224 citations · 622 across the 13 of their papers we have counts for
13 papers
DeepChess: End-to-End Deep Neural Network for Automatic Learning in Chess
Eli David, Nathan S. Netanyahu, Lior Wolf
We present an end-to-end learning method for chess, relying on deep neural networks. Without any a priori knowledge, in particular without any knowledge regarding the rules of ches…
DeepPainter: Painter Classification Using Deep Convolutional Autoencoders
Eli David, Nathan S. Netanyahu
In this paper we describe the problem of painter classification, and propose a novel approach based on deep convolutional autoencoder neural networks. While previous approaches rel…
DNN-Buddies: A Deep Neural Network-Based Estimation Metric for the Jigsaw Puzzle Problem
Dror Sholomon, Eli David, Nathan S. Netanyahu
This paper introduces the first deep neural network-based estimation metric for the jigsaw puzzle problem. Given two puzzle piece edges, the neural network predicts whether or not…
DeepSign: Deep Learning for Automatic Malware Signature Generation and Classification
Eli David, Nathan S. Netanyahu
This paper presents a novel deep learning based method for automatic malware signature generation and classification. The method uses a deep belief network (DBN), implemented with…
Genetic Algorithms for Evolving Computer Chess Programs
Eli David, H. Jaap van den Herik, Moshe Koppel +1
This paper demonstrates the use of genetic algorithms for evolving: 1) a grandmaster-level evaluation function, and 2) a search mechanism for a chess program, the parameter values…
Genetic Algorithms for Evolving Deep Neural Networks
Eli David, Iddo Greental
In recent years, deep learning methods applying unsupervised learning to train deep layers of neural networks have achieved remarkable results in numerous fields. In the past, many…