Michal Rosen-Zvi:
The DLR Hierarchy of Approximate
Inference
Michal Rosen-Zvi, Alan L. Yuille and Michael
I. Jordan
UAI 2005
Exponential Family
Harmoniums with an Application to Information Retrieval
Max Welling, Michal Rosen-Zvi and Geoffrey Hinton
Advances in Neural Information Processing Systems 17 MIT Press,
Approximate Inference by
Markov Chains on Union Spaces
Max Welling, Michal Rosen-Zvi and Yee Whye Teh
ICML 2004
The Author-Topic Model for Authors and Documents
Michal Rosen-Zvi,
Tom Griffiths, Mark Steyvers and Padhraic Smyth
UAI 2004
Go to this website for an
online version of the Author-Topic model
Probabilistic
Author-Topic Models for Information Discovery
Mark Steyvers, Padhraic Smyth , Michal
Rosen-Zvi and Tom
Griffiths
KDD 2004
Approximate
inference and the DLR equations
Michal Rosen-Zvi and Michael I. Jordan
Technical Report, Computer Science Division,
Time series prediction by feedforward neural
networks - is it difficult?
M Rosen-Zvi, I Kanter and W Kinzel
J. Phys. A: Math. Gen. 36: 4543-4550, (2003)
Mutual learning in a tree parity machine and its application
to cryptography
M. Rosen-Zvi, E. Klein, I. Kanter, and W. Kinzel
Phys. Rev. E 66: 066135 (2002)
Cryptography based on neural networks - analytical
results
M Rosen-Zvi, I Kanter and W Kinzel
J. Phys. A: Math. Gen. 35: L707-L713, (2002)
Generalization and capacity of extensively large
two-layered perceptrons
M. Rosen-Zvi, A. Engel, and I. Kanter
Phys. Rev. E 66: 036138 (2002)
Multilayer Neural Networks with Extensively Many
Hidden Units
M. Rosen-Zvi, A. Engel, and I. Kanter
Phys. Rev. Lett. 87: 078101 (2001)
Training a perceptron in a discrete weight space
M. Rosen-Zvi and I. Kanter
Phys. Rev. E 64: 046109 (2001)
On-line learning in the Ising perceptron
M Rosen-Zvi
J. Phys. A: Math. Gen. 33: 7277-7287 (2000)
Learnability of periodic activation functions:
General results
M. Rosen-Zvi, M. Biehl,
and I. Kanter
Phys. Rev. E 58: 3606-3609 (1998)
Frequency-Domain Photon Migration in Two-Layered Tissues
M. Rosen-Zvi and H. Taitelbaum,
Optical Society of
Slides
from Talks