The rapid developing area of compressed sensing suggests that a sparse vector lying in a high dimensional space can be accurately and efficiently recovered from only a small set of...
The linear model with sparsity-favouring prior on the coefficients has important applications in many different domains. In machine learning, most methods to date search for maxim...
Graphs are fundamental data structures and have been employed for centuries to model real-world systems and phenomena. Random walk with restart (RWR) provides a good proximity sco...
In 1969, Thomas Schelling proposed one of the most cited models in economics to explain how similar people (e.g. people with the same race, education, community) group together in...
We describe a simple improvement to ngram language models where we estimate the distribution over closed-class (function) words separately from the conditional distribution of ope...