Timezone: »
This paper presents Generalized Correspondence-LDA (GC-LDA), a generalization of the Correspondence-LDA model that allows for variable spatial representations to be associated with topics, and increased flexibility in terms of the strength of the correspondence between data types induced by the model. We present three variants of GC-LDA, each of which associates topics with a different spatial representation, and apply them to a corpus of neuroimaging data. In the context of this dataset, each topic corresponds to a functional brain region, where the region's spatial extent is captured by a probability distribution over neural activity, and the region's cognitive function is captured by a probability distribution over linguistic terms. We illustrate the qualitative improvements offered by GC-LDA in terms of the types of topics extracted with alternative spatial representations, as well as the model's ability to incorporate a-priori knowledge from the neuroimaging literature. We furthermore demonstrate that the novel features of GC-LDA improve predictions for missing data.
Author Information
Tim Rubin (Indiana University)
Sanmi Koyejo (UIUC)
Sanmi (Oluwasanmi) Koyejo an Assistant Professor in the Department of Computer Science at the University of Illinois at Urbana-Champaign. Koyejo's research interests are in the development and analysis of probabilistic and statistical machine learning techniques motivated by, and applied to various modern big data problems. He is particularly interested in the analysis of large scale neuroimaging data. Koyejo completed his Ph.D in Electrical Engineering at the University of Texas at Austin advised by Joydeep Ghosh, and completed postdoctoral research at Stanford University with a focus on developing Machine learning techniques for neuroimaging data. His postdoctoral research was primarily with Russell A. Poldrack and Pradeep Ravikumar. Koyejo has been the recipient of several awards including the outstanding NCE/ECE student award, a best student paper award from the conference on uncertainty in artificial intelligence (UAI) and a trainee award from the Organization for Human Brain Mapping (OHBM).
Michael Jones (Indiana University)
Tal Yarkoni (University of Texas at Austin)
More from the Same Authors
-
2020 Poster: CSER: Communication-efficient SGD with Error Reset »
Cong Xie · Shuai Zheng · Sanmi Koyejo · Indranil Gupta · Mu Li · Haibin Lin -
2020 Poster: Fairness with Overlapping Groups; a Probabilistic Perspective »
Forest Yang · Mouhamadou M Cisse · Sanmi Koyejo -
2020 Poster: Fair Performance Metric Elicitation »
Gaurush Hiranandani · Harikrishna Narasimhan · Sanmi Koyejo -
2019 Poster: Learning Sparse Distributions using Iterative Hard Thresholding »
Jacky Zhang · Rajiv Khanna · Anastasios Kyrillidis · Sanmi Koyejo -
2019 Poster: Multiclass Performance Metric Elicitation »
Gaurush Hiranandani · Shant Boodaghians · Ruta Mehta · Sanmi Koyejo -
2019 Tutorial: Representation Learning and Fairness »
Moustapha Cisse · Sanmi Koyejo -
2016 Oral: Examples are not enough, learn to criticize! Criticism for Interpretability »
Been Kim · Sanmi Koyejo · Rajiv Khanna -
2016 Poster: Preference Completion from Partial Rankings »
Suriya Gunasekar · Sanmi Koyejo · Joydeep Ghosh -
2016 Poster: Examples are not enough, learn to criticize! Criticism for Interpretability »
Been Kim · Sanmi Koyejo · Rajiv Khanna -
2015 Poster: Consistent Multilabel Classification »
Oluwasanmi Koyejo · Nagarajan Natarajan · Pradeep Ravikumar · Inderjit Dhillon -
2014 Poster: On Prior Distributions and Approximate Inference for Structured Variables »
Sanmi Koyejo · Rajiv Khanna · Joydeep Ghosh · Russell Poldrack -
2014 Poster: Consistent Binary Classification with Generalized Performance Metrics »
Sanmi Koyejo · Nagarajan Natarajan · Pradeep Ravikumar · Inderjit Dhillon -
2014 Spotlight: Consistent Binary Classification with Generalized Performance Metrics »
Sanmi Koyejo · Nagarajan Natarajan · Pradeep Ravikumar · Inderjit Dhillon -
2014 Poster: Sparse Bayesian structure learning with dependent relevance determination prior »
Anqi Wu · Mijung Park · Sanmi Koyejo · Jonathan W Pillow -
2010 Spotlight: Improving Human Judgments by Decontaminating Sequential Dependencies »
Michael Mozer · Harold Pashler · Matthew Wilder · Robert Lindsey · Matt Jones · Michael Jones -
2010 Poster: Improving Human Judgments by Decontaminating Sequential Dependencies »
Michael Mozer · Harold Pashler · Matthew Wilder · Robert Lindsey · Matt Jones · Michael Jones -
2006 Poster: Context Effects in Category Learning: An Investigation of Four Probabilistic Models »
Michael Mozer · Michael Jones · Michael Shettel