feldmanDan Feldman's Home Page

Director of the Robotics and Big Data Lab,
and
Senior Lecturer at the Computer Science Department

University of Haifa,

e-mail: dannyf.post@gmail.com

 


 

 

 

 

 

 

 

Check out the new Robotics & Big Data Lab page of my group !

Current research

Machine learning of Big Data, Internet of Things, Swarm robotics, and 3D-cameras.

I am especially excited about reducing the gap between theoretical and practical algorithms, using my experience in the industry and academy.

Main technique

Core-sets: Semantic compression of data sets into small sets that provably approximate the original data for a given problem. Using merge-reduce (e.g. Spark) the small sets can then be used for solving hard machine learning problems in parallel (on the cloud/network), real-time and on Big streaming data.

Publications and Slides

Introduction to Coresets: Videos from the Machine Learning Summer School 2014 at CMU

Lecture 1, 2+3, 4, 5

 

Dimensionality Reduction of Massive Sparse Datasets Using Coresets,

with Mikhali Volkov, Daniela Rus, (supplementary material)
Proc. 29th Conference on Neural Information Processing Systems (NIPS) 2016, to appear

 

k-Means for Streaming and Distributed Big Sparse Data,

with Artem Barger.
Proceedings of the 2016 SIAM International Conference on Data Mining (SDM'16).

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

with Soliman Nasser and Ibrahim Jobran. [Video]

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

with Andrew Sugaya, Cynthia Sung, and Daniela Rus,

ACM Transactions on Sensor Networks, Volume I, Issue 4 (2015).

Coresets for Visual Summarization with Applications to Loop Closure

with G. Rossman, Dan Feldman, Mikhail V. Volkov, and, D. RusĢ,

IEEE International Conference on Robotics and Automation (ICRA) 2015.

Fleye on the Car: Big data Meets the Internet of Things,

with Soliman Nasser, Andrew Barry, Marek Doniec, Guy Peled, Guy Rosman
Daniela Rus, and Mikhail Volkov.

ACM/IEEE Conf. on Information Processing in Sensor Networks (IPSN) 2015.

More Constraints, Smaller Coresets: Constrained Matrix Approximation of Sparse Big Data,  
with Tamir Tassa,
21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) 2015

Coresets for k-segmentation of streaming data
with G. Rosman, M. Volkov, J.W. Fisher III, and D. Rus
Proc. 27th Conference on Neural Information Processing Systems (NIPS) 2014

Smallest enclosing ball for probabilistic data,
with Alexander Munteanu, and Christian Sohler
The 30th Annual Symposium on Computational Geometry (SoCG) 2014,

Visual Precis Generation using Coresets,
with Rohan Paul, Daniela Rus and Paul Newman.
IEEE International Conference on Robotics and Automation (ICRA) 2014,

Big Data for Robots: Online HMM Coresets for Sensor Streams,
with Cathy Wu, Brian Julian, Cynthia Sung, and Daniela Rus.
IEEE International Conference on Robotics and Automation (ICRA) 2013

K-Robots Clustering of Moving Sensors Using Coresets, [Slides]
with Stephanie Gil and Daniela Rus.
IEEE International Conference on Robotics and Automation (ICRA) 2013

iDiary: From GPS Signals to a Text-Searchable Diary,
with Andrew Sugaya, Cynthia Sung, and Daniela Rus.
The 11th ACM Conference on Embedded Networked Sensor System (SenSys) 2013

Learning Big (Image) Data via Coresets for Dictionaries,
with Micha Feigin, and Nir Sochen.

The International Biomedical and Astronomical Signal Processing (BASP) Frontiers workshop, 2013, selected to
The  Journal of Mathematical Imaging and Vision (JMIV)

The Single Pixel GIS:
Learning Big Data Signals from Tiny Coresets,
[Slides]
with Cynthia Sung and Daniela Rus.
Proc. 20th ACM  International Conference on Advances in Geographic Information Systems (SIGSPATIAL GIS) 2012

Turning Big Data into Tiny Data:
Constant-size Coresets for k-means, PCA and Projective Clustering,

with Melanie Schmidt and Christian Sohler.
Proc. 24th Annu. ACM  Symp. on Discrete Algorithms (SODA) 2013, to appear,
and in the 4th Workshop on Massive Data Algorithms (MASSIVE) 2012

Trajectory Clustering for Motion Prediction, [Slides]
with Cynthia Sung and Daniela Rus.

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROSí12)

Communication Coverage for Independently Moving Robots, [Slides]

with Stephanie Gil and Daniela Rus.


IEEE/RSJ International Conference on Intelligent Robots and Systems (IROSí12)

An Effective Coreset Compression Algorithm for Large Scale Sensor Networks, [Slides]

with Andrew Sugaya and Daniela Rus.

Proc. 11th ACM/IEEE Conf. on Information Processing in Sensor Networks (IPSN) 2012

Data Reduction for Weighted and Outlier-resistant Clustering [Slides]

with Leonard J. Schulman.

Proc. 23th Annu. ACM  Symp. on Discrete Algorithms (SODA) 2012

Scalable Training of Mixture Models via Coresets, [Slides]

with Andreas Krause and Matthew Faulkner.

Proc. 25th Conference on Neural Information Processing Systems (NIPS) 2011

A Unified Framework for Approximating and Clustering Data,

with Michael Langberg. 

Proc. 43st Annu. ACM Symposium on Theory of Computing (STOC 2011) [Fuller Version]

From High Definition Image to Low Space Optimization,

with Micha Feigin and Nir Sochen

Scale Space and Variational Methods in Computer Vision (SSVM) 2011

Coresets and Sketches for High Dimensional Subspace Approximation Problems,

with Morteza Monemizadeh, Christian Sohler and David Woodruf

Proc. 21th Annu. ACM  Symp. on Discrete Algorithms (SODA) 2010

 

Private Coresets, [Slides]

with Amos Fiat, Haim Kaplan and Kobbi Nissim.

Proc. 41st Annu. ACM Symposium on Theory of Computing (STOC) 2009

A PTAS for k-Means Clustering Based on Weak Coresets,

with Morteza Monemizadeh and Christian Sohler,

Proc. 23th Annu. ACM Symposium on Computational Geometry (SoCG) 2007

Bi-criteria Linear-time Approximations for Generalized k-Mean/Median/Center,

with Amos Fiat, Danny Segev and Micha Sharir,

Proc. 23th Annu. ACM Symposium on Computational Geometry (SoCG) 2007

Coresets for Weighted Facilities and Their Applications, [Slides]

with Amos Fiat and Micha Sharir,

Proc. 47th Annu. IEEE Symposium on Foundations of Computer Science (FOCS) 2006

Thesis

       Coresets and their applications

Under the supervision of Amos Fiat and Micha Sharir

      Ph.D Thesis, December 2010

   Algorithms for Finding the Optimal k-Line Mean,
under the supervision of Amos Fiat,

      M.Sc Thesis, March 2004