Principal component analysis (PCA) is a classical data analysis technique that finds linear transformations of data that retain the maximal amount of variance. We study a case whe...
Context based entropy coding has the potential to provide higher gain over memoryless entropy coding. However serious difficulties arise regarding the practical implementation in...
Guillaume Fuchs, Vignesh Subbaraman, Markus Multru...
Recent years have witnessed a growing interest in analogical learning for NLP applications. If the principle of analogical learning is quite simple, it does involve complex steps ...
Recent work has focused on increasing availability in the face of Internet path failures. To date, proposed solutions have relied on complex routing and pathmonitoring schemes, tr...
P. Krishna Gummadi, Harsha V. Madhyastha, Steven D...
One of the most challenging problems in wireless sensor networks is the design of scalable and efficient routing algorithms without location information. The use of specialized ha...