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PLDI
2011
ACM
14 years 5 months ago
The tao of parallelism in algorithms
For more than thirty years, the parallel programming community has used the dependence graph as the main abstraction for reasoning about and exploiting parallelism in “regularâ€...
Keshav Pingali, Donald Nguyen, Milind Kulkarni, Ma...
ICML
2009
IEEE
16 years 3 months ago
SimpleNPKL: simple non-parametric kernel learning
Previous studies of Non-Parametric Kernel (NPK) learning usually reduce to solving some Semi-Definite Programming (SDP) problem by a standard SDP solver. However, time complexity ...
Jinfeng Zhuang, Ivor W. Tsang, Steven C. H. Hoi
ICML
2008
IEEE
16 years 3 months ago
Fast solvers and efficient implementations for distance metric learning
In this paper we study how to improve nearest neighbor classification by learning a Mahalanobis distance metric. We build on a recently proposed framework for distance metric lear...
Kilian Q. Weinberger, Lawrence K. Saul
ICML
2005
IEEE
16 years 3 months ago
Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Xiaojin Zhu, John D. Lafferty
INDIASE
2009
ACM
15 years 9 months ago
An effective learning environment for teaching problem solving in software architecture
A software architect engages in solving Software Engineering (SE) problems throughout his career. Thus inculcating problem solving skills should be one of the learning objectives ...
Kirti Garg, Vasudeva Varma