“The curse of dimensionality” is pertinent to many learning algorithms, and it denotes the drastic raise of computational complexity and classification error in high dimension...
Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal
We consider the problem of learning a mapping function from low-level feature space to high-level semantic space. Under the assumption that the data lie on a submanifold embedded ...
In this paper, we consider a variation of the Euclidean Steiner Tree Problem in which the space underlying the set of nodes has a specified non-uniform cost structure. This proble...
DRAM vendors have traditionally optimized the cost-perbit metric, often making design decisions that incur energy penalties. A prime example is the overfetch feature in DRAM, wher...
Aniruddha N. Udipi, Naveen Muralimanohar, Niladris...
The availability of multicore processors has led to significant interest in compiler techniques for speculative parallelization of sequential programs. Isolation of speculative s...