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» Evaluating learning algorithms and classifiers
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BMVC
2002
14 years 23 days ago
Adaptive Learning of Statistical Appearance Models for 3D Human Tracking
A likelihood formulation for human tracking is presented based upon matching feature statistics on the surface of an articulated 3D body model. A benefit of such a formulation ove...
Timothy J. Roberts, Stephen J. McKenna, Ian W. Ric...
BMCBI
2010
135views more  BMCBI 2010»
13 years 10 months ago
A classification approach for genotyping viral sequences based on multidimensional scaling and linear discriminant analysis
Background: Accurate classification into genotypes is critical in understanding evolution of divergent viruses. Here we report a new approach, MuLDAS, which classifies a query seq...
Ji Woong Kim, Yongju Ahn, Kichan Lee, Sung-Hee Par...
ICML
2003
IEEE
14 years 11 months ago
Hidden Markov Support Vector Machines
This paper presents a novel discriminative learning technique for label sequences based on a combination of the two most successful learning algorithms, Support Vector Machines an...
Yasemin Altun, Ioannis Tsochantaridis, Thomas Hofm...
KCAP
2009
ACM
14 years 4 months ago
Interactively shaping agents via human reinforcement: the TAMER framework
As computational learning agents move into domains that incur real costs (e.g., autonomous driving or financial investment), it will be necessary to learn good policies without n...
W. Bradley Knox, Peter Stone
ANLP
1997
186views more  ANLP 1997»
13 years 11 months ago
Software Infrastructure for Natural Language Processing
We classify and review current approaches to software infrastructure for research, development and delivery of NLP systems. The task is motivated by a discussion of current trends...
Hamish Cunningham, Kevin Humphreys, Robert J. Gaiz...