We study the phenomenon of cognitive learning from an algorithmic standpoint. How does the brain effectively learn concepts from a small number of examples despite the fact that e...
Abstract. We give a high-level description of some fundamental randomized and deterministic techniques for routing and sorting on xedconnection networks such as meshes, hypercubes ...
Consider the problem of membership query for a given partially ordered set. We devise a greedy algorithm which can produce near-optimal search strategies. Rigorous analysis has be...
Many computer vision problems can be formulated in
a Bayesian framework with Markov Random Field (MRF)
or Conditional Random Field (CRF) priors. Usually, the
model assumes that ...
Background: Data generated using `omics' technologies are characterized by high dimensionality, where the number of features measured per subject vastly exceeds the number of...
Yu Guo, Armin Graber, Robert N. McBurney, Raji Bal...