navigation for Autonomous Toy-Drones. CoRR (2022)
Alaa Maalouf, Murad Tukan, Eric Price, Daniel Kane, Dan Feldman
Coresets for Data Discretization and Sine Wave Fitting. CoRR (2022)
Ibrahim Jubran, Dan Feldman
Aligning Points to Lines: Provable Approximations. IEEE Trans. Knowl. Data Eng. 34 (1) (2022)
Alaa Maalouf, Yotam Gurfinkel, Barak Diker, Oren Gal, Daniela Rus, Dan Feldman
Deep Learning on Home Drone: Searching for the Optimal Architecture. CoRR (2022)
Ibrahim Jubran, Fares Fares, Yuval Alfassi, Firas Ayoub, Dan Feldman
Newton-PnP: Real-time Visual Navigation for Autonomous Toy-Drones. IROS (2022)
Murad Tukan, Cenk Baykal, Dan Feldman, Daniela Rus
On coresets for support vector machines. Theor. Comput. Sci. 890 (2021)
Ibrahim Jubran, Ernesto Evgeniy Sanches Shayda, Ilan Newman, Dan Feldman
Coresets for Decision Trees of Signals. NeurIPS (2021)
Cenk Baykal, Lucas Liebenwein, Dan Feldman, Daniela Rus
Low-Regret Active learning. CoRR (2021)
Alaa Maalouf, Gilad Eini, Ben Mussay, Dan Feldman, Margarita Osadchy
A Unified Approach to Coreset Learning. CoRR (2021)
Alaa Maalouf, Harry Lang, Daniela Rus, Dan Feldman
Deep Learning meets Projective Clustering. ICLR (2021)
Alaa Maalouf, Ibrahim Jubran, Murad Tukan, Dan Feldman
Coresets for the Average Case Error for Finite Query Sets. Sensors 21 (19) (2021)
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
Artificial Intelligence for Modeling Complex Systems: Taming the Complexity of Expert Models to Improve Decision Making. ACM Trans. Interact. Intell. Syst. 11 (2) (2021)
Ibrahim Jubran, Alaa Maalouf, Ron Kimmel, Dan Feldman
Provably Approximated Point Cloud Registration. ICCV (2021)
Murad Tukan, Alaa Maalouf, Matan Weksler, Dan Feldman
No Fine-Tuning, No Cry: Robust SVD for Compressing Deep Networks. Sensors 21 (16) (2021)
Lucas Liebenwein, Alaa Maalouf, Dan Feldman, Daniela Rus
Compressing Neural Networks: Towards Determining the Optimal Layer-wise Decomposition. NeurIPS (2021)
Ibrahim Jubran, Ernesto Evgeniy Sanches Shayda, Ilan Newman, Dan Feldman
Coresets for Decision Trees of Signals. CoRR (2021)
Lucas Liebenwein, Alaa Maalouf, Oren Gal, Dan Feldman, Daniela Rus
Compressing Neural Networks: Towards Determining the Optimal Layer-wise Decomposition. CoRR (2021)
Alaa Maalouf, Ibrahim Jubran, Dan Feldman
Introduction to Coresets: Approximated Mean. CoRR (2021)
Vladimir Braverman, Dan Feldman, Harry Lang, Adiel Statman, Samson Zhou
Efficient Coreset Constructions via Sensitivity Sampling. ACML (2021)
Ibrahim Jubran, Alaa Maalouf, Ron Kimmel, Dan Feldman
Provably Approximated ICP. CoRR (2021)
Ibrahim Jubran, Alaa Maalouf, Dan Feldman
Overview of accurate coresets. WIREs Data Mining Knowl. Discov. 11 (6) (2021)
Jeryes Danial, Yosi Ben-Asher, Dan Feldman
Resolving battery status and customer matching to create 24/7 drones based advertisement system. IRC (2021)
Artem Barger, Dan Feldman
Deterministic Coresets for k-Means of Big Sparse Data †. Algorithms 13 (4) (2020)
Murad Tukan, Alaa Maalouf, Dan Feldman
Coresets for Near-Convex Functions. NeurIPS (2020)
Alaa Maalouf, Adiel Statman, Dan Feldman
Tight Sensitivity Bounds For Smaller Coresets. KDD (2020)
Murad Tukan, Alaa Maalouf, Matan Weksler, Dan Feldman
Compressed Deep Networks: Goodbye SVD, Hello Robust Low-Rank Approximation. CoRR (2020)
Dror Epstein, Dan Feldman
Sphere Fitting with Applications to Machine Tracking. Algorithms 13 (8) (2020)
Murad Tukan, Cenk Baykal, Dan Feldman, Daniela Rus
On Coresets for Support Vector Machines. TAMC (2020)
