Daniel Keren's Publications

Journal Papers:

  • Improving Image Resolution Using Sub-Pixel Motion
    S. Peleg, D. Keren and L. Schweitzer, Pattern Recognition Letters, 5, 223-226, 1987.

  • Probabilistic Analysis of Regularization
    D. Keren and M. Werman, IEEE Transactions on Pattern Analysis and Machine Intelligence, 15, 982-995, 1993.

  • Describing Complicated Objects by Implicit Polynomials
    D. Keren, D. Cooper and J. Subrahmonia, IEEE Transactions on Pattern Analysis and Machine Intelligence, 16, 38-53, 1994.

  • Using Symbolic Computation to Find Algebraic Invariants
    D. Keren, IEEE Transactions on Pattern Analysis and Machine Intelligence, 16, 1143-1149, 1994.

  • J. Subrahmonia, D. Keren and D. Cooper: "An Algebraic and Bayesian Technology for Object Recognition",
    Journal of Applied Statistics, 21, 165-205, 1994.

  • Data-Driven Priors for Hyperparameters in Regularization
    D. Keren and M. Werman, Maximum Entropy and Bayesian Methods, 79, 77-85, 1995

  • Practical Reliable Bayesian Recognition of 2D and 3D Objects Using Implicit Polynomials and Algebraic Invariants
    J. Subrahmonia, D. Cooper and D. Keren, IEEE Transactions on Pattern Analysis and Machine Intelligence, 18, 505-519, 1996.

  • Tight Fitting of Convex Polyhedral Shapes
    C. Gotsman and D. Keren, International Journal of Shape Modeling, 4(3-4):111-126, 1998.

  • Denoising Color Images Using Regularization and Correlation Terms
    D. Keren and A. Gotlib, Journal of Visual Communication and Image Representation, 9, 352-365, 1998.

  • Restoring Subsampled Color Images
    D. Keren and M. Osadchy, Machine Vision and Applications, 11, 197-202, 1999.

  • Fitting Curves and Surfaces with Constrained Implicit Polynomials
    D. Keren and C. Gotsman, IEEE Transactions on Pattern Analysis and Machine Intelligence, 21, 31-41, 1999.

  • A Full Bayesian Approach to Curve and Surface Reconstruction
    D. Keren and M. Werman, Journal of Mathematical Imaging and Vision, 11.1 27-44, 1999.

  • Recognizing 3D Objects Using Tactile Sensing and Curve Invariants
    D. Keren, E. Rivlin, I. Shimshoni and I. Weiss, Journal of Mathematical Imaging and Vision, 12.1, 5-23, 2000

  • Antifaces: A Novel, Fast Method for Image Detection
    D. Keren, M. Osadchy and C. Gotsman, IEEE Transactions on Pattern Analysis and Machine Intelligence, 23.7, 747-761, 2001.

  • A Bayesian Method for Fitting Parametric and Non-Parametric Models to Noisy Data
    M. Werman and D. Keren, IEEE Transactions on Pattern Analysis and Machine Intelligence, 23.5, 528-534, 2001.

  • All Points Considered: A Maximum Likelihood Method for Motion Recovery
    D. Keren, I, Shimshoni, L. Goshen and M. Werman, Theoretical Foundations of Computer Vision, 72-85, 2002.

  • Recognizing Image Style and Activities in Video Using Local Features and Naive Bayes
    D. Keren, Pattern Recognition Letters, 24.16 2913-2922, 2003.

  • Bayesian-Based Motion Estimation with Flat Priors,
    D. Keren, Bayesian Inference and Maximum Entropy Methods, AIP Vol. 735, 153-160, 2004.

  • Efficient Detection Under Varying Illumination Conditions and Image Plane Rotations
    M. Osadchy and D. Keren, Computer Vision and Image Understanding, 93, 245-259, 2004.

  • A Rejection-Based Method for Event Detection in Video
    M. Osadchy and D. Keren, IEEE Transactions on Circuits and Systems for Video Technology, 14.4 534-541, 2004.

  • Topologically Faithful Fitting of Simple Closed Curves
    D. Keren, IEEE Transactions on Pattern Analysis and Machine Intelligence, 26.1, 118-123, 2004.

  • Motion Recovery by Integrating over the Joint Image Manifold
    L. Goshen, I. Shimshoni, P. Anandan and D. Keren, International Journal of Computer Vision, Vol. 65.3, 131-145, 2005.

  • Hierarchical Decision Tree Induction in Distributed Genomic Databases
    A. Bar-Or, D. Keren, A. Schuster and R. Wolff, IEEE Transactions
    on Knowledge and Data Engineering, 17.8, 1138-1151, 2005.
    (This paper has an appendix with proofs of some lemmas).

