We consider the problem of fitting a large-scale covariance matrix to multivariate Gaussian data in such a way that the inverse is sparse, thus providing model selection. Beginnin...
Onureena Banerjee, Laurent El Ghaoui, Alexandre d'...
We show a remarkable fact about folding paper: From a single rectangular sheet of paper, one can fold it into a flat origami that takes the (scaled) shape of any connected polygo...
Erik D. Demaine, Martin L. Demaine, Joseph S. B. M...
Abstract. We present a new reinforcement learning approach for deterministic continuous control problems in environments with unknown, arbitrary reward functions. The difficulty of...
To support dynamic address translation in today's microprocessors, the first-level cache is accessed in parallel with a translation lookaside buffer (TLB). However, this curre...
Distance metric learning and nonlinear dimensionality reduction are two interesting and active topics in recent years. However, the connection between them is not thoroughly studi...