GECCO
2009
Springer
14 years 4 days ago
2009
Springer
Typical domains used in machine learning analyses only partially cover the complexity space, remaining a large proportion of problem difficulties that are not tested. Since the ac...
FPL
2009
Springer
14 years 5 days ago
2009
Springer
Restricted Boltzmann Machines (RBMs) — the building block for newly popular Deep Belief Networks (DBNs) — are a promising new tool for machine learning practitioners. However,...
ICADL
2010
Springer
14 years 10 days ago
2010
Springer
Maintaining and extending large thesauri is an important challenge facing digital libraries and IT businesses alike. In this paper we describe a method building on and extending ex...
AI
2010
Springer
14 years 10 days ago
2010
Springer
This paper presents a supervised machine learning approach for summarizing legal documents. A commercial system for the analysis and summarization of legal documents provided us wi...
GCB
2003
Springer
14 years 23 days ago
2003
Springer
: Classification and prediction of protein structure has been a central research theme in structural bioinformatics. Due to the imbalanced distribution of proteins over multi SCOP ...
ESSMAC
2003
Springer
14 years 23 days ago
2003
Springer
Abstract. We consider a linear system, such as an estimator or a controller, in which several signals are transmitted over wireless communication channels. With the coding and medi...
ESSMAC
2003
Springer
14 years 23 days ago
2003
Springer
We present a gestural interface for entering text on a mobile device via continuous movements, with control based on feedback from a probabilistic language model. Text is represent...
ESSMAC
2003
Springer
14 years 23 days ago
2003
Springer
ESSMAC
2003
Springer
14 years 23 days ago
2003
Springer
Kernel-based non-parametric models have been applied widely over recent years. However, the associated computational complexity imposes limitations on the applicability of those me...
ESSMAC
2003
Springer
14 years 23 days ago
2003
Springer
Gaussian Process prior models, as used in Bayesian non-parametric statistical models methodology are applied to implement a nonlinear adaptive control law. The expected value of a...