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ICRA
2009
IEEE
179views Robotics» more  ICRA 2009»
13 years 11 months ago
Automatic weight learning for multiple data sources when learning from demonstration
— Traditional approaches to programming robots are generally inaccessible to non-robotics-experts. A promising exception is the Learning from Demonstration paradigm. Here a polic...
Brenna Argall, Brett Browning, Manuela M. Veloso
CSB
2005
IEEE
189views Bioinformatics» more  CSB 2005»
13 years 10 months ago
Learning Yeast Gene Functions from Heterogeneous Sources of Data Using Hybrid Weighted Bayesian Networks
We developed a machine learning system for determining gene functions from heterogeneous sources of data sets using a Weighted Naive Bayesian Network (WNB). The knowledge of gene ...
Xutao Deng, Huimin Geng, Hesham H. Ali
KDD
2004
ACM
164views Data Mining» more  KDD 2004»
14 years 4 months ago
Ordering patterns by combining opinions from multiple sources
Pattern ordering is an important task in data mining because the number of patterns extracted by standard data mining algorithms often exceeds our capacity to manually analyze the...
Pang-Ning Tan, Rong Jin
MM
2004
ACM
142views Multimedia» more  MM 2004»
13 years 9 months ago
Learning query-class dependent weights in automatic video retrieval
Combining retrieval results from multiple modalities plays a crucial role for video retrieval systems, especially for automatic video retrieval systems without any user feedback a...
Rong Yan, Jun Yang 0003, Alexander G. Hauptmann
IROS
2008
IEEE
203views Robotics» more  IROS 2008»
13 years 10 months ago
Learning equivalent action choices from demonstration
Abstract— In their interactions with the world robots inevitably face equivalent action choices, situations in which multiple actions are equivalently applicable. In this paper, ...
Sonia Chernova, Manuela M. Veloso