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JMLR
2010
144views more  JMLR 2010»
14 years 4 months ago
Maximum Margin Learning with Incomplete Data: Learning Networks instead of Tables
In this paper we address the problem of predicting when the available data is incomplete. We show that changing the generally accepted table-wise view of the sample items into a g...
Sándor Szedmák, Yizhao Ni, Steve R. ...
CIKM
2009
Springer
15 years 4 months ago
L2 norm regularized feature kernel regression for graph data
Features in many real world applications such as Cheminformatics, Bioinformatics and Information Retrieval have complex internal structure. For example, frequent patterns mined fr...
Hongliang Fei, Jun Huan
ISLPED
2004
ACM
108views Hardware» more  ISLPED 2004»
15 years 3 months ago
SEPAS: a highly accurate energy-efficient branch predictor
Designers have invested much effort in developing accurate branch predictors with short learning periods. Such techniques rely on exploiting complex and relatively large structure...
Amirali Baniasadi, Andreas Moshovos
ECCV
2010
Springer
15 years 2 months ago
Efficient Highly Over-Complete Sparse Coding using a Mixture Model
Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...
ICRA
2006
IEEE
161views Robotics» more  ICRA 2006»
15 years 3 months ago
Quadruped Robot Obstacle Negotiation via Reinforcement Learning
— Legged robots can, in principle, traverse a large variety of obstacles and terrains. In this paper, we describe a successful application of reinforcement learning to the proble...
Honglak Lee, Yirong Shen, Chih-Han Yu, Gurjeet Sin...