We investigate the use of self-predicting neural networks for autonomous robot learning within noisy or partially predictable environments. A benchmark experiment is performed in ...
James B. Marshall, Neil K. Makhija, Zachary D. Rot...
We propose Link Propagation as a new semi-supervised learning method for link prediction problems, where the task is to predict unknown parts of the network structure by using aux...
In this paper we consider the problem of building a system to predict readability of natural-language documents. Our system is trained using diverse features based on syntax and l...
Rohit J. Kate, Xiaoqiang Luo, Siddharth Patwardhan...
File prefetching based on previous file access patterns has been shown to be an effective means of reducing file system latency by implicitly loading caches with files that are li...
In this paper, weexplore the use of machinelearning and data mining to improvethe prediction of travel times in an automobile. Weconsider two formulations of this problem, one tha...