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RESEARCH:
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I have worked on exploiting
structure for statistical estimation and pattern localization.
Currently, I am working on optimal design and active learning for
Ising and infection models, structured sparsity, and density
estimation over large graphs.
My advisors are Aarti Singh
and Alessandro
Rinaldo.
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| THESIS PROPOSAL: |
Graph Structured Statistical Inference
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BIO:
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I am currently a Ph.D student in Machine Learning and Statistics at
Carnegie Mellon University. I have a masters in Statistics from CMU and bachelors in Math and
Physics from the Ohio State University.
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PUBLICATIONS:
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Detecting activations over graphs using spanning tree wavelet bases
(arXiv)
J. Sharpnack, A. Krishnamurthy, and A. Singh, submitted for publication, 2012.
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Changepoint detection over graphs with the spectral scan statistic
(arXiv)
J. Sharpnack, A. Rinaldo, and A. Singh, submitted for publication, 2012.
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Variance function estimation in high-dimensions
(pdf)
M. Kolar, and J. Sharpnack, International Conference of Machine
Learning, ICML 2012, Accepted with Oral Presentation.
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Sparsistency of the edge lasso over graphs
(pdf)
J. Sharpnack, A. Rinaldo, and A. Singh, AIStats (JMLR WCP), 22:1028–1036, 2012.
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Identifying graph-structured activation patterns in networks
(pdf)
J. Sharpnack, and A. Singh, Neural Information Processing Systems,
NIPS 2010, Accepted with Oral Presentation.
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