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ISCAS
2003
IEEE
117views Hardware» more  ISCAS 2003»
14 years 2 months ago
Learning temporal correlations in biologically-inspired aVLSI
Temporally-asymmetric Hebbian learning is a class of algorithms motivated by data from recent neurophysiology experiments. While traditional Hebbian learning rules use mean firin...
Adria Bofill-i-Petit, Alan F. Murray
UIST
2010
ACM
13 years 7 months ago
Designing adaptive feedback for improving data entry accuracy
Data quality is critical for many information-intensive applications. One of the best opportunities to improve data quality is during entry. USHER provides a theoretical, data-dri...
Kuang Chen, Joseph M. Hellerstein, Tapan S. Parikh
SIGIR
2008
ACM
13 years 9 months ago
Learning to rank with partially-labeled data
Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
Kevin Duh, Katrin Kirchhoff
ICRA
1998
IEEE
105views Robotics» more  ICRA 1998»
14 years 1 months ago
PSOM Network: Learning with Few Examples
: Precise sensorimotor mappings between various motor, ensor, and abstract physical spaces are the basis for many robotics tasks. Their cheap construction is a challenge for adapti...
Jörg A. Walter
BMCBI
2010
224views more  BMCBI 2010»
13 years 9 months ago
An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Susmita Datta, Vasyl Pihur, Somnath Datta