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ICML
2000
IEEE
15 years 10 months ago
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
Algorithms for feature selection fall into two broad categories: wrappers that use the learning algorithm itself to evaluate the usefulness of features and filters that evaluate f...
Mark A. Hall
ICML
2005
IEEE
15 years 10 months ago
Learning strategies for story comprehension: a reinforcement learning approach
This paper describes the use of machine learning to improve the performance of natural language question answering systems. We present a model for improving story comprehension th...
Eugene Grois, David C. Wilkins
ICML
2004
IEEE
15 years 10 months ago
The Bayesian backfitting relevance vector machine
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
Aaron D'Souza, Sethu Vijayakumar, Stefan Schaal
ICS
1999
Tsinghua U.
15 years 2 months ago
Fast cluster failover using virtual memory-mapped communication
This paper proposes a novel way to use virtual memorymapped communication (VMMC) to reduce the failover time on clusters. With the VMMC model, applications’ virtual address spac...
Yuanyuan Zhou, Peter M. Chen, Kai Li
ICANN
2009
Springer
15 years 4 months ago
Using Kernel Basis with Relevance Vector Machine for Feature Selection
This paper presents an application of multiple kernels like Kernel Basis to the Relevance Vector Machine algorithm. The framework of kernel machines has been a source of many works...
Frederic Suard, David Mercier