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» Sampling Binary Contingency Tables
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ISIPTA
1999
IEEE
13 years 10 months ago
Implicative Analysis for Multivariate Binary Data using an Imprecise Dirichlet Model
Bayesian implicative analysis was proposed for summarizing the association in a 22 contingency table in terms possibly asymmetrical such as, e.g., presence of feature a implies, i...
Jean-Marc Bernard
SDM
2012
SIAM
235views Data Mining» more  SDM 2012»
11 years 8 months ago
Sampling Strategies to Evaluate the Performance of Unknown Predictors
The focus of this paper is on how to select a small sample of examples for labeling that can help us to evaluate many different classification models unknown at the time of sampl...
Hamed Valizadegan, Saeed Amizadeh, Milos Hauskrech...
SODA
2003
ACM
115views Algorithms» more  SODA 2003»
13 years 7 months ago
Random walks on the vertices of transportation polytopes with constant number of sources
We consider the problem of uniformly sampling a vertex of a transportation polytope with m sources and n destinations, where m is a constant. We analyse a natural random walk on t...
Mary Cryan, Martin E. Dyer, Haiko Müller, Lee...
JMLR
2010
144views more  JMLR 2010»
13 years 1 months ago
Maximum Margin Learning with Incomplete Data: Learning Networks instead of Tables
In this paper we address the problem of predicting when the available data is incomplete. We show that changing the generally accepted table-wise view of the sample items into a g...
Sándor Szedmák, Yizhao Ni, Steve R. ...
STOC
2003
ACM
164views Algorithms» more  STOC 2003»
14 years 6 months ago
Approximate counting by dynamic programming
We give efficient algorithms to sample uniformly, and count approximately, the solutions to a zero-one knapsack problem. The algorithm is based on using dynamic programming to pro...
Martin E. Dyer