10 Result(s)
within
English
Artificial Intelligence
Information Storage and Retrieval
M. **gliang
Chapter
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Chapter and Conference Paper
User Perceptions of a Virtual Human Over Mobile Video Chat Interactions
We believe that virtual humans, presented over video chat services, such as Skype, and delivered using smartphones, can be an effective way to deliver innovative applications where social interactions are impo...
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Chapter and Conference Paper
Discriminative Interpolation for Classification of Functional Data
The modus operandi for machine learning is to represent data as feature vectors and then proceed with training algorithms that seek to optimally partition the feature space
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Chapter and Conference Paper
Spá: A Web-Based Viewer for Text Mining in Evidence Based Medicine
Summarizing the evidence about medical interventions is an immense undertaking, in part because unstructured Portable Document Format (PDF) documents remain the main vehicle for disseminating scientific findin...
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Chapter and Conference Paper
Revisit Behavior in Social Media: The Phoenix-R Model and Discoveries
How many listens will an artist receive on a online radio? How about plays on a YouTube video? How many of these visits are new or returning users? Modeling and mining popularity dynamics of social activity ha...
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Chapter and Conference Paper
Students, Teachers, Exams and MOOCs: Predicting and Optimizing Attainment in Web-Based Education Using a Probabilistic Graphical Model
We propose a probabilistic graphical model for predicting student attainment in web-based education. We empirically evaluate our model on a crowdsourced dataset with students and teachers; Teachers prepared le...
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Chapter and Conference Paper
Decision-Theoretic Sparsification for Gaussian Process Preference Learning
We propose a decision-theoretic sparsification method for Gaussian process preference learning. This method overcomes the loss-insensitive nature of popular sparsification approaches such as the Informative Ve...
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Chapter and Conference Paper
Adaptive Parallel/Serial Sampling Mechanisms for Particle Filtering in Dynamic Bayesian Networks
Monitoring the variables of real world dynamical systems is a difficult task due to their inherent complexity and uncertainty. Particle Filters (PF) perform that task, yielding probability distribution over th...
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Chapter and Conference Paper
Parallel Subspace Sampling for Particle Filtering in Dynamic Bayesian Networks
Monitoring the variables of real world dynamic systems is a difficult task due to their inherent complexity and uncertainty. Particle Filters (PF) perform that task, yielding probability distribution over the ...
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Chapter and Conference Paper
Leveraging Higher Order Dependencies between Features for Text Classification
Traditional machine learning methods only consider relationships between feature values within individual data instances while disregarding the dependencies that link features across instances. In this work, w...
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Chapter and Conference Paper
Integrating Novel Class Detection with Classification for Concept-Drifting Data Streams
In a typical data stream classification task, it is assumed that the total number of classes are fixed. This assumption may not be valid in a real streaming environment, where new classes may evolve. Tradition...
