Machine Learning

2016

  • Shikhar Sharma.  Action Recognition and Video Description using Visual Attention. 2016.  M.Sc. Thesis, University of Toronto, Toronto, Canada. [PDF]

2015

  • George E. Dahl.  Deep learning approaches to problems in speech recognition, computational chemistry, and natural language text processing.  2015.  Ph.D. Thesis, University of Toronto, Toronto, Canada. [PDF]

2014

  • Navdeep Jaitly. Exploring Deep Learning Methods for discovering features in speech signals. 2014.  Ph.D. Thesis, University of Toronto, Toronto, Canada. [PDF]
  • Tijmen Tieleman. Optimizing neural networks that generate images. 2014.  Ph.D. Thesis, University of Toronto, Toronto, Canada. [PDF]

2013

  • Yujia Li. Exploring Compositional High Order Pattern Potentials for Structured Output Learning. 2013. Master’s Thesis, University of Toronto, Toronto, Canada. [PDF]
  • Nitish Srivastava. Improving Neural Networks with Dropout. 2013. Master’s Thesis, University of Toronto, Toronto, Canada. [PDF]
  • Volodymyr Mnih. Machine Learning for Aerial Image Labeling. 2013. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]

2012

  • Ilya Sutskever. Training Recurrent Neural Networks. 2012. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]

2011

  • Patrick S. Li. ”Flobject” Analysis: Learning about Static Images from Motion. 2011. Master’s Thesis, Graduate Department of Electrical Engineering, University of Toronto.
  • Inmar Ella Givoni. Beyond Affinity Propagation: Message Passing Algorithms for Clustering. 2011. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]

2010

  • Andriy Mnih. Learning Distributed Representations for Statistical Language Modelling and Collaborative Filtering. 2010. Ph. D. Thesis, Department of Computer Science, University of Toronto.
  • Renqiang Min. Machine Learning Approaches to Biological Sequence and Phenotype Data Analysis. 2010. Ph. D. Thesis, Department of Computer Science, University of Toronto.
  • Vinod Nair. Visual Object Recognition Using Generative Models of Images. 2010. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]

2009

  • Dustin Lang. Astrometry.net: Automatic Recognition and Calibration of Astronomical Images. 2009. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]
  • Graham Taylor. Composable, Distributed-state Models for High-dimensional Time Series. 2009. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]
  • Jim C. Huang. Cumulative distribution networks: Inference, estimation and applications of graphical models for cumulative distribution functions. 2009. Ph. D. Thesis, Department of Electrical and Computer Engineering, University of Toronto. [PDF]
  • Ruslan R. Salakhutdinov. Learning Deep Generative Models. 2009. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]

2008

  • David Ross. Learning Probabilistic Models for Visual Motion. 2008. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]
  • Benjamin Marlin. Missing Data Problems in Machine Learning. 2008. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]
  • Edward Meeds. Nonparametric Bayesian Methods for Extracting Structure from Data. 2008. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]

2007

  • Xuming He. Learning Structured Prediction Models for Image Labeling. 2007. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]
  • Roland Memisevic. Non-linear Latent Factor Models for Revealing Structure in High-dimensional Data. 2007. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]
  • Ilya Sutskever. Nonlinear Multilayered Sequence Models. 2007. Master’s Thesis, Department of Computer Science, University of Toronto. [PDF]
  • Scott Leishman. Shape-Free Statistical Information in Optical Character Recognition. 2007. Master’s Thesis, Department of Computer Science, University of Toronto. [PDF]
  • Tijmen Tieleman. Some Investigations into Energy-based Models. 2007. Master’s Thesis, Department of Computer Science, University of Toronto. [PDF]

2006

  • Jennifer Listgarten. Analysis of Sibling Time Series Data: Alignment and Difference Detection. 2006. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]

2004

  • Benjamin Marlin. Collaborative Filtering: A Machine Learning Perspective. 2004. Master’s Thesis, Department of Computer Science, University of Toronto. [PDF]

2003

  • Yee Whye Teh. Bethe Free Energy and Contrastive Divergence Approximations for Undirected Graphical Models.2003. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]

2002

  • Brian Sallans. Reinforcement Learning for Factored Markov Decision Processes. 2002. Ph. D. Thesis, Department of Computer Science, University of Toronto. [PDF]

2000

  • Yee Whye Teh. Learning to Parse Images. 2000. Master’s Thesis, Department of Computer Science, University of Toronto. [PDF]