We propose an ℓ1 criterion for dictionary learning for sparse signal representation. Instead of directly searching for the dictionary vectors, our dictionary learning approach i...
We propose a simple distributed algorithm for balancing indivisible tokens on graphs. The algorithm is completely deterministic, though it tries to imitate (and enhance) a random ...
Tobias Friedrich, Martin Gairing, Thomas Sauerwald
Process-aware information systems are typically driven by process models capturing an idealized view of the actual processes. For example, most process models assume that planned ...
Wil M. P. van der Aalst, Michael Rosemann, Marlon ...
A conventional automatic speech recognizer does not perform well in the presence of multiple sound sources, while human listeners are able to segregate and recognize a signal of i...
Yang Shao, Soundararajan Srinivasan, Zhaozhang Jin...
We introduce a general-purpose learning machine that we call the Guaranteed Error Machine, or GEM, and two learning algorithms, a real GEM algorithm and an ideal GEM algorithm. Th...