In this paper, we propose a unified algorithmic framework for solving many known variants of MDS. Our algorithm is a simple iterative scheme with guaranteed convergence, and is mo...
Arvind Agarwal, Jeff M. Phillips, Suresh Venkatasu...
Maintaining compact and competent case bases has become a main topic of Case Based Reasoning (CBR) research. The main goal is to obtain a compact case base (with a reduced number o...
Supervised learning is difficult with high dimensional input spaces and very small training sets, but accurate classification may be possible if the data lie on a low-dimensional ...
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...