697 citations · 2.5k across the 36 of their papers we have counts for
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Narrowing the Gap: Random Forests In Theory and In Practice
Misha Denil, David Matheson, Nando de Freitas
Despite widespread interest and practical use, the theoretical properties of random forests are still not well understood. In this paper we contribute to this understanding in two…
Linear and Parallel Learning of Markov Random Fields
Yariv Dror Mizrahi, Misha Denil, Nando de Freitas
We introduce a new embarrassingly parallel parameter learning algorithm for Markov random fields with untied parameters which is efficient for a large class of practical models. Ou…
Predicting Parameters in Deep Learning
Misha Denil, Babak Shakibi, Laurent Dinh +2
We demonstrate that there is significant redundancy in the parameterization of several deep learning models. Given only a few weight values for each feature it is possible to accur…
Consistency of Online Random Forests
Misha Denil, David Matheson, Nando de Freitas
As a testament to their success, the theory of random forests has long been outpaced by their application in practice. In this paper, we take a step towards narrowing this gap by p…