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» Two Algorithms for Inducing Causal Models from Data
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KDD
2007
ACM
137views Data Mining» more  KDD 2007»
15 years 10 months ago
Characterising the difference
Characterising the differences between two databases is an often occurring problem in Data Mining. Detection of change over time is a prime example, comparing databases from two b...
Jilles Vreeken, Matthijs van Leeuwen, Arno Siebes
SDM
2007
SIAM
104views Data Mining» more  SDM 2007»
14 years 11 months ago
Boosting Optimal Logical Patterns Using Noisy Data
We consider the supervised learning of a binary classifier from noisy observations. We use smooth boosting to linearly combine abstaining hypotheses, each of which maps a subcube...
Noam Goldberg, Chung-chieh Shan
EMMCVPR
2011
Springer
13 years 9 months ago
Data-Driven Importance Distributions for Articulated Tracking
Abstract. We present two data-driven importance distributions for particle filterbased articulated tracking; one based on background subtraction, another on depth information. In ...
Søren Hauberg, Kim Steenstrup Pedersen
BMCBI
2008
135views more  BMCBI 2008»
14 years 10 months ago
Inferring the role of transcription factors in regulatory networks
Background: Expression profiles obtained from multiple perturbation experiments are increasingly used to reconstruct transcriptional regulatory networks, from well studied, simple...
Philippe Veber, Carito Guziolowski, Michel Le Borg...
SDM
2008
SIAM
139views Data Mining» more  SDM 2008»
14 years 11 months ago
Simultaneous Unsupervised Learning of Disparate Clusterings
Most clustering algorithms produce a single clustering for a given data set even when the data can be clustered naturally in multiple ways. In this paper, we address the difficult...
Prateek Jain, Raghu Meka, Inderjit S. Dhillon