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JMLR
2010
101views more  JMLR 2010»
15 years 1 months ago
Exploiting Feature Covariance in High-Dimensional Online Learning
Some online algorithms for linear classification model the uncertainty in their weights over the course of learning. Modeling the full covariance structure of the weights can prov...
Justin Ma, Alex Kulesza, Mark Dredze, Koby Crammer...
COMPGEOM
2007
ACM
15 years 10 months ago
Bi-criteria linear-time approximations for generalized k-mean/median/center
We consider the problem of approximating a set P of n points in Rd by a collection of j-dimensional flats, and extensions thereof, under the standard median / mean / center measur...
Dan Feldman, Amos Fiat, Micha Sharir, Danny Segev
ICRA
2008
IEEE
135views Robotics» more  ICRA 2008»
16 years 1 months ago
Path and trajectory diversity: Theory and algorithms
— We present heuristic algorithms for pruning large sets of candidate paths or trajectories down to smaller subsets that maintain desirable characteristics in terms of overall re...
Michael S. Branicky, Ross A. Knepper, James J. Kuf...
CVPR
2005
IEEE
16 years 8 months ago
Beyond Pairwise Clustering
We consider the problem of clustering in domains where the affinity relations are not dyadic (pairwise), but rather triadic, tetradic or higher. The problem is an instance of the ...
Sameer Agarwal, Jongwoo Lim, Lihi Zelnik-Manor, Pi...
NIPS
2007
15 years 8 months ago
Structured Learning with Approximate Inference
In many structured prediction problems, the highest-scoring labeling is hard to compute exactly, leading to the use of approximate inference methods. However, when inference is us...
Alex Kulesza, Fernando Pereira