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...
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...
Traditional non-parametric statistical learning techniques are often computationally attractive, but lack the same generalization and model selection abilities as state-of-the-art...
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...
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...