Abstract. In many application domains, e.g. sensor databases, traffic management or recognition systems, objects have to be compared based on positionally and existentially uncert...
Thomas Bernecker, Hans-Peter Kriegel, Matthias Ren...
During past few years, a variety of methods have been developed for learning probabilistic networks from data, among which the heuristic single link forward or backward searches ar...
The importance of query processing over uncertain data has recently arisen due to its wide usage in many real-world applications. In the context of uncertain databases, previous wo...
We propose a new matrix completion algorithm— Kernelized Probabilistic Matrix Factorization (KPMF), which effectively incorporates external side information into the matrix fac...
This paper attempts to extend the XCS research by analyzing the impact of information exchange between XCS agents on classifier performance. Two types of information are exchange...