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ICPR
2008
IEEE
16 years 7 months ago
Efficient user preference predictions using collaborative filtering
Two major challenges in collaborative filtering are the efficiency of the algorithms and the quality of the recommendations. A variety of machine learning methods have been applie...
C. Lee Giles, Yang Song
ICIP
2009
IEEE
16 years 7 months ago
Discrete Curvature Calculation For Fast Level Set Segmentation
Fast level set methods replace continuous PDEs by a discrete formulation, improving the execution times. The regularization in fast level set methods was so far handled indirectly...
DAC
2001
ACM
16 years 7 months ago
Future Performance Challenges in Nanometer Design
We highlight several fundamental challenges to designing highperformance integrated circuits in nanometer-scale technologies (i.e. drawn feature sizes < 100 nm). Dynamic power ...
Dennis Sylvester, Himanshu Kaul
ICML
2009
IEEE
16 years 7 months ago
Online feature elicitation in interactive optimization
Most models of utility elicitation in decision support and interactive optimization assume a predefined set of "catalog" features over which user preferences are express...
Craig Boutilier, Kevin Regan, Paolo Viappiani
ICML
2004
IEEE
16 years 7 months ago
Unifying collaborative and content-based filtering
Collaborative and content-based filtering are two paradigms that have been applied in the context of recommender systems and user preference prediction. This paper proposes a nove...
Justin Basilico, Thomas Hofmann