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TSP
2010
15 years 1 months ago
Distributed sparse linear regression
The Lasso is a popular technique for joint estimation and continuous variable selection, especially well-suited for sparse and possibly under-determined linear regression problems....
Gonzalo Mateos, Juan Andrés Bazerque, Georg...
ECCV
2002
Springer
16 years 8 months ago
Hyperdynamics Importance Sampling
Sequential random sampling (`Markov Chain Monte-Carlo') is a popular strategy for many vision problems involving multimodal distributions over high-dimensional parameter spac...
Cristian Sminchisescu, Bill Triggs
WSDM
2010
ACM
166views Data Mining» more  WSDM 2010»
16 years 4 months ago
Ranking Mechanisms in Twitter-Like Forums
We study the problem of designing a mechanism to rank items in forums by making use of the user reviews such as thumb and star ratings. We compare mechanisms where forum users rat...
Anish Das Sarma, Atish Das Sarma, Sreenivas Gollap...
AIPS
2010
15 years 9 months ago
Classical Planning in MDP Heuristics: with a Little Help from Generalization
Heuristic functions make MDP solvers practical by reducing their time and memory requirements. Some of the most effective heuristics (e.g., the FF heuristic function) first determ...
Andrey Kolobov, Mausam, Daniel S. Weld
NIPS
2007
15 years 8 months ago
A New View of Automatic Relevance Determination
Automatic relevance determination (ARD) and the closely-related sparse Bayesian learning (SBL) framework are effective tools for pruning large numbers of irrelevant features leadi...
David P. Wipf, Srikantan S. Nagarajan