In this paper, we propose a novel method which involves neural adaptive techniques for identifying salient features and for classifying high dimensionality data. In particular a ne...
Abstract. We present a survey of recent results concerning the theoretical and empirical performance of algorithms for learning regularized least-squares classifiers. The behavior ...
Digital Manipulatives embed computation in familiar children's toys and provide means for children to design behavior. Some systems use "record and play" as a form ...
Hayes Raffle, Amanda J. Parkes, Hiroshi Ishii, Jos...
In this paper, we propose a new way to automatically model and predict human behavior of receiving and disseminating information by analyzing the contact and content of personal c...
Xiaodan Song, Ching-Yung Lin, Belle L. Tseng, Ming...
Supervised and unsupervised learning methods have traditionally focused on data consisting of independent instances of a single type. However, many real-world domains are best des...