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» Termination Analysis with Algorithmic Learning
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133
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CIARP
2007
Springer
15 years 10 months ago
Image Segmentation Using Automatic Seeded Region Growing and Instance-Based Learning
Segmentation through seeded region growing is widely used because it is fast, robust and free of tuning parameters. However, the seeded region growing algorithm requires an automat...
Octavio Gómez, Jesús A. Gonzá...
128
Voted
NIPS
2007
15 years 5 months ago
A Game-Theoretic Approach to Apprenticeship Learning
We study the problem of an apprentice learning to behave in an environment with an unknown reward function by observing the behavior of an expert. We follow on the work of Abbeel ...
Umar Syed, Robert E. Schapire
SODA
2008
ACM
184views Algorithms» more  SODA 2008»
15 years 5 months ago
Coresets, sparse greedy approximation, and the Frank-Wolfe algorithm
The problem of maximizing a concave function f(x) in a simplex S can be solved approximately by a simple greedy algorithm. For given k, the algorithm can find a point x(k) on a k-...
Kenneth L. Clarkson
125
Voted
ICML
2007
IEEE
16 years 4 months ago
Local learning projections
This paper presents a Local Learning Projection (LLP) approach for linear dimensionality reduction. We first point out that the well known Principal Component Analysis (PCA) essen...
Bernhard Schölkopf, Kai Yu, Mingrui Wu, Shipe...
ICDM
2009
IEEE
120views Data Mining» more  ICDM 2009»
15 years 10 months ago
Least Square Incremental Linear Discriminant Analysis
Abstract—Linear discriminant analysis (LDA) is a wellknown dimension reduction approach, which projects highdimensional data into a low-dimensional space with the best separation...
Li-Ping Liu, Yuan Jiang, Zhi-Hua Zhou