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» Learning to Select a Ranking Function
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NIPS
2001
14 years 10 months ago
Global Coordination of Local Linear Models
High dimensional data that lies on or near a low dimensional manifold can be described by a collection of local linear models. Such a description, however, does not provide a glob...
Sam T. Roweis, Lawrence K. Saul, Geoffrey E. Hinto...
CORR
2006
Springer
153views Education» more  CORR 2006»
14 years 9 months ago
Genetic Programming, Validation Sets, and Parsimony Pressure
Fitness functions based on test cases are very common in Genetic Programming (GP). This process can be assimilated to a learning task, with the inference of models from a limited n...
Christian Gagné, Marc Schoenauer, Marc Pari...
KDD
2007
ACM
177views Data Mining» more  KDD 2007»
15 years 9 months ago
Mining optimal decision trees from itemset lattices
We present DL8, an exact algorithm for finding a decision tree that optimizes a ranking function under size, depth, accuracy and leaf constraints. Because the discovery of optimal...
Élisa Fromont, Siegfried Nijssen
IROS
2008
IEEE
238views Robotics» more  IROS 2008»
15 years 3 months ago
Shape-guided superpixel grouping for trail detection and tracking
Abstract— We describe a framework for detecting and tracking continuous ”trails” in images and image sequences for autonomous robot navigation. Continuous trails are extended...
Christopher Rasmussen, Donald Scott
ACCV
2007
Springer
14 years 11 months ago
A Convex Programming Approach to the Trace Quotient Problem
Abstract. The trace quotient problem arises in many applications in pattern classification and computer vision, e.g., manifold learning, low-dimension embedding, etc. The task is ...
Chunhua Shen, Hongdong Li, Michael J. Brooks