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KDD
2009
ACM
229views Data Mining» more  KDD 2009»
16 years 3 months ago
Relational learning via latent social dimensions
Social media such as blogs, Facebook, Flickr, etc., presents data in a network format rather than classical IID distribution. To address the interdependency among data instances, ...
Lei Tang, Huan Liu
BMCBI
2008
173views more  BMCBI 2008»
15 years 3 months ago
Improved machine learning method for analysis of gas phase chemistry of peptides
Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) o...
Allison Gehrke, Shaojun Sun, Lukasz A. Kurgan, Nat...
106
Voted
CORR
2010
Springer
142views Education» more  CORR 2010»
15 years 1 months ago
HyperANF: Approximating the Neighbourhood Function of Very Large Graphs on a Budget
The neighbourhood function NG(t) of a graph G gives, for each t ∈ N, the number of pairs of nodes x, y such that y is reachable from x in less that t hops. The neighbourhood fun...
Paolo Boldi, Marco Rosa, Sebastiano Vigna
WACV
2007
IEEE
15 years 9 months ago
Object Categorization Robust to Surface Markings using Entropy-guided Codebook
Visual categorization is fundamentally important for autonomous mobile robots to get intelligence such as novel object acquisition and topological place recognition. The main difï...
Sungho Kim, In-So Kweon
85
Voted
ICPR
2008
IEEE
16 years 4 months ago
A new objective function for sequence labeling
We propose a new loss function for discriminative learning of Markov random fields, which is an intermediate loss function between the sequential loss and the pointwise loss. We s...
Hisashi Kashima, Yuta Tsuboi