Ph.D Thesis

  1. Advances in Spectral Learning with Applications to Text Analysis and Brain Imaging.
    Winner of the 2015 Morris & Dorothy Rubinoff Best Dissertation Award.
    Thesis Committee (including advisors):
    Lyle Ungar, James Gee, Dean Foster, Mitch Marcus, Mark Liberman, Chris Callison-Burch and Tom Mitchell (External, Carnegie Mellon U.)
    Department of Computer & Information Science, University of Pennsylvania, July 2014.
    Thesis|BibTeX



                                                                                                         Working Papers

  1. Digital Paywall Design: Effects on Subscription Rates & Cross-Channel Demand
    (with Sinan Aral)
    Working Paper
    Under Review |BibTeX
    Presentation at NBER Summer Institute on Economics of IT and Digitization.
    Winner of Runner-up best paper award at WISE 2016.

  2. Influence Maximization Revisited
    (with Sinan Aral)
    Under Review at Proceedings of National Academy of Sciences (PNAS)

  3. Unpacking Novelty: Anatomy of vision advantanges
    (with Sinan Aral)
    Working Paper
    Paper (Preprint Available on request) |BibTeX

Note:
  • JMLR (Impact Factor: 3.42) is the highest impact-factor Machine Learning journal.
  • NeuroImage (Impact Factor: 6.36) is the highest impact-factor quantitative methods Brain Imaging journal.


  •                                                                                                          Journal Papers

    1. Eigenwords: Spectral Word Embeddings
      Paramveer Dhillon, Dean Foster and Lyle Ungar.
      JMLR (Journal of Machine Learning Research 16), Dec. 2015
      Paper|BibTeX

    2. Subject-Specific Functional Parcellation via Prior Based Eigenanatomy
      Paramveer Dhillon, David Wolk, Sandhitsu Das, Lyle Ungar, James Gee and Brian Avants.
      NeuroImage, 2014
      Paper|BibTeX

    3. A Risk Comparison of Ordinary Least Squares vs Ridge Regression
      Paramveer Dhillon, Dean Foster, Sham Kakade and Lyle Ungar.
      JMLR (Journal of Machine Learning Research 14), June 2013
      Paper|BibTeX

    4. Minimum Description Length Penalization for Group and Multi-Task Sparse Learning
      Paramveer Dhillon, Dean Foster and Lyle Ungar.
      JMLR (Journal of Machine Learning Research 12), Feb. 2011
      Paper |BibTeX

                                                              Conference Papers (Highly Competitive: Typical Acceptance Rate < 30%)

    1. New Subsampling Algorithms for Fast Least Squares Regression
      Paramveer Dhillon, Yichao Lu, Dean Foster and Lyle Ungar.
      NIPS 2013 (Advances in Neural Information Processing Systems 26), Lake Tahoe, NV, U.S.A.
      Paper | Supplementary Material | BibTeX

    2. Faster Ridge Regression via the Subsampled Randomized Hadamard Transform
      Yichao Lu, Paramveer Dhillon, Dean Foster and Lyle Ungar.
      NIPS 2013 (Advances in Neural Information Processing Systems 26), Lake Tahoe, NV, U.S.A.
      Paper | Supplementary Material | BibTeX

    3. Two Step CCA: A new spectral method for estimating vector models of words
      Paramveer Dhillon, Jordan Rodu, Dean Foster and Lyle Ungar.
      ICML 2012 (International Conference on Machine Learning), Edinburgh, U.K.
      Paper (Please see the updated JMLR version above) | Supplementary Material | BibTeX

    4. Spectral Dependency Parsing with Latent Variables
      Paramveer Dhillon, Jordan Rodu, Michael Collins, Dean Foster and Lyle Ungar.
      EMNLP-CoNLL 2012 (Joint International Conference on Empirical Methods in Natural Language Processing & Conference on Natural Language Learning), Jeju, Korea.
      Paper | BibTeX

    5. Partial Sparse Canonical Correlation Analysis (PSCCA) for population studies in Medical Imaging
      Paramveer Dhillon, Brian Avants, Lyle Ungar and James Gee.
      ISBI 2012 (IEEE International Symposium on Biomedical Imaging), Barcelona, Spain.
      Paper | BibTeX

    6. Eigenanatomy improves detection power for longitudinal cortical change
      Brian Avants, Paramveer Dhillon, Benjamin Kandel, Philip Cook, Corey McMillan, Murray Grossman and James Gee.
      MICCAI 2012 (International Conference on Medical Image Computing and Computer Assisted Intervention), Nice, France.
      Paper | BibTeX

    7. Deterministic Annealing for Semi-Supervised Structured Output Learning
      Paramveer Dhillon, Sathiya Keerthi, Olivier Chapelle, Kedar Bellare and S. Sundararajan.
      AISTATS 2012 (International Conference on Artificial Intelligence and Statistics), La Palma, Canary Islands.
      Paper | BibTeX

    8. Metric Learning for Graph-based Domain Adaptation
      Paramveer Dhillon, Partha Talukdar and Koby Crammer.
      COLING 2012 (International Conference on Computational Linguistics), Mumbai, India.
      Paper |BibTeX

    9. Multi-View Learning of Word Embeddings via CCA
      Paramveer Dhillon, Dean Foster and Lyle Ungar.
      NIPS 2011 (Advances in Neural Information Processing Systems 24), Granada, Spain.
      Paper (Please see the updated JMLR version above) | Supplementary Material | BibTeX

    10. Semi-supervised Multi-task Learning of Structured Prediction Models for Web Information Extraction
      Paramveer Dhillon, S. Sundararajan and S. Sathiya Keerthi.
      CIKM 2011 (ACM International Conference on Information and Knowledge Management), Glasgow, U.K.
      Paper |BibTeX

    11. A New Approach to Lexical Disambiguation of Arabic Text
      Rushin Shah, Paramveer Dhillon, Mark Liberman, Dean Foster, Mohamed Maamouri and Lyle Ungar.
      EMNLP 2010 (International Conference on Empirical Methods in Natural Language Processing), Cambridge, MA, U.S.A.
      Paper |BibTeX

    12. Learning Better Data Representation using Inference-Driven Metric Learning (IDML)
      Paramveer Dhillon, Partha Pratim Talukdar and Koby Crammer.
      ACL 2010 (Annual Meeting of the Association of Computational Linguistics), Uppsala, Sweden.
      Paper | BibTeX

    13. Feature Selection using Multiple Streams
      Paramveer Dhillon, Dean Foster and Lyle Ungar.
      AISTATS 2010 (International Conference on Artificial Intelligence and Statistics), Sardinia, Italy.
      Paper | BibTeX

    14. Transfer Learning, Feature Selection and Word Sense Disambiguation
      Paramveer Dhillon and Lyle Ungar.
      ACL-IJCNLP 2009 (Annual Meeting of the Association of Computational Linguistics), Singapore.
      Paper | BibTeX

    15. Multi-Task Feature Selection using the Multiple Inclusion Criterion (MIC)
      Paramveer Dhillon, Brian Tomasik, Dean Foster and Lyle Ungar.
      ECML-PKDD 2009 (European Conference on Machine Learning), Bled, Slovenia.
      Paper | BibTeX

    16. Efficient Feature Selection in the Presence of Multiple Feature Classes
      Paramveer Dhillon, Dean Foster and Lyle Ungar.
      ICDM 2008 (IEEE International Conference on Data Mining), Pisa, Italy.
      Paper | BibTeX

                                                              Workshop/Student