In transfer learning the aim is to solve new learning tasks using fewer examples by using information gained from solving related tasks. Existing transfer learning methods have be...
The runtime analysis of randomized search heuristics is a growing field where, in the last two decades, many rigorous results have been obtained. These results, however, apply pa...
Benjamin Doerr, Frank Neumann, Dirk Sudholt, Carst...
We present a novel boosting algorithm where temporal consistency is addressed in a short-term way. Although temporal correlation of observed data may be an important cue for classi...
Pedro Canotilho Ribeiro, Plinio Moreno, José...
In the k-medoid problem, given a dataset P, we are asked to choose k points in P as the medoids. The optimal medoid set minimizes the average Euclidean distance between the points ...
Testing a database engine has been and continues to be a challenging task. The space of possible SQL queries along with their possible access paths is practically unbounded. Moreo...
Hardik Bati, Leo Giakoumakis, Steve Herbert, Aleks...