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208
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FPL
2009
Springer
161views Hardware» more  FPL 2009»
16 years 1 days ago
A multi-FPGA architecture for stochastic Restricted Boltzmann Machines
Although there are many neural network FPGA architectures, there is no framework for designing large, high-performance neural networks suitable for the real world. In this paper, ...
Daniel L. Ly, Paul Chow
201
Voted
ISCAS
1995
IEEE
97views Hardware» more  ISCAS 1995»
15 years 11 months ago
A New Paradigm for Developing Digital Systems Based on a Multi-Cellular Organization
Embryological electronics or “Embryonics” is a new paradigm for developing digital systems of any complexity, endowed of universal computation, self-repair and self-reproducti...
Daniel Mange, Serge Durand, Eduardo Sanchez, Andr&...
NIPS
2008
15 years 8 months ago
Weighted Sums of Random Kitchen Sinks: Replacing minimization with randomization in learning
Randomized neural networks are immortalized in this well-known AI Koan: In the days when Sussman was a novice, Minsky once came to him as he sat hacking at the PDP-6. "What a...
Ali Rahimi, Benjamin Recht
227
Voted
NN
2008
Springer
201views Neural Networks» more  NN 2008»
15 years 7 months ago
Learning representations for object classification using multi-stage optimal component analysis
Learning data representations is a fundamental challenge in modeling neural processes and plays an important role in applications such as object recognition. In multi-stage Optima...
Yiming Wu, Xiuwen Liu, Washington Mio
202
Voted
NN
2000
Springer
177views Neural Networks» more  NN 2000»
15 years 7 months ago
Independent component analysis: algorithms and applications
A fundamental problem in neural network research, as well as in many other disciplines, is finding a suitable representation of multivariate data, i.e. random vectors. For reasons...
Aapo Hyvärinen, Erkki Oja