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ESANN
2001
13 years 9 months ago
Motor control and movement optimization learned by combining auto-imitative and genetic algorithms
In sensorimotor behaviour often a great movement execution variability is combined with a relatively low error in reaching the intended goal. This phenomenon can especially be obse...
Karl-Theodor Kalveram, Ulrich Nakte
ICCV
2009
IEEE
15 years 22 days ago
Efficient Discriminative Learning of Parts-based Models
Supervised learning of a parts-based model can be for- mulated as an optimization problem with a large (exponen- tial in the number of parts) set of constraints. We show how thi...
M. Pawan Kumar, Andrew Zisserman, Philip H.S. Torr
ACL
2011
12 years 11 months ago
In-domain Relation Discovery with Meta-constraints via Posterior Regularization
We present a novel approach to discovering relations and their instantiations from a collection of documents in a single domain. Our approach learns relation types by exploiting m...
Harr Chen, Edward Benson, Tahira Naseem, Regina Ba...
ACL
2012
11 years 10 months ago
Labeling Documents with Timestamps: Learning from their Time Expressions
Temporal reasoners for document understanding typically assume that a document’s creation date is known. Algorithms to ground relative time expressions and order events often re...
Nathanael Chambers
ICML
2000
IEEE
14 years 8 months ago
Clustering with Instance-level Constraints
Clustering algorithms conduct a search through the space of possible organizations of a data set. In this paper, we propose two types of instance-level clustering constraints ? mu...
Kiri Wagstaff, Claire Cardie