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» A Bayesian Metric for Evaluating Machine Learning Algorithms
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ICML
2008
IEEE
16 years 1 months ago
A worst-case comparison between temporal difference and residual gradient with linear function approximation
Residual gradient (RG) was proposed as an alternative to TD(0) for policy evaluation when function approximation is used, but there exists little formal analysis comparing them ex...
Lihong Li
TMI
2010
172views more  TMI 2010»
14 years 11 months ago
Comparison of AdaBoost and Support Vector Machines for Detecting Alzheimer's Disease Through Automated Hippocampal Segmentation
Abstract— We compared four automated methods for hippocampal segmentation using different machine learning algorithms (1) hierarchical AdaBoost, (2) Support Vector Machines (SVM)...
Jonathan H. Morra, Zhuowen Tu, Liana G. Apostolova...
110
Voted
HCI
2009
14 years 10 months ago
Did I Get It Right: Head Gestures Analysis for Human-Machine Interactions
This paper presents a system for another input modality in a multimodal human-machine interaction scenario. In addition to other common input modalities, e.g. speech, we extract he...
Jürgen Gast, Alexander Bannat, Tobias Rehrl, ...
78
Voted
ICML
2000
IEEE
16 years 1 months ago
Incremental Learning in SwiftFile
SwiftFile is an intelligent assistant that helps users organize their e-mail into folders. SwiftFile uses a text classifier to predict where each new message is likely to be filed...
Richard Segal, Jeffrey O. Kephart
122
Voted
MIR
2005
ACM
129views Multimedia» more  MIR 2005»
15 years 6 months ago
Tracking concept drifting with an online-optimized incremental learning framework
Concept drifting is an important and challenging research issue in the field of machine learning. This paper mainly addresses the issue of semantic concept drifting in time series...
Jun Wu, Dayong Ding, Xian-Sheng Hua, Bo Zhang