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Tal Grossman
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1990 – 1999
- 1998
- [j7]David H. Wolpert, Emanuel Knill, Tal Grossman:
Some results concerning off-training-set and IID error for the Gibbs and the Bayes optimal generalizers. Stat. Comput. 8(1): 35-54 (1998) - 1995
- [c7]Tal Grossman, Robert M. Farber, Alan S. Lapedes:
Neural Net Representations of Empirical Protein Potentials. ISMB 1995: 154-161 - 1994
- [c6]Tal Grossman, Alan S. Lapedes:
Noise sensitivity signatures for model selection. ICPR (2) 1994: 213-218 - 1993
- [j6]Amir A. Handzel, Tal Grossman, Eytan Domany, Shlomit Tarem, Ehud Duchovni:
A Neural Network Classifier In Experimental Particle Physics. Int. J. Neural Syst. 4(2): 95-108 (1993) - [c5]Tal Grossman:
Applying the INN model to the Maximum Clique problem. Cliques, Coloring, and Satisfiability 1993: 125-145 - [c4]Tal Grossman, Arun Jagota:
On the equivalence of two Hopfield-type networks. ICNN 1993: 1063-1068 - [c3]Tal Grossman, Alan S. Lapedes:
Use of Bad Training Data for Better Predictions. NIPS 1993: 343-350 - 1991
- [j5]Dimitry Nabutovsky, Tal Grossman, Eytan Domany:
Complex Systems: Errata and Changes. Complex Syst. 5(6) (1991) - [j4]Harel Z. Shouval, Isaac Shariv, Tal Grossman, Asher A. Friesem, Eytan Domany:
An All-Optical Hopfield Network: Theory and Experiment. Int. J. Neural Syst. 1(4): 355-360 (1991) - 1990
- [j3]Dimitry Nabutovsky, Tal Grossman, Eytan Domany:
Learning by CHIR without Storing Internal Representations. Complex Syst. 4(5) (1990)
1980 – 1989
- 1989
- [j2]Tal Grossman:
The CHIR Algorithm: A Generalization for Multiple-Output and Multilayered Networks. Complex Syst. 3(5) (1989) - [c2]Tal Grossman:
The CHIR Algorithm for Feed Forward Networks with Binary Weights. NIPS 1989: 516-523 - 1988
- [j1]Tal Grossman, Ronny Meir, Eytan Domany:
Learning by Choice of Internal Representations. Complex Syst. 2(5) (1988) - [c1]Tal Grossman, Ronny Meir, Eytan Domany:
Learning by Choice of Internal Representations. NIPS 1988: 73-80
Coauthor Index
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