  • Applying Reproducing Kernels to the Evaluation and Approximation of the
    Simple and Time-Dependent Imaginary Time Harmonic Oscillator Path Integrals
    D. Keren, Applicable Analysis Vol. 85, Nos. 6-7, 793-810, 2006.

  • "Hereditary Family Signature of Facial Expression", G. Peleg, G. Katzir, O. Peleg, M. Kamara, L. Brodsky,
    H. Helor, D. Keren, E. Nevo, Proceedings of the National Academy of Sciences (PNAS), Vol. 103, No. 43,
    15921-15926, 2006.
    Paper on PNAS Website.

  • A Geometric Approach to Monitoring Threshold Functions over Distributed Data Streams
    I. Sharfman, A. Schuster, D. Keren, ACM Transactions on Database Systems,
    Vol. 32, No. 4, Article 23, pages 23:1 - 23:29, 2007.

  • A New Measure of Symmetry and its Application to Classification of Bifurcating Structures.
    D. Milner, S. Raz, H. Hel-Or, D. Keren, E. Nevo. Pattern Recognition 40, 2237-2250, 2007.

  • A Probabilistic Method for Point Matching in the Presence of Noise and Degeneracy ,
    D. Keren, Journal of Mathematical Imaging and Vision, Volume 33, Number 3, 338-346, 2009.

  • 3D Surface Reconstruction Using a Generalized Distance Function
    R. Poranne, C. Gotsman and D. Keren, Computer Graphics Forum, 29.8, 2479--2491, 2010.

  • Distributed Threshold Querying of General Functions by a Difference of Monotonic Representation
    G. Sagy, D. Keren, I. Sharfman, and A. Schuster, Proceedings of the VLDB Endowment, 4(2), 46-57, 2010.

  • Applying Property Testing to an Image Partitioning Problem
    I. Kleiner, D. Keren, I. Newman, O. Ben-Zwi, IEEE Transactions on Pattern Analysis and Machine Intelligence, 33.2, p. 256-265, 2011.

  • Top-k vectorial aggregation queries in a distributed environment,
    G. Sagy, I. Sharfman, D. Keren, A. Schuster, Journal of Parallel and Distributed Computing 71.2, 302-315, 2011.

  • On the uncertainty in the regularized solution
    D. Keren and I. Nissenboim, Journal of Physics A: Mathematical and Theoretical 44(2), 2011.

  • Shape Sensitive Geometric Monitoring
    D. Keren, I. Sharfman, A. Schuster, and A. Livne, IEEE Transactions on Knowledge and Data Engineering, 24(8): 1520-1535, 2012.

  • A Probabilistic Approach to Pattern Matching in the Continuous Domain
    D. Keren, M. Werman, J. Feinberg, IEEE Transactions on Pattern Analysis and Machine Intelligence, 34(10):1873-1885, 2012.

  • Sketch-based Geometric Monitoring of Distributed Stream Queries.
    M. Garofalakis, D. Keren, V. Samoladas, PVLDB 2013.

  • Planar Shape Interpolation with Bounded Distortion.
    R. Chen, O. Weber, D. Keren, M. Ben-Chen, ACM Transactions on Graphics Vol.32, No. 4 (SIGGRAPH 2013).
    Renjie's SIGGRAPH presentation (powerpoint).

  • Geometric Monitoring of Heterogeneous Streams
    D. Keren, G. Sagy, A. Abboud, D. Ben-David, A. Schuster, I. Sharfman, A. Deligiannakis. IEEE TKDE 2014, to appear.
    Long Version, with Proofs of the NP-hardness theorems (Section 7).

  • Clustering for Monitoring Distributed Data Streams (PCA 2014)
    M. Barouti, D. Keren, J. Kogan, Y. Malinovsky. Partitional Clustering Algorithms, 2014.

  • Monitoring Distributed Streams using Convex Decompositions
    A. Lazerson, I. Sharfman, D. Keren, A. Schuster, M. Garofalakis, V. Samoladas. VLDB 2015.

  • Recognition Using Hybrid Classifiers
    M. Osadchy, D. Keren, D. Raviv. IEEE Transactions on Pattern Analysis and Machine Intelligence, VOL. 38, NO. 4, 2016.

  • Scalable Approximate Query Tracking over Highly Distributed Data Streams
    with Tunable Accuracy Guarantees
    N. Giatrakos , A. Deligiannakis , M. Garofalakis , D. Keren , V. Samoladas.
    Information Systems 2018, to appear.

    Conference Papers:

  • Image Sequence Enhancement Using Sub-Pixel Displacement
    D. Keren, S. Peleg and R. Brada, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR),
    742-746, 1988.

  • Variations on Regularization
    D. Keren and M. Werman, IEEE International Conference on Pattern Recognition (ICPR), 93-98, 1990.

