Classification is one of the most fundamental problems in machine learning, which aims to separate the data from different classes as far away as possible. A common way to get a g...
Bin Zhang, Fei Wang, Ta-Hsin Li, Wen Jun Yin, Jin ...
We use a generative history-based model to predict the most likely derivation of a dependency parse. Our probabilistic model is based on Incremental Sigmoid Belief Networks, a rec...
— Three-dimensional digital terrain models are of fundamental importance in many areas such as the geo-sciences and outdoor robotics. Accurate modeling requires the ability to de...
We are developing an object-oriented real-time database system that includes a relationally complete query language. Unlike conventional query optimizers, our optimizer estimates ...
Application Service Maintenance(ASM) projects mainly use Activity-Based software estimation methodology compared to Function Point or Lines of Code Estimation methodologies[1]. Th...