Publications


Identifying and predicting social lifestyles in people's trajectories by neural networks

E Ben Zion and B Lerner

EPJ Data Science, vol. 7(45), pp. 1-27, 2018.

Analyzing large-scale human mobility data: A survey of machine learning methods and applications

E Toch, B Lerner, E Ben-Zion, and I Ben-Gal

Knowledge and Information System, pp.1–23, March 2018.

Temporal modeling of ALS using longitudinal data and long-short term memory-based algorithm

A Nahon and B Lerner

European Symposium on Artificial Networks, Computational Intelligence and Machine Learning (ESANN2018), Bruges, Belgium, 2018.

Stratifying ALS patients by disease progression patterns

J Gordon and B Lerner

28th International Symposium on ALS/MND, Boston, USA, 2017

Modeling of ALS progression using a temporal machine-learning algorithm

            J Gordon, A Nahon, and B Lerner

28th International Symposium on ALS/MND, Boston, USA, 2017

Dynamic weighting of old and new information for predicting future condition of ALS patients

A Nahon and B Lerner

28th International Symposium on ALS/MND, Boston, USA, 2017.

Learning human behaviors and lifestyle by capturing temporal relations in mobility patterns

E Ben Zion and B Lerner

European Symposium on Artificial Networks, Computational Intelligence and Machine Learning (ESANN2017), Bruges, Belgium, 2017

(available code)

Learning latent variable models by pairwise cluster comparison: Part I Theory and overview

            N Asbeh and B Lerner

Journal of Machine Learning Research (JMLR), vol. 17(224), pp. 1–52, 2016. (available code and data sets)

Learning latent variable models by pairwise cluster comparison: Part II Algorithm and evaluation

            N Asbeh and B Lerner

Journal of Machine Learning Research (JMLR), vol. 17(233), pp. 1–45, 2016. (available code and data sets)

Human mobility-pattern discovery and next-place prediction from GPS data

F Khoroshevsky and B Lerner

In: Schwenker F., Scherer S. (eds) (2017) Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction. MPRSS 2016. Lecture Notes in Computer Science, vol 10183. Springer, Cham

(23rd International Conference on Pattern Recognition, ICPR, Cancun, Mexico, 2016. The 4th International Workshop on Multimodal Pattern Recognition of Social Signals in Human Computer Interaction, MPRSS)

Exposing and modeling underlying mechanisms in ALS with machine learning

J Gordon and B Lerner

23rd International Conference on Pattern Recognition (ICPR), Cancun, Mexico, 2016

Learning a Bayesian network classifier by jointly maximizing accuracy and information

            D Halbersberg and B Lerner

22nd European Conference on Artificial Intelligence (ECAI), The Hague, Holland, 2016

Disease state prediction, knowledge representation, and heterogeneity decomposition for ALS

J Gordon and B Lerner

Uncertainty in Artificial Intelligence (UAI) Workshop on Machine Learning for Health: Learning to Understand Human Disease, Jersey City, NJ, 2016.

Insights into amyotrophic lateral sclerosis from a machine learning perspective

J Gordon and B Lerner

14th European Network for the Cure of ALS (ENCALS) Meeting, Milan, Italy, 2016

Pairwise cluster comparison for learning latent variable models

N Asbeh and B Lerner

Uncertainty in Artificial Intelligence (UAI) Workshop on Causation: Foundation to Application, Jersey City, NJ, 2016.

Adaptive thresholding in structure learning of a Bayesian network

            B Lerner, M Afek and R Bojmel

23rd International Joint Conference on Artificial Intelligence (IJCAI2013), Beijing, pp. 1458-1464, 2013.

