The performance of graph based clustering methods critically depends on the quality of the distance function, used to compute similarities between pairs of neighboring nodes. In t...
This paper addresses the important tradeoff between privacy and learnability, when designing algorithms for learning from private databases. We focus on privacy-preserving logisti...
Modern science is collecting massive amounts of data from sensors, instruments, and through computer simulation. It is widely believed that analysis of this data will hold the key ...
Predictive data mining typically relies on labeled data without exploiting a much larger amount of available unlabeled data. The goal of this paper is to show that using unlabeled...
Kang Peng, Slobodan Vucetic, Bo Han, Hongbo Xie, Z...
In this paper we introduce the concept and method for adaptively tuning the model complexity in an online manner as more examples become available. Challenging classification pro...