Learning by Choice of Internal Representations. - Tal Grossman; Ronny Meir; Eytan Domany (Complex Syst., 1988)

The CHIR Algorithm for Feed Forward Networks with Binary Weights. - Tal Grossman (NIPS, 1989)

The CHIR Algorithm: A Generalization for Multiple-Output and Multilayered Networks. - Tal Grossman (Complex Syst., 1989)

Learning by CHIR without Storing Internal Representations. - Dimitry Nabutovsky; Tal Grossman; Eytan Domany (Complex Syst., 1990)

Complex Systems: Errata and Changes. - Dimitry Nabutovsky; Tal Grossman; Eytan Domany (Complex Syst., 1991)

An All-Optical Hopfield Network: Theory and Experiment. - Harel Z. Shouval; Isaac Shariv; Tal Grossman; Asher A. Friesem; Eytan Domany (Int. J. Neural Syst., 1991)

Applying the INN model to the Maximum Clique problem. - Tal Grossman (Cliques, Coloring, and Satisfiability, 1993)

On the equivalence of two Hopfield-type networks. - Tal Grossman; Arun Jagota (ICNN, 1993)

Use of Bad Training Data for Better Predictions. - Tal Grossman; Alan S. Lapedes (NIPS, 1993)

A Neural Network Classifier In Experimental Particle Physics. - Amir A. Handzel; Tal Grossman; Eytan Domany; Shlomit Tarem; Ehud Duchovni (Int. J. Neural Syst., 1993)

Noise sensitivity signatures for model selection. - Tal Grossman; Alan S. Lapedes (ICPR (2), 1994)

Neural Net Representations of Empirical Protein Potentials. - Tal Grossman; Robert M. Farber; Alan S. Lapedes (ISMB, 1995)

Some results concerning off-training-set and IID error for the Gibbs and the Bayes optimal generalizers. - David H. Wolpert; Emanuel Knill; Tal Grossman (Stat. Comput., 1998)