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KDD
2010
ACM
257views Data Mining» more  KDD 2010»
14 years 1 months ago
Multi-task learning for boosting with application to web search ranking
In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing...
Olivier Chapelle, Pannagadatta K. Shivaswamy, Srin...
ECCV
2008
Springer
13 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
ICPR
2010
IEEE
13 years 8 months ago
Boosting Bayesian MAP Classification
In this paper we redefine and generalize the classic k-nearest neighbors (k-NN) voting rule in a Bayesian maximum-a-posteriori (MAP) framework. Therefore, annotated examples are u...
Paolo Piro, Richard Nock, Frank Nielsen, Michel Ba...
SOCIALCOM
2010
13 years 7 months ago
Learning to Predict Ad Clicks Based on Boosted Collaborative Filtering
This paper addresses the topic of social advertising, which refers to the allocation of ads based on individual user social information and behaviors. As social network services (e...
Teng-Kai Fan, Chia-Hui Chang
INTERSPEECH
2010
13 years 4 months ago
Boosted mixture learning of Gaussian mixture HMMs for speech recognition
In this paper, we propose a novel boosted mixture learning (BML) framework for Gaussian mixture HMMs in speech recognition. BML is an incremental method to learn mixture models fo...
Jun Du, Yu Hu, Hui Jiang