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» Incremental Dependency Parsing Using Online Learning
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TIP
2008
157views more  TIP 2008»
13 years 7 months ago
Robust Face Tracking via Collaboration of Generic and Specific Models
Significant appearance changes of objects under different orientations could cause loss of tracking, "drifting." In this paper, we present a collaborative tracking framew...
Peng Wang, Qiang Ji
ECML
2003
Springer
14 years 27 days ago
Learning Context Free Grammars in the Limit Aided by the Sample Distribution
We present an algorithm for learning context free grammars from positive structural examples (unlabeled parse trees). The algorithm receives a parameter in the form of a finite se...
Yoav Seginer
CISIS
2011
IEEE
12 years 7 months ago
Improving Scheduling Techniques in Heterogeneous Systems with Dynamic, On-Line Optimisations
—Computational performance increasingly depends on parallelism, and many systems rely on heterogeneous resources such as GPUs and FPGAs to accelerate computationally intensive ap...
Marcin Bogdanski, Peter R. Lewis, Tobias Becker, X...
ICDM
2003
IEEE
181views Data Mining» more  ICDM 2003»
14 years 29 days ago
Dynamic Weighted Majority: A New Ensemble Method for Tracking Concept Drift
Algorithms for tracking concept drift are important for many applications. We present a general method based on the Weighted Majority algorithm for using any online learner for co...
Jeremy Z. Kolter, Marcus A. Maloof
AR
2002
157views more  AR 2002»
13 years 7 months ago
Acquiring state from control dynamics to learn grasping policies for robot hands
Abstract--A prominent emerging theory of sensorimotor development in biological systems proposes that control knowledge is encoded in the dynamics of physical interaction with the ...
Roderic A. Grupen, Jefferson A. Coelho Jr.