In recent years analysis of complexity of learning Gaussian mixture models from sampled data has received significant attention in computational machine learning and theory commun...
In this paper we explore private computation built on vector addition and its applications in privacypreserving data mining. Vector addition is a surprisingly general tool for imp...
An empirical study of the domain of patch-based learning algorithms for image and video processing is conducted. As patch-based algorithms are commonly used, knowledge of the prop...
Inspectable Bayesian student models have been used to support student reflection, knowledge awareness and communication among teacher, students and parents. This paper presents a...
We study the learnability of first order Horn expressions from equivalence and membership queries. We show that the class of expressions where every term in the consequent of a c...