Learning latent variable models by pairwise cluster comparison

            N Asbeh and B Lerner

            Fourth Asian Conference on Machine Learning (ACML2012), Singapore

JMLR Workshop & Conference Proceedings, vol. 25, pp. 33-48, 2012. (available code)

Learning Bayesian network classifiers by risk minimization

R Kelner and B Lerner

International Journal of Approximate Reasoning, vol. 53, pp. 248-272, 2012. (available code)

Machine learning in predicting and explaining failure using class-imbalance FAB data

H Belyavin and B Lerner

21st Inter. Conf. on Production Research (ICPR21), Stuttgart, Germany, 2011.

Trading between classification accuracy and information in production

M Wienreb, B Lerner and G Rabinowitz

21st Inter. Conf. on Production Research (ICPR21), Stuttgart, Germany, 2011.

Structure-based identification of catalytic residues

R Yahalom, D Reshef, A Wiener, S Frankel, N Kalisman, B Lerner and C Keasar

Proteins: Structure, Function, and Bioinformatics, vol. 79, pp. 1952-1963, 2011.

Cycle-time key factor identification and prediction in semiconductor manufacturing using machine learning and data mining

Y Meidan, B Lerner, G Rabinowitz and M Hassoun

IEEE Transactions on Semiconductor Manufacturing, vol. 24, pp. 237-248, 2011.

Investigation of the K2 algorithm in learning Bayesian network classifiers

B Lerner and R Malka

Applied Artificial Intelligence, vol. 25, pp. 74-96, 2011.

Bayesian Network Structure Learning by Recursive Autonomy Identification

R Yehezkel and B Lerner

The Journal of Machine Learning Research, vol. 10, pp. 1527-1570, 2009. (available code)

Advanced Developments and Applications of the Fuzzy ARTMAP Neural Network in Pattern Classification

B Lerner and H Guterman

Computational Intelligence Paradigms - Innovative Applications, (eds.) L C Jain and Sato, Springer-Verlag, pp. 77-107, 2008.

The Bayesian ARTMAP

B Vigdor and B Lerner

IEEE Transactions on Neural Networks, vol. 18(6), pp. 1628-1644, 2007. (available code)

Localization and Magnetic Moment Estimation of a Ferromagnetic Target by Simmulated Annealing

A Sheinker, B Lerner, N Salomonski, B Ginzburg, L Frumkis and BZ Kaplan

Measurement Science and Technology, vol. 18, pp. 3451-3457, 2007.

Segmentation and Classification of Dot and Non-Dot-Like Fluorescence in-situ Hybridization Signals for Automated Detection of Cytogenetic Abnormalities

B Lerner, L Koushnir and J Yeshaya

IEEE Transactions on Information Technology in Biomedicine, vol. 11(4), pp. 443-449, 2007.

On the Classification of a Small Imbalanced Cytogenetic Image Database

B Lerner, J Yeshaya and L Koushnir

IEEE Transactions on Computational Biology & Bioinformatics, vol. 4(2), pp. 204-215, 2007.

Bayesian Class-Matched Multinet Classifier

Y Gurwicz and B Lerner

SSPR/SPR, ser. Lecture Notes in Computer Science, vol. 4109, pp. 145-153, 2006.

Bayesian Network Structure Learning by Recursive Autonomy Identification

R Yehezkel and B Lerner

SSPR/SPR, ser. Lecture Notes in Computer Science, vol. 4109, pp. 154-162, 2006.

Learning Bayesian Networks for Pattern Classification

B Lerner

Invited tutorial at the 18th International Conference on Pattern Recognition (ICPR2006), Hong-Kong, August 2006.

Accurate and Fast Off and Online Fuzzy ARTMAP-Based Image Classification With Application to Genetic Abnormality Diagnosis

B Vigdor and B Lerner

IEEE Transactions on Neural Networks, vol. 17(5), pp. 1288-1300, 2006.

Bayesian Network Classification using Spline-Approximated Kernel Density Estimation

Y Gurwicz and B Lerner

Pattern Recognition Letters, vol. 26(11), pp. 1761-1771, 2005.

Recursive Autonomy Identification for Bayesian Network Structure Learning

R Yehezkel and B Lerner

The 10th International Workshop on Artificial Intelligence & Statistics, AISTATS 2005, 6-8 January, 2005, Barbados, pages 429-436.

