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» Regularized Learning with Networks of Features
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121
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ICDM
2010
IEEE
127views Data Mining» more  ICDM 2010»
15 years 18 days ago
Learning Markov Network Structure with Decision Trees
Traditional Markov network structure learning algorithms perform a search for globally useful features. However, these algorithms are often slow and prone to finding local optima d...
Daniel Lowd, Jesse Davis
119
Voted
ICDAR
2007
IEEE
15 years 9 months ago
A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images
We describe an unsupervised learning algorithm for extracting sparse and locally shift-invariant features. We also devise a principled procedure for learning hierarchies of invari...
Marc'Aurelio Ranzato, Yann LeCun
110
Voted
FPL
2007
Springer
126views Hardware» more  FPL 2007»
15 years 8 months ago
A Time-Triggered Network-on-Chip
In this paper we propose a time-triggered network-onchip (NoC) for on-chip real-time systems. The NoC provides time predictable on- and off-chip communication, a mandatory feature...
Martin Schoeberl
155
Voted
ICMCS
2008
IEEE
207views Multimedia» more  ICMCS 2008»
15 years 9 months ago
Structure learning in a Bayesian network-based video indexing framework
Several stochastic models provide an effective framework to identify the temporal structure of audiovisual data. Most of them need as input a first video structure, i.e. connecti...
Siwar Baghdadi, Guillaume Gravier, Claire-Hé...
139
Voted
KDD
2010
ACM
224views Data Mining» more  KDD 2010»
15 years 6 months ago
Multi-label learning by exploiting label dependency
In multi-label learning, each training example is associated with a set of labels and the task is to predict the proper label set for the unseen example. Due to the tremendous (ex...
Min-Ling Zhang, Kun Zhang