Ensemble learning is attracting much attention from pattern recognition and machine learning domains for good generalization. Both theoretical and experimental researches show tha...
Random walk simulation is employed in many experimental algorithmic applications. Efficient execution on modern computer architectures demands that the random walk be implemented t...
Ilya Safro, Paul D. Hovland, Jaewook Shin, Michell...
This paper describes a successful but challenging application of data mining in the railway industry. The objective is to optimize maintenance and operation of trains through prog...
Linear Support Vector Machines (SVMs) have become one of the most prominent machine learning techniques for highdimensional sparse data commonly encountered in applications like t...
The notion of algorithmic stability has been used effectively in the past to derive tight generalization bounds. A key advantage of these bounds is that they are designed for spec...