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» A Model of Inductive Bias Learning
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FUIN
2008
142views more  FUIN 2008»
13 years 8 months ago
Relational Transformation-based Tagging for Activity Recognition
Abstract. The ability to recognize human activities from sensory information is essential for developing the next generation of smart devices. Many human activity recognition tasks...
Niels Landwehr, Bernd Gutmann, Ingo Thon, Luc De R...
CHI
2009
ACM
14 years 9 months ago
A biologically inspired approach to learning multimodal commands and feedback for human-robot interaction
In this paper we describe a method to enable a robot to learn how a user gives commands and feedback to it by speech, prosody and touch. We propose a biologically inspired approac...
Anja Austermann, Seiji Yamada
EDM
2008
97views Data Mining» more  EDM 2008»
13 years 10 months ago
Using Item-type Performance Covariance to Improve the Skill Model of an Existing Tutor
Using data from an existing pre-algebra computer-based tutor, we analyzed the covariance of item-types with the goal of describing a more effective way to assign skill labels to it...
Philip I. Pavlik, Hao Cen, Lili Wu, Kenneth R. Koe...
BMCBI
2010
145views more  BMCBI 2010»
13 years 8 months ago
Clustering metagenomic sequences with interpolated Markov models
Background: Sequencing of environmental DNA (often called metagenomics) has shown tremendous potential to uncover the vast number of unknown microbes that cannot be cultured and s...
David R. Kelley, Steven L. Salzberg
APIN
2004
116views more  APIN 2004»
13 years 8 months ago
Neural Learning from Unbalanced Data
This paper describes the result of our study on neural learning to solve the classification problems in which data is unbalanced and noisy. We conducted the study on three differen...
Yi Lu Murphey, Hong Guo, Lee A. Feldkamp