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» Boosting as a Metaphor for Algorithm Design
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ICASSP
2011
IEEE
14 years 1 months ago
Application specific loss minimization using gradient boosting
Gradient boosting is a flexible machine learning technique that produces accurate predictions by combining many weak learners. In this work, we investigate its use in two applica...
Bin Zhang, Abhinav Sethy, Tara N. Sainath, Bhuvana...
ECCV
2008
Springer
14 years 11 months ago
Multiple Instance Boost Using Graph Embedding Based Decision Stump for Pedestrian Detection
Pedestrian detection in still image should handle the large appearance and stance variations arising from the articulated structure, various clothing of human as well as viewpoints...
Junbiao Pang, Qingming Huang, Shuqiang Jiang
GECCO
2004
Springer
120views Optimization» more  GECCO 2004»
15 years 3 months ago
Comparison of Selection Strategies for Evolutionary Quantum Circuit Design
Evolution of quantum circuits faces two major challenges: complex and huge search spaces and the high costs of simulating quantum circuits on conventional computers. In this paper ...
André Leier, Wolfgang Banzhaf
GIS
2010
ACM
14 years 8 months ago
Location disambiguation in local searches using gradient boosted decision trees
Local search is a specialization of the web search that allows users to submit geographically constrained queries. However, one of the challenges for local search engines is to un...
Ritesh Agrawal, James G. Shanahan
ICRA
2005
IEEE
122views Robotics» more  ICRA 2005»
15 years 3 months ago
Supervised Learning of Places from Range Data using AdaBoost
— This paper addresses the problem of classifying places in the environment of a mobile robot into semantic categories. We believe that semantic information about the type of pla...
Óscar Martínez Mozos, Cyrill Stachni...