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» Optimizing Feature Sets for Structured Data
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KDD
2012
ACM
194views Data Mining» more  KDD 2012»
13 years 4 months ago
A sparsity-inducing formulation for evolutionary co-clustering
Traditional co-clustering methods identify block structures from static data matrices. However, the data matrices in many applications are dynamic; that is, they evolve smoothly o...
Shuiwang Ji, Wenlu Zhang, Jun Liu
EMMCVPR
2011
Springer
14 years 1 months ago
Branch and Bound Strategies for Non-maximal Suppression in Object Detection
In this work, we are concerned with the detection of multiple objects in an image. We demonstrate that typically applied objectives have the structure of a random field model, but...
Matthew B. Blaschko
BMCBI
2006
110views more  BMCBI 2006»
15 years 1 months ago
Bias in error estimation when using cross-validation for model selection
Background: Cross-validation (CV) is an effective method for estimating the prediction error of a classifier. Some recent articles have proposed methods for optimizing classifiers...
Sudhir Varma, Richard Simon
JMLR
2010
206views more  JMLR 2010»
14 years 8 months ago
Learning Translation Invariant Kernels for Classification
Appropriate selection of the kernel function, which implicitly defines the feature space of an algorithm, has a crucial role in the success of kernel methods. In this paper, we co...
Sayed Kamaledin Ghiasi Shirazi, Reza Safabakhsh, M...
IJDMMM
2008
124views more  IJDMMM 2008»
15 years 1 months ago
Completing missing views for multiple sources of web media
: Combining multiple data sources, each with its own features, to achieve optimal inference has received a lot of attention in recent years. In inference from multiple data sources...
Shankara B. Subramanya, Zheshen Wang, Baoxin Li, H...