Agnostic Learning vs. Prior Knowledge Challenge (2008)
Guyon, Isabelle, Saffari, Amir, Dror, Gideon, Cawley, Gavin
Abstract—“When everything fails, ask for additional domain knowledge” is the current motto of machine learning. Therefore, assessing the real added value of prior/domain knowledge is a both...
Analysis of the IJCNN 2007 Agnostic Learning vs. Prior Knowledge Challenge (2007)
Guyon, Isabelle, Saffari, Amir, Dror, Gideon, Cawley, Gavin
We organized a challenge for IJCNN 2007 to assess the added value of prior domain knowledge in machine learning. Most commercial data mining programs accept data pre-formatted in the form of a table,...
Alon Kaufman, Gideon Dror, Isaac Meilijson, Eytan Ruppin
The claim that genetic properties of neurons significantly influence their synaptic network structure is a common notion in neuroscience. The nematode Caenorhabditis elegans provides an exciting...
Assessing the number of ancestral alternatively spliced exons in the human genome (2006)
Sorek, Rotem, Dror, Gideon, Shamir, Ron
Abstract Background It is estimated that between 35% and 74% of all human genes undergo alternative splicing. However, as a gene that undergoes alternative splicing can have between one and dozens of...
Performance Prediction Challenge (2006)
Guyon, Isabelle, Saffari, Amir, Dror, Gideon, Buhmann, Joachim
A major challenge for machine learning algorithms in real world applications is to predict their performance. We have approached this question by organizing a challenge in performance prediction for...
Result Analysis of the NIPS 2003 Feature Selection Challenge (2004)
Guyon, Isabelle, Gunn, Steve, Ben-Hur, Asa, Dror, Gideon
The NIPS 2003 workshops included a feature selection competition organized by the authors. We provided participants with five datasets from different application domains and called for classification...
Learning Facial Attractiveness (2004)
In this work we study of the notion of "attractiveness" of faces in a machine-learning context. To this end, we collected human beauty ratings for datasets of facial images and used various...
Dynamic Proximity of Spatiotemporal Sequences (2004)
David Horn, Gideon Dror, Brigitte Quenet
Recurrent networks can generate spatiotemporal neural sequences of very large cycles, having an apparent random behavior. Nonetheless a proximity measure between these sequences may be defined...
Momentum Reconstruction and Triggering in the TALAS Detector (2000)
A neural network solution for a complicated experimental High Energy Physics problem is described. The method is used to reconstruct the momentum and charge of muons produced in collisions of...
Vertex Reconstructing Neural Network at the ZEUS Central Tracking Detector (2000)
An unconventional solution for finding the location of event creation is presented. It is based on two feed-forward neural networks with fixed architecture, whose parameters are chosen so as to reach...
Momentum reconstruction of particles in the forward muon trigger system of the ATLAS detector (1999)
Gideon Dror, Erez Etzion, David Horn
We devise a feed forward neural network which identifies the charge and momentum of muons in the forward trigger system of the ATLAS detector. We use second order learning methods to train the...
Vertex Identification in High Energy Physics Experiments (1999)
Gideon Dror, Halina Abramowicz, David Horn
In High Energy Physics experiments one has to sort through a high flux of events, at a rate of tens of MHz, and select the few that are of interest. One of the key factors in making this decision is...
Vertex Identification in High Energy Physics Experiments (1998)
Gideon Dror, Halina Abramowicz, David Horn
In High Energy Physics experiments one has to sort through a high flux of events, at a rate of tens of MHz, and select the few that are of interest. In making this decision one relies on the location...
Gene Expression of Caenorhabditis elegans Neurons Carries Information on Their Synaptic Connectivity
Kaufman, Alon, Dror, Gideon, Meilijson, Isaac, Ruppin, Eytan
The claim that genetic properties of neurons significantly influence their synaptic network structure is a common notion in neuroscience. The nematode Caenorhabditis elegans provides an exciting...