Deep autoencoder networks have successfully been applied in unsupervised dimension reduction. The autoencoder has a "bottleneck" middle layer of only a few hidden units, ...
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...
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...
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...
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...