Classification is one of the most fundamental problems in machine learning, which aims to separate the data from different classes as far away as possible. A common way to get a g...
Bin Zhang, Fei Wang, Ta-Hsin Li, Wen Jun Yin, Jin ...
Clustering is an old research topic in data mining and machine learning communities. Most of the traditional clustering methods can be categorized local or global ones. In this pa...
We consider the problem of estimating the time-average variance constant for a stationary process. A previous paper described an approach based on multiple integrations of the sim...
In this paper, we re-examine the RSSI measurement model for location estimation and provide the first detailed formulation of the probability distribution of the position of a sens...
Charalampos Papamanthou, Franco P. Preparata, Robe...
We study distribution-dependent, data-dependent, learning in the limit with adversarial disturbance. We consider an optimization-based approach to learning binary classifiers from...