Soliman Nasser, Ibrahim Jubran, Dan Feldman
Autonomous Toy Drone via Coresets for Pose Estimation. Sensors 20 (11) (2020)
Hayim Shaul, Dan Feldman, Daniela Rus
Secure k-ish nearest neighbors classifier. IACR Cryptol. ePrint Arch. 2020 (2020)
Ben Mussay, Margarita Osadchy, Vladimir Braverman, Samson Zhou, Dan Feldman
Data-Independent Neural Pruning via Coresets. ICLR (2020)
Lucas Liebenwein, Cenk Baykal, Harry Lang, Dan Feldman, Daniela Rus
Provable Filter Pruning for Efficient Neural Networks. ICLR (2020)
Dan Feldman
Introduction to Core-sets: an Updated Survey. CoRR (2020)
Ibrahim Jubran, Murad Tukan, Alaa Maalouf, Dan Feldman
Sets Clustering. CoRR (2020)
Adiel Statman, Liat Rozenberg, Dan Feldman
k-Means: Outliers-Resistant Clustering+++. Algorithms 13 (12) (2020)
Murad Tukan, Alaa Maalouf, Dan Feldman
Coresets for Near-Convex Functions. CoRR (2020)
Ibrahim Jubran, Murad Tukan, Alaa Maalouf, Dan Feldman
Sets Clustering. ICML (2020)
Eitan Netzer, Alex Frid, Dan Feldman
Real-time EEG classification via coresets for BCI applications. Eng. Appl. Artif. Intell. 89 (2020)
Vladimir Braverman, Dan Feldman, Harry Lang, Daniela Rus, Adiel Statman
Sparse Coresets for SVD on Infinite Streams. CoRR (2020)
Hayim Shaul, Dan Feldman, Daniela Rus
Secure k-ish Nearest Neighbors Classifier. Proc. Priv. Enhancing Technol. 2020 (3) (2020)
Alaa Maalouf, Ibrahim Jubran, Murad Tukan, Dan Feldman
Faster PAC Learning and Smaller Coresets via Smoothed Analysis. CoRR (2020)
Murad Tukan, Cenk Baykal, Dan Feldman, Daniela Rus
On Coresets for Support Vector Machines. CoRR (2020)
Alaa Maalouf, Harry Lang, Daniela Rus, Dan Feldman
Deep Learning Meets Projective Clustering. CoRR (2020)
Ben Mussay, Dan Feldman, Samson Zhou, Vladimir Braverman, Margarita Osadchy
Data-Independent Structured Pruning of Neural Networks via Coresets. CoRR (2020)
Dan Feldman
Core-sets: An updated survey. WIREs Data Mining Knowl. Discov. 10 (1) (2020)
Dan Feldman, Melanie Schmidt, Christian Sohler
Turning Big Data Into Tiny Data: Constant-Size Coresets for k-Means, PCA, and Projective Clustering. SIAM J. Comput. 49 (3) (2020)
Adiel Statman, Liat Rozenberg, Dan Feldman
Faster Projective Clustering Approximation of Big Data. CoRR (2020)
Lucas Liebenwein, Cenk Baykal, Harry Lang, Dan Feldman, Daniela Rus
Provable Filter Pruning for Efficient Neural Networks. CoRR (2019)
Ibrahim Jubran, David Cohn, Dan Feldman
Provable Approximations for Constrained $\ell_p$ Regression. CoRR (2019)
Eitan Netzer, Alex Frid, Dan Feldman
Real-Time EEG Classification via Coresets for BCI Applications. CoRR (2019)
Ibrahim Jubran, Alaa Maalouf, Dan Feldman
Introduction to Coresets: Accurate Coresets. CoRR (2019)
Ben Mussay, Samson Zhou, Vladimir Braverman, Dan Feldman
On Activation Function Coresets for Network Pruning. CoRR (2019)
Yair Marom, Dan Feldman
k-Means Clustering of Lines for Big Data. NeurIPS (2019)
Vladimir Braverman, Dan Feldman, Harry Lang, Daniela Rus
Streaming Coreset Constructions for M-Estimators. APPROX-RANDOM (2019)
Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman, Daniela Rus
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds. ICLR (Poster) (2019)
Dan Feldman, Zahi Kfir, Xuan Wu
Coresets for Gaussian Mixture Models of Any Shape. CoRR (2019)
Liat Rozenberg, Sagi Lotan, Dan Feldman
Finding Patterns in Signals Using Lossy Text Compression. Algorithms 12 (12) (2019)
Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman, Daniela Rus
