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FPL
2009
Springer
161views Hardware» more  FPL 2009»
14 years 3 months 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
ISCAS
1995
IEEE
97views Hardware» more  ISCAS 1995»
14 years 1 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
13 years 12 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
NN
2008
Springer
201views Neural Networks» more  NN 2008»
13 years 10 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
NN
2000
Springer
177views Neural Networks» more  NN 2000»
13 years 10 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