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Robot life-long task learning from human demonstrations: a Bayesian approach
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Sparse representation models and applications to bioinformatics
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Novel variations of sparse representation techniques with applications
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Modeling, learning, and leveraging similarity
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Advanced machine learning techniques for video, social and biomedical data analytics
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Exploring complexity reduction in deep learning
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Novel algorithms for large scale supervised and one class learning
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Structure learning for manifolds and multivariate time series
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Experimental and computational explorations of different forms of plasticity in motor learning and stroke recovery
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Precision-based sample size reduction for Bayesian experimentation using Markov chain simulation
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Exploitation of sparse and low-rank structures for tracking and channel estimation
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Computational model of stroke therapy and long term recovery
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When AI helps wildlife conservation: learning adversary behavior in green security games
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Physics-based data-driven inference
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Noise benefits in expectation-maximization algorithms
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Learning contour statistics from natural images
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Clustering 16S rRNA sequences: an accurate and efficient approach
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Knowledge-driven representations of physiological signals: developing measurable indices of non-observable behavior
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Learning about the Internet through efficient sampling and aggregation
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A Bayesian model for the prediction of local policy outputs in California public sector labor relations
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Functional brain imaging:  Combining EEG and  fMRI using finite element and Bayesian methods
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Model selection principles and false discovery rate control
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Natural language description of emotion
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Towards tractable parameter -free statistical learning
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Exploiting latent reliability information for classification tasks
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