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CVPR
2009
IEEE
15 years 5 months ago
What's It Going to Cost You?: Predicting Effort vs. Informativeness for Multi-Label Image Annotations
Active learning strategies can be useful when manual labeling effort is scarce, as they select the most informative examples to be annotated first. However, for visual category ...
Sudheendra Vijayanarasimhan (University of Texas a...
EDM
2011
197views Data Mining» more  EDM 2011»
12 years 10 months ago
Towards Improvements on Domain-independent Measurements for Collaborative Assessment
Assessment on collaborative student behavior is a longstanding issue in user modeling. Nowadays thanks to the proliferation of online learning and the vast amount of data on studen...
Antonio R. Anaya, Jesus Boticario
ISVC
2007
Springer
14 years 4 months ago
Boosting with Temporal Consistent Learners: An Application to Human Activity Recognition
We present a novel boosting algorithm where temporal consistency is addressed in a short-term way. Although temporal correlation of observed data may be an important cue for classi...
Pedro Canotilho Ribeiro, Plinio Moreno, José...
AIED
2009
Springer
14 years 4 months ago
Identifying strategies in user's exploratory learning behaviour for mathematical generalisation
Abstract. The nature of the activities that take place in Exploratory Learning Environments allow generating a variety of learner trajectories and makes difficult to develop a mod...
Mihaela Cocea, George D. Magoulas
ISI
2007
Springer
13 years 10 months ago
Host Based Intrusion Detection using Machine Learning
—Detecting unknown malicious code (malcode) is a challenging task. Current common solutions, such as anti-virus tools, rely heavily on prior explicit knowledge of specific instan...
Robert Moskovitch, Shay Pluderman, Ido Gus, Dima S...