The effectiveness of knowledge transfer using classification algorithms depends on the difference between the distribution that generates the training examples and the one from wh...
Graph clustering (also called graph partitioning) -- clustering the nodes of a graph -- is an important problem in diverse data mining applications. Traditional approaches involve...
Operating systems are complex and their behavior depends on many factors. Source code, if available, does not directly help one to understand the OS's behavior, as the behavi...
Nikolai Joukov, Avishay Traeger, Rakesh Iyer, Char...
Recent years have seen growing interest in effective algorithms for summarizing and querying massive, high-speed data streams. Randomized sketch synopses provide accurate approxima...
Graham Cormode, Minos N. Garofalakis, Dimitris Sac...
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...