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CVPR
2006
IEEE
15 years 25 days ago
Learning Boosted Asymmetric Classifiers for Object Detection
Object detection can be posted as those classification tasks where the rare positive patterns are to be distinguished from the enormous negative patterns. To avoid the danger of m...
Xinwen Hou, Cheng-Lin Liu, Tieniu Tan
ECCV
1998
Springer
15 years 20 days ago
Projective and Illumination Invariant Representation of Disjoint Shapes
We describe a new projectively invariant representation of disjoint contour groups which is suitable for shape-based retrieval from an image database. It consists of simultaneous ...
Sergei Startchik, Ruggero Milanese, Thierry Pun
ICML
2008
IEEE
14 years 11 months ago
No-regret learning in convex games
Quite a bit is known about minimizing different kinds of regret in experts problems, and how these regret types relate to types of equilibria in the multiagent setting of repeated...
Geoffrey J. Gordon, Amy R. Greenwald, Casey Marks
ECOOP
2009
Springer
14 years 11 months ago
Scaling CFL-Reachability-Based Points-To Analysis Using Context-Sensitive Must-Not-Alias Analysis
Pointer analyses derived from a Context-Free-Language (CFL) reachability formulation achieve very high precision, but they do not scale well to compute the points-to solution for a...
Guoqing Xu, Atanas Rountev, Manu Sridharan
PODS
2006
ACM
122views Database» more  PODS 2006»
14 years 11 months ago
Space- and time-efficient deterministic algorithms for biased quantiles over data streams
Skew is prevalent in data streams, and should be taken into account by algorithms that analyze the data. The problem of finding "biased quantiles"-- that is, approximate...
Graham Cormode, Flip Korn, S. Muthukrishnan, Dives...