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» Semi-Supervised Dimensionality Reduction
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ICANN
2010
Springer
15 years 4 months ago
Deep Bottleneck Classifiers in Supervised Dimension Reduction
Deep autoencoder networks have successfully been applied in unsupervised dimension reduction. The autoencoder has a "bottleneck" middle layer of only a few hidden units, ...
Elina Parviainen
ISQED
2007
IEEE
124views Hardware» more  ISQED 2007»
15 years 10 months ago
Multi-Dimensional Circuit and Micro-Architecture Level Optimization
This paper studies multi-dimensional optimization at both circuit and micro-architecture levels. By formulating and solving the optimization problem with conflicting design objec...
Zhenyu Qi, Matthew M. Ziegler, Stephen V. Kosonock...
MDM
2004
Springer
138views Communications» more  MDM 2004»
15 years 9 months ago
Optimizing Data Placement over Wireless Broadcast Channel for Multi-Dimensional Range Query Processing
Data broadcasting is well known for its excellent scalability. Multi-dimensional range queries, such as spatial range queries of geographical information for location dependent se...
Jianting Zhang, Le Gruenwald
149
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ARITH
2001
IEEE
15 years 7 months ago
The Use of the Multi-Dimensional Logarithmic Number System in DSP Applications
A recently introduced double-base number representation has proved to be successful in optimizing the performance of several algorithms in cryptography and digital signal processi...
Vassil S. Dimitrov, Jonathan Eskritt, Laurent Imbe...
ICCS
2005
Springer
15 years 9 months ago
Dimension Reduction for Clustering Time Series Using Global Characteristics
Existing methods for time series clustering rely on the actual data values can become impractical since the methods do not easily handle dataset with high dimensionality, missing v...
Xiaozhe Wang, Kate A. Smith, Rob J. Hyndman