Theses most similar to those of author Bouvrie, Jacob V

Multi-source contingency clustering (2004) read it

Learning from one example in machine vision by sharing probability densities

Miller, Erik G. (Erik Gundersen) (2002)

  • Advisor: Paul A. Viola
  • Department of Electrical Engineering and Computer Science
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Statistical modeling and analysis of audio-visual association in speech

Siracusa, Michael Richard, 1980- (2004)

  • Advisors: Darrell, Trevor; John W. Fisher
  • Department of Electrical Engineering and Computer Science
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Learning static object segmentation from motion segmentation

Ross, Michael G. (Michael Gregory), 1975- (2005)

  • Advisor: Keslie Pack Kaelbling
  • Department of Electrical Engineering and Computer Science
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The information regularization framework for semi-supervised learning

Corduneanu, Adrian (Adrian Dumitru), 1977- (2006)

  • Advisor: Jaakkola, Tommi S. (Tommi Sakari)
  • Department of Electrical Engineering and Computer Science
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Matching sets of features for efficient retrieval and recognition

Grauman, Kristen Lorraine, 1979- (2006)

  • Advisor: Darrell, Trevor
  • Department of Electrical Engineering and Computer Science
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Learning to transform time series with a few examples

Rahimi, Ali, 1976- (2005)

  • Advisor: Darrell, Trevor
  • Department of Electrical Engineering and Computer Science
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Probabilistic procrustean models for shape recognition with an application to robotic grasping

Glover, Jared Marshall (2008)

  • Advisors: Daniela Rus; Gaiano, Nicholas R. (Nicholas Roger)
  • Department of Electrical Engineering and Computer Science
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Context-based motion retrieval using vector space model

Zhang, Zhunping (2008)

  • Advisor: Jovan Popović
  • Department of Electrical Engineering and Computer Science
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Nonparametric Bayesian methods for supervised and unsupervised learning

Mansinghka, Vikash Kumar (2009)

  • Advisor: Joshua B. Tenenbaum
  • Department of Electrical Engineering and Computer Science
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A Bayesian latent time-series model for switching temporal interaction analysis

Dzunic, Zora (2016)

  • Advisor: John W. Fisher III
  • Department of Electrical Engineering and Computer Science
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Hierarchical learning : theory with applications in speech and vision (2009) read it

Nonparametric statistical methods for image segmentation and shape analysis

Kim, Junmo, 1976- (2005)

  • Advisor: Alan S. Willsky
  • Department of Electrical Engineering and Computer Science
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Multimodal dynamics : self-supervised learning in perceptual and motor systems

Coen, Michael Harlan (2006)

  • Advisors: Howard Shrobe; Whitman Richards
  • Department of Electrical Engineering and Computer Science
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Quantization and erasures in frame representations

Boufounos, Petros T., 1977- (2006)

  • Advisors:
  • Department of Electrical Engineering and Computer Science
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Learning to transform time series with a few examples

Rahimi, Ali, 1976- (2005)

  • Advisor: Darrell, Trevor
  • Department of Electrical Engineering and Computer Science
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The Gowers norm in the testing of Boolean functions

Chen, Victor Yen-Wen (2009)

  • Advisor: Madhu Sudan
  • Department of Mathematics
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Machine learning of image analysis with convolutional networks and topological constraints

Jain, Viren (2010)

  • Advisor: H. Sebastian Seung
  • Department of Brain and Cognitive Sciences
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Generalization and properties of the neural response

Wibisono, Andre Yohannes (2010)

  • Advisors: Lorenzo Rosasco; Tomaso Poggio
  • Department of Electrical Engineering and Computer Science
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Forward engineering object recognition : a scalable approach

Pinto, Nicolas (2011)

  • Advisor: James J. DiCarlo
  • Department of Brain and Cognitive Sciences
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Learning and enforcing diversity with Determinantal Point Processes

Mariet, Zelda Elaine (2016)

  • Advisors: Leslie Pack Kaelbling; Suvrit Sra
  • Department of Electrical Engineering and Computer Science
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Graphical models for visual object recognition and tracking

Sudderth, Erik B. (Erik Blaine), 1977- (2006)

  • Advisors: Alan S. Willsky; Freeman, William Tafel
  • Department of Electrical Engineering and Computer Science
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