Model-based diagnostic reasoning often leads to a large number of diagnostic hypotheses. The set of diagnoses can be reduced by taking into account extra observations (passive mon...
Alexander Feldman, Gregory M. Provan, Arjan J. C. ...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
We present a clustering scheme that combines a mode-seeking phase with a cluster merging phase in the corresponding density map. While mode detection is done by a standard graph-b...
Gowers [Gow98, Gow01] introduced, for d 1, the notion of dimension-d uniformity Ud (f) of a function f : G C, where G is a finite abelian group. Roughly speaking, if a function ...
Extracting dense sub-components from graphs efficiently is an important objective in a wide range of application domains ranging from social network analysis to biological network...
Nan Wang, Srinivasan Parthasarathy, Kian-Lee Tan, ...