Support Vector Machine-based Image Classification for Genetic Syndrome Diagnosis

A David and B Lerner

Pattern Recognition Letters, vol. 26(8), pp. 1029-1038, 2005.

Classification of Fluorescence In-Situ Hybridization Images using Belief Networks

R Malka and B Lerner

Pattern Recognition Letters, vol. 25(16), pp. 1777-1785, 2004.

Bayesian Fluorescence in-situ Hybridization Signal Classification

B Lerner

Artificial Intelligence in Medicine, vol. 30(3), A special issue on Bayesian Models in Medicine, pp. 301-316, 2004.

Signal Discrimination Using a Support Vector Machine for Genetic Syndrome Diagnosis

A David and B Lerner

17th International Conference on Pattern Recognition (ICPR2004), 23-26 August, 2004, Cambridge, UK, Vol. 3, pp. 490-493.

Rapid Spline-based Kernel Density Estimation for Bayesian Networks

Y Gurwicz and B Lerner

17th International Conference on Pattern Recognition (ICPR2004), 23-26 August, 2004, Cambridge, UK, Vol. 3, pp. 700-703.

An Empirical Study of Fuzzy ARTMAP Applied to Cytogenetics

B Lerner and B Vigdor

23rd IEEE Convention of Electrical & Electronics Engineers in Israel, 6-7 September, 2004 (IEEEI2004), Tel-Aviv, Israel, pp. 301-304.

Belief Networks for Cytogenetic Image Categorization

B Lerner and R Malka

23rd IEEE Convention of Electrical & Electronics Engineers in Israel, 6-7 September, 2004 (IEEEI2004), Tel-Aviv, Israel, pp. 297-300.

Fluorescence In-Situ Hybridization Signal Discrimination in Medical Genetics

B Lerner

NNESMED 2003/CIMED 2003, Sheffield, pp. 29-34, 2003.

Introduction to Learning Probabilistic Graphical Models

B Lerner

Invited tutorial at Computational Intelligence: Methods & Applications (CIMA'2001), ICSC Academic Press, NL, 2001.

A Comparison of State-of-the-Art Classification Techniques with Application to Cytogenetics

B Lerner and N D Lawrence

Neural Computing & Applications, vol. 10(1), pp. 39-47, 2001.

Feature Representation and Signal Classification in Fluorescence in-situ Hybridization Image Analysis

B Lerner, W F Clocksin, S Dhanjal, M A Hult'en and C M Bishop

IEEE Transactions on Systems, Man and Cybernetics, Part A: Systems & Humans, vol. 31(6), pp. 655-665, 2001.

Automatic Signal Classification in Fluorescence in-situ Hybridization Images

B Lerner, W F Clocksin, S Dhanjal, M A Hult'en and C M Bishop

Cytometry, vol. 43(2), pp. 87-93, 2001.

GELFISH - Graphical Environment for Labelling Fluorescence in-situ Hybridization Images

B Lerner, S Dhanjal and M A Hult'en

Journal of Microscopy, vol. 203(3), pp. 258-268, 2001.

On the Initialisation of Sammon's Nonlinear Mapping

B Lerner, H Guterman, M Aladjem and I Dinstein

Pattern Analysis and Applications, 3(1), 61-68, 2000.

A Comparative Study of Neural Network based Feature Extraction Paradigms

B Lerner, H Guterman, M Aladjem and I Dinstein

Pattern Recognition Letters, vol. 20(1), pp. 7-14, 1999.

On Pattern Classification with Sammon's Nonlinear Mapping - An Experimental Study

B Lerner, H Guterman, M Aladjem, I Dinstein and Y Romem

Pattern Recognition, vol. 31(4), pp. 371-381, 1998.

Toward a Completely Automatic Neural Network based Human Chromosome Analysis

B Lerner

IEEE Transactions on Systems, Man and Cybernetics. Special issue on Artificial Neural Networks, vol. 28(4), Part B, pp. 544-552, 1998.