SiPPing Neural Networks: Sensitivity-informed Provable Pruning of Neural Networks. CoRR (2019)
Harry Lang, Cenk Baykal, Najib Abu Samra, Tony Tannous, Dan Feldman, Daniela Rus
Deterministic Coresets for Stochastic Matrices with Applications to Scalable Sparse PageRank. TAMC (2019)
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
An intelligent interface for integrating climate, hydrology, agriculture, and socioeconomic models. IUI Companion (2019)
Jeryes Danial, Dan Feldman, Ariel Hutterer
Position Estimation of Moving Objects: Practical Provable Approximation. IEEE Robotics Autom. Lett. 4 (2) (2019)
Adi Akavia, Dan Feldman, Hayim Shaul
Secure Data Retrieval on the Cloud: Homomorphic Encryption meets Coresets. IACR Trans. Cryptogr. Hardw. Embed. Syst. 2019 (2) (2019)
Yair Marom, Dan Feldman
k-Means Clustering of Lines for Big Data. CoRR (2019)
Alaa Maalouf, Ibrahim Jubran, Dan Feldman
Fast and Accurate Least-Mean-Squares Solvers. CoRR (2019)
Alaa Maalouf, Ibrahim Jubran, Dan Feldman
Fast and Accurate Least-Mean-Squares Solvers. NeurIPS (2019)
Alaa Maalouf, Adiel Statman, Dan Feldman
Tight Sensitivity Bounds For Smaller Coresets. CoRR (2019)
Elad Tolochinsky, Dan Feldman
Coresets For Monotonic Functions with Applications to Deep Learning. CoRR (2018)
Cenk Baykal, Lucas Liebenwein, Igor Gilitschenski, Dan Feldman, Daniela Rus
Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds. CoRR (2018)
Adi Akavia, Dan Feldman, Hayim Shaul
Secure Data Retrieval On The Cloud Homomorphic Encryption Meets Coresets. IACR Cryptol. ePrint Arch. 2018 (2018)
Hayim Shaul, Dan Feldman, Daniela Rus
Scalable Secure Computation of Statistical Functions with Applications to k-Nearest Neighbors. CoRR (2018)
Dan Feldman, Melanie Schmidt, Christian Sohler
Turning Big data into tiny data: Constant-size coresets for k-means, PCA and projective clustering. CoRR (2018)
Ibrahim Jubran, Dan Feldman
Minimizing Sum of Non-Convex but Piecewise log-Lipschitz Functions using Coresets. CoRR (2018)
Adi Akavia, Dan Feldman, Hayim Shaul
Secure Search on Encrypted Data via Multi-Ring Sketch. CCS (2018)
Adi Akavia, Dan Feldman, Hayim Shaul
Secure Search via Multi-Ring Fully Homomorphic Encryption. IACR Cryptol. ePrint Arch. 2018 (2018)
Dror Epstein, Dan Feldman
Quadcopter Tracks Quadcopter via Real-Time Shape Fitting. IEEE Robotics Autom. Lett. 3 (1) (2018)
Dan Feldman, Chongyuan Xiang, Ruihao Zhu, Daniela Rus
Coresets for differentially private k-means clustering and applications to privacy in mobile sensor networks. IPSN (2017)
Dan Feldman, Sedat Ozer, Daniela Rus
Coresets for Vector Summarization with Applications to Network Graphs. ICML (2017)
Mario Lucic, Matthew Faulkner, Andreas Krause, Dan Feldman
Training Gaussian Mixture Models at Scale via Coresets. J. Mach. Learn. Res. 18 (2017)
Adi Akavia, Dan Feldman, Hayim Shaul
Secure Search on the Cloud via Coresets and Sketches. CoRR (2017)
Dan Feldman, Sedat Ozer, Daniela Rus
Coresets for Vector Summarization with Applications to Network Graphs. CoRR (2017)
Weiwei Duan, Yao-Yi Chiang, Craig A. Knoblock, Vinil Jain, Dan Feldman, Johannes H. Uhl, Stefan Leyk
Automatic alignment of geographic features in contemporary vector data and historical maps. GeoAI@SIGSPATIAL (2017)
Vladimir Braverman, Dan Feldman, Harry Lang
New Frameworks for Offline and Streaming Coreset Constructions. CoRR (2016)
Artem Barger, Dan Feldman
-Means for Streaming and Distributed Big Sparse Data. SDM (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Dan Feldman