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» Learning Functions from Imperfect Positive Data
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IMC
2010
ACM
13 years 8 months ago
Temporally oblivious anomaly detection on large networks using functional peers
Previous methods of network anomaly detection have focused on defining a temporal model of what is "normal," and flagging the "abnormal" activity that does not...
Kevin M. Carter, Richard Lippmann, Stephen W. Boye...
MLG
2007
Springer
14 years 4 months ago
A Universal Kernel for Learning Regular Languages
We give a universal kernel that renders all the regular languages linearly separable. We are not able to compute this kernel efficiently and conjecture that it is intractable, but...
Leonid Kontorovich
BMCBI
2007
144views more  BMCBI 2007»
13 years 10 months ago
Assessing the ability of sequence-based methods to provide functional insight within membrane integral proteins: a case study an
Background: Efforts to predict functional sites from globular proteins is increasingly common; however, the most successful of these methods generally require structural insight. ...
Dennis R. Livesay, Patrick D. Kidd, Sepehr Eskanda...
ICML
2007
IEEE
14 years 11 months ago
Multifactor Gaussian process models for style-content separation
We introduce models for density estimation with multiple, hidden, continuous factors. In particular, we propose a generalization of multilinear models using nonlinear basis functi...
Jack M. Wang, David J. Fleet, Aaron Hertzmann
CVPR
2007
IEEE
15 years 3 days ago
Parameter Sensitive Detectors
Object detection can be challenging when the object class exhibits large variations. One commonly-used strategy is to first partition the space of possible object variations and t...
Quan Yuan, Ashwin Thangali, Vitaly Ablavsky, Stan ...