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Improving language understanding and summarization by leveraging auxiliary information through self-supervised or unsupervised learning
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Learning semantic types and relations from text
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Human behavior understanding from language through unsupervised modeling
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Experimental and computational explorations of different forms of plasticity in motor learning and stroke recovery
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Deep learning techniques for supervised pedestrian detection and critically-supervised object detection
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Modeling, learning, and leveraging similarity
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Learning the geometric structure of high dimensional data using the Tensor Voting Graph
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Video object segmentation and tracking with deep learning techniques
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Unsupervised learning of holistic 3D scene understanding
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Mode of visual perceptual learning: augmented Hebbian learning explains the function of feedback and beyond
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Human appearance analysis and synthesis using deep learning
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Labeling cost reduction techniques for deep learning: methodologies and applications
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Invariant representation learning for robust and fair predictions
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Learning to detect and adapt to unpredicted changes
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Structure learning for manifolds and multivariate time series
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Behavior understanding from speech under constrained conditions: exploring sparse networks, transfer and unsupervised learning
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Tensor learning for large-scale spatiotemporal analysis
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Learning invariant features in modulatory neural networks through conflict and ambiguity
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Understanding sources of variability in learning robust deep audio representations
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Mutual information estimation and its applications to machine learning
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Application of machine learning methods in genomic data analysis
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Learning distributed representations from network data and human navigation
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Explorations in the use of quantum annealers for machine learning
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Noise-robust spectro-temporal acoustic signature recognition using nonlinear Hebbian learning
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Evaluating machine learning tools for humanitarian road network mapping
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