  • Segmentation by Minimal Length Encoding
    D. Keren, R. Marcus, M. Werman and S. Peleg, IEEE International Conference on Pattern Recognition (ICPR), 681-683, 1990.

  • D. Keren, J. Subrahmonia, D. Cooper and G. Taubin, "Bounded and Unbounded Implicit Polynomial Curves and Surfaces,
    Mahalanobis Distances, and Geometric Invariants for Robust Object Recognition", Proceedings of DARPA Image Understanding
    Workshop, 769-777, 1992.

  • Robust Object Recognition Based on Implicit Algebraic Curves and Surfaces
    D. Keren, J. Subrahmonia and D. Cooper, IEEE International Conference on Pattern Recognition (ICPR), 791-794, 1992.

  • J. Subrahmonia, D. Keren and D. Cooper, "Bayesian Methods for the Use of Implicit Polynomials and Algebraic Invariants in Practical
    Computer Vision", Proc. SPIE Vol. 1830, Curves and Surfaces in Computer Vision and Graphics III, 104-117, 1992.

  • Computing Correspondence Based on Regions and Invariants Without Feature Extraction and Segmentation
    C. Lee, D. Cooper and D. Keren,IEEE International Conference on Computer Vision and Pattern Recognition (ICPR), 655-656, 1993.

  • Recognizing Mice, Vegetables and Hand Printed Characters Based on Implicit Polynomials, Invariants and Bayesian Methods
    J. Subrahmonia, D. Cooper and D. Keren, International Conference on Computer Vision (ICCV) 320-324, 1993.

  • D. Keren, J. Subrahmonia and D. Cooper, "Integrating Algebraic Curves and Surfaces, Algebraic Invariants and Bayesian Methods
    for 2D and 3D Object Recognition", Applications of Invariance in Computer Vision, 493-510, 1993.

  • A Bayesian Framework for Regularization
    D. Keren and M. Werman, IEEE International Conference on Pattern Recognition (ICPR), 72-76, 1994.

  • M. BarZohar, D. Keren and D. Cooper, "Recognizing Groups of Curves Based on New Affine Mutual Geometric,
    Invariants, with Applications to Recognizing Intersecting Roads in Aerial Images", IEEE International Conference
    on Pattern Recognition (ICPR), 205-209, 1994.

  • Using Color Correlation To Improve Restoration of Color Images
    D. Keren, A. Gotlib and H. Hel-Or, International Workshop on Image and Signal Processing, 603-607, 1996.

  • New Approach to the Arc Length Parameterization Problem
    Y. Gil and D. Keren, Spring Conference on Computer Graphics, 27-35, 1997.

  • Recognizing Surfaces Using Curve Invariants and Differential Properties of Curves and Surfaces
    D. Keren, I. Shimshoni, E. Rivlin and I. Weiss, IEEE Conference on Robotics and Automation (ICRA), 3375-3381, 1998.

  • Recognizing Surfaces from 3D Curves
    D. Keren, E. Rivlin, I. Shimshoni and I. Weiss, International Conference on Image Processing (ICIP) 3, 551-555, 1998.

  • A Novel Bayesian Method for Fitting Parametric and Non-Parametric Models to Noisy Data
    M. Werman and D. Keren, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), II:552-558, 1999.

  • Anti-Faces for Detection
    D. Keren, M. Osadchy, and C. Gotsman, Sixth European Conference on Computer Vision (ECCV), 134-148, 2000.

  • Image Detection under varying illumination and pose
    M. Osadchy and D. Keren, IEEE International Conference on Computer Vision (ICCV), II:668-673, 2001.

  • Anti-Sequences: Event Detection by Frame Stacking
    M. Osadchy and D. Keren and Y. Gal, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), II:46-51, 2001.

  • Painter Identification Using Local Features and Naive Bayes
    D. Keren, International Conference on Pattern Recognition (ICPR), II 474- 477, 2002.

  • Recovery of Epipolar Geometry as a Manifold Fitting Problem
    L. Goshen, I. Shimshoni, P. Anandan and D. Keren, IEEE 9th International Conference on Computer Vision (ICCV), 1321-1328, 2003.

  • Hierarchical Decision Tree Induction in Distributed Genomic Databases
    A. Bar-Or, A. Schuster, R. Wolff and D. Keren, Conference on Data Mining and the Grid, 2004.

  • Decision Tree Induction in High Dimensional, Hierarchically Distributed Databases.
    A. Bar-Or, A. Schuster, R. Wolff and D. Keren, SIAM International Conference on Data Mining, 2005.

  • Analyzing Symmetry in Biological Systems
    D. Milner, H. Hel-Or, D. Keren, S. Raz, E. Nevo, International Conference on Image Processing (ICIP) 2005, 361-364.