A Classification-Driven Partially Occluded Object Segmentation (CPOOS) Method with Application To Chromosome Analysis

B Lerner, H Guterman and I Dinstein

IEEE Transactions on Signal Processing, vol. 46(10), pp. 2841-2847, 1998.

Feature Extraction by Neural Network Nonlinear Mapping for Pattern Classification

B Lerner, H Guterman, M Aladjem, I Dinstein and Y Romem

The 13th International Conference on Pattern Recognition, ICPR13, Vienna, vol. 4, pp 320-324, 1996.

Human Chromosome Classification using Multilayer Perceptron Neural Network

B Lerner, H Guterman, I Dinstein and Y Romem

International Journal of Neural Systems, vol. 6(3), pp 359-370, 1995.

Medial Axis Transform based Features and a Neural Network for Human Chromosome Classification

B Lerner, H Guterman, I Dinstein and Y Romem

Pattern Recognition, vol. 28(11), pp 1673-1683, 1995.

Unsupervized Feature Extraction for Nonlinear Supervized Classification with Application to Chromosome Analysis

B Lerner, H Guterman, M Aladjem and I Dinstein

The International Conference on Neural Information Processing, ICONIP95, Beijing, vol. 1, pp 279-284, 1995.

Feature Selection and Learning Curves of a Multilayer Perceptron Chromosome Classifier

B Lerner, H Guterman, I Dinstein and Y Romem

The 12th International Conference on Pattern Recognition, 12ICPR, Jerusalem, vol. 2, pp 497-499, 1994.

Medial Axis Transform based Features and a Neural Network for Human Chromosome Classification

B Lerner, B Rosenberg, M Levinstein, H Guterman, I Dinstein and Y Romem

World Congress on Neural Networks, WCNN94, San Diego, vol. 3, pp 173-178, 1994.

Feature Selection and Chromosome Classification using a Multilayer Perceptron Neural Network

B Lerner, M Levinstein, B Rosenberg, H Guterman, I Dinstein and Y Romem

World Congress on Computational Intelligence, WCCI'94, Orlando, vol. 6, pp 3540-3545, 1994.

A Comparison of Multilayer Perceptron Neural Network and and Bayes Piecewise Classifier for Chromosome Classification

B Lerner, H Guterman, I Dinstein and Y Romem

World Congress on Computational Intelligence, WCCI'94, Orlando, vol. 6, pp 3472-3477, 1994.

Learning Curves and Optimization of a Multilayer Perceptron Neural Network for Chromosome Classification

B Lerner, H Guterman, I Dinstein and Y Romem

World Congress on Neural Networks, WCCN'94, San Diego, vol. 3, pp 248-253, 1994.

`Tailored' Neural Networks to Improve Image Classification

B Lerner, H Guterman, I Dinstein and Y Romem

World Congress on Neural Networks, WCNN94, San Diego, vol. 4. pp 327-331, 1994.

Classification of Human Chromosomes by Two-Dimensional Fourier Transform Components

B Lerner, H Guterman and I Dinstein

World Congress on Neural Networks, WCNN93, Portland, vol. 3, pp 793-796, 1993.

Multilayer Perceptron as a Human Chromosome Classifier

B Lerner, B Rosenberg, M Levinstein, H Guterman, I Dinstein and Y Romem

Artificial Intelligence, Computer Vision and Neural Networks, AICVNN'93, Kfar-Maccabiah, 207-216, 1993.

On Classification of Human Chromosomes

B Lerner, H Guterman and I Dinstein

Neural Networks for Learning, Recognition and Control, Boston University, 1992.

Two-Frequency Intensity Fluctuations in a Random Medium

B Lerner, M Tur and Z Azar

SPIE, vol. 1038, 569-576, Tel-Aviv, 1988.

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This page is maintained by Boaz Lerner (boaz@bgu.ac.il)