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ICML
2007
IEEE
14 years 8 months ago
Gradient boosting for kernelized output spaces
A general framework is proposed for gradient boosting in supervised learning problems where the loss function is defined using a kernel over the output space. It extends boosting ...
Florence d'Alché-Buc, Louis Wehenkel, Pierr...
AI
2009
Springer
14 years 2 months ago
Cost-Based Sampling of Individual Instances
In many practical domains, misclassification costs can differ greatly and may be represented by class ratios, however, most learning algorithms struggle with skewed class distrib...
William Klement, Peter A. Flach, Nathalie Japkowic...
ICALP
2009
Springer
14 years 2 months ago
Improved Bounds for Speed Scaling in Devices Obeying the Cube-Root Rule
Speed scaling is a power management technique that involves dynamically changing the speed of a processor. This gives rise to dualobjective scheduling problems, where the operating...
Nikhil Bansal, Ho-Leung Chan, Kirk Pruhs, Dmitriy ...
ICDE
2008
IEEE
110views Database» more  ICDE 2008»
14 years 8 months ago
Standing Out in a Crowd: Selecting Attributes for Maximum Visibility
In recent years, there has been significant interest in development of ranking functions and efficient top-k retrieval algorithms to help users in ad-hoc search and retrieval in da...
Muhammed Miah, Gautam Das, Vagelis Hristidis, Heik...
STOC
2007
ACM
146views Algorithms» more  STOC 2007»
14 years 7 months ago
Playing games with approximation algorithms
In an online linear optimization problem, on each period t, an online algorithm chooses st S from a fixed (possibly infinite) set S of feasible decisions. Nature (who may be adve...
Sham M. Kakade, Adam Tauman Kalai, Katrina Ligett