  • Incorporating the Boltzmann Prior in Object Detection Using SVM.
    M. Osadchy and D. Keren, IEEE International Conference on Computer Vision and Pattern Recognition 2006 (CVPR06).

  • A Geometric Approach to Monitoring Threshold Functions Over Distributed Data Streams
    I. Sharfman, A. Schuster and D. Keren, SIGMOD06 (honorable mention for best paper award).

  • Spline-Based Robot Navigation
    E. Magid, D. Keren, E. Rivlin, and I. Yavneh, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS06), 2296-2301.

  • Aggregate Threshold Queries in Sensor Networks
    I. Sharfman, A. Schuster, and D. Keren, IEEE International Parallel & Distributed Processing Symposium 2007 (IPDPS 2007).

  • Multi-Camera Topology Recovery from Coherent Motion
    Z. Mandel, I. Shimshoni, and D. Keren, ACM/IEEE International Conference on Distributed Smart Cameras (ICDSC-07).

  • Shape Sensitive Geometric Monitoring
    I. Sharfman, A. Schuster, and D. Keren, Principles of Database Systems (PODS) 2008.

  • Applying Two-Pixel Features to Face Detection
    I. Nissenboim, D. Keren, and M. Werman. IEEE International Conference on Signal Image Technology and Internet Based Systems, 2008.

  • Distributed Threshold Querying of General Functions by a Difference of Monotonic Representation
    G. Sagy, D. Keren, I. Sharfman, and A. Schuster, VLDB 2011.

  • Monitoring Distributed, Dynamic Systems (keynote lecture). D. Keren, SYSTOR 2011.

  • Hybrid Classifiers for Object Classification with a Rich Background
    M. Osadchy, D. Keren, and B. Fadida-Specktor, ECCV 2012, V, 284-297.

  • Sketch-based Geometric Monitoring of Distributed Stream Queries.
    M. Garofalakis, D. Keren, and V. Samoladas, PVLDB 2013.

  • Communication efficient Outlier Detection for Scaleout Systems
    M. Gabel, D. Keren, and A. Schuster, BD3 Workshop, PVLDB 2013.

  • Communication Efficient Distributed Online Prediction using Dynamic Model Synchronizations
    M. Boley, M. Kamp, D. Keren, A. Schuster, and I. Sharfman. BD3 Workshop, PVLDB 2013.

  • Safe-Zones for Monitoring Distributed Streams.
    D. Keren, G. Sagy, A. Abboud, D. Ben-David, I. Sharfman, and A. Schuster. BD3 Workshop, PVLDB 2013.

  • Planar Shape Interpolation with Bounded Distortion.
    R. Chen, O. Weber, D. Keren, M. Ben-Chen, ACM Transactions on Graphics Vol.32, No. 4 (SIGGRAPH 2013).
    Renjie's SIGGRAPH presentation (powerpoint).

  • Invited Talk, by Assaf Schuster, ICAA 2014

  • Privacy-Preserving Distributed Stream Monitoring.
    A. Friedman, I. Sharfman, D. Keren, A. Schuster. NDSS 2014.

  • Communication-Efficient Distributed Variance Monitoring and Outlier Detection for Multivariate Time Series.
    M. Gabel, A. Schuster, D. Keren. IPDPS 2014.

  • Adaptive Clustering for Monitoring Distributed Data Streams.
    M. Barouti, D. Keren, J. Kogan, Y. Malinovsky. SDM-EDA 2014.

  • Monitoring Distributed Data Streams Through Node Clustering.
    M. Barouti, D. Keren, J. Kogan, Y. Malinovsky. MLDM 2014.

  • Communication-Efficient Distributed Online Prediction by Dynamic Model Synchronization (ECML/PKDD14).
    M. Kamp, M. Boley, D. Keren, A. Schuster, I. Sharfman. The European Conference on Machine Learning and
    Principles and Practice of Knowledge Discovery in Databases, 2014.

  • Adaptive Communication Bounds for Distributed Online Learning (OPT2014 Workshop, NIPS 2014)
    M. Kamp, M. Boley, M. Mock, D. Keren, A. Schuster, I. Sharfman. Optimization for Machine Learning Workshop, NIPS 2014.

  • Latent Fault Detection With Unbalanced Workloads.
    M. Gabel, K. Sato, D. Keren, S. Matsuoka, A. Schuster. EPForDM Workshop, EDBT 2015.

  • Monitoring Least Squares Models of Distributed Streams
    M. Gabel, D. Keren, A. Schuster. KDD 2015.

  • K-hyperplane Hinge-Minimax Classifier.
    M. Osadchy, T. Hazan, D. Keren. ICML 2015.

  • Lightweight Monitoring of Distributed Streams
    A. Lazerson, D. Keren, A. Schuster. KDD 2016.

    Misc.

  • YNET article about painter identification project

  • MSNBC article about painter identification project