I argue that computer graphics can benefit from a deeper use of machine learning techniques. I give an overview of what learning has to offer the graphics community, with an emph...
This work describes a multi-agent architecture and strategy for trade in simultaneous and related auctions. The proposed SIMPLE Agency combines an integer programming model, machi...
In this paper we evaluate two methods for key estimation from polyphonic audio recordings. Our goal is to compare between a strategy using a cognition-inspired model and several m...
This paper presents a comparison among several well-known machine learning techniques when they are used to carry out a one-session ahead prediction of page categories. We use reco...
This paper describes ongoing research into the application of machine learning techniques for improving access to governmental information in complex digital libraries. Under the ...
Miles Efron, Jonathan L. Elsas, Gary Marchionini, ...
In this article we will introduce a new approach (and several implementations) to the task of sentence classification, where pre-defined classes are assigned to sentences. This a...
Menno van Zaanen, Luiz Augusto Sangoi Pizzato, Die...
This article introduces the concept of context knowledge discovery process, and presents a middleware architecture which eases the task of ubiquitous computing developers, while su...
Abstract. Although similarity measures play a crucial role in CBR applications, clear methodologies for defining them have not been developed yet. One approach to simplify the de...
Overfitting is a fundamental problem of most machine learning techniques, including genetic programming (GP). Canary functions have been introduced in the literature as a concept ...
This paper is concerned with personalisation of user agents by symbolic, on-line machine learning techniques. The application of these ideas to an infotainment agent is discussed ...
Joshua J. Cole, Matt J. Gray, John W. Lloyd, Kee S...