Solutions to complex tasks often require the cooperation of multiple robots, however, developing multi-robot policies can present many challenges. In this work, we introduce teach...
I describe a framework for interpreting Support Vector Machines (SVMs) as maximum a posteriori (MAP) solutions to inference problems with Gaussian Process priors. This probabilisti...
We present DIADS, an integrated DIAgnosis tool for Databases and Storage area networks (SANs). Existing diagnosis tools in this domain have a database-only (e.g., [11]) or SAN-onl...
As context is acknowledged as an important factor that can affect users’ preferences, many researchers have worked on improving the quality of recommender systems by utilizing ...
We introduce a novel machine learning framework based on recursive autoencoders for sentence-level prediction of sentiment label distributions. Our method learns vector space repr...
Richard Socher, Jeffrey Pennington, Eric H. Huang,...