JMLR
2010
12 years 11 months ago
2010
Probabilistic models of the performance of computer systems are useful both for predicting system performance in new conditions, and for diagnosing past performance problems. The ...
JMLR
2010
12 years 11 months ago
2010
Model selection strategies for machine learning algorithms typically involve the numerical optimisation of an appropriate model selection criterion, often based on an estimator of...
JCIT
2010
12 years 11 months ago
2010
Web Service Choreography Description Language is a main-stream standard for the description of peer-to-peer collaborations for the participants for service composition. To predict...
ICFHR
2010
12 years 11 months ago
2010
This competition scenario aims at a performance comparison of several automated systems for the task of signature verification. The systems have to rate the probability of authors...
17
Voted
WWW
2011
ACM
12 years 11 months ago
2011
ACM
In social bookmarking systems, existing methods in tag prediction have shown that the performance of prediction can be significantly improved by modeling users’ preferences. Ho...
TCOM
2011
12 years 11 months ago
2011
—Low-density parity-check (LDPC) codes are gaining interest for high data rate applications in both terrestrial and spatial communications. They can be designed and studied throu...
MMS
2011
12 years 11 months ago
2011
Abstract In recent years, some approximate highdimensional indexing techniques have shown promising results by trading off quality guarantees for improved query performance. While ...
IJDMB
2011
12 years 11 months ago
2011
: Classification methods are vital for efficient access of knowledge hidden in biomedical publications. Support vector machines (SVMs) are modern non-parametric deterministic clas...
COGSR
2011
12 years 11 months ago
2011
Fatigue has been implicated in an alarming number of motor vehicle accidents, costing billions of dollars and thousands of lives. Unfortunately, the ability to predict performance...
CDC
2010
IEEE
12 years 11 months ago
2010
IEEE
This paper studies iterative learning control (ILC) in a multi-agent framework. A group of agents simultaneously and repeatedly perform the same task. The agents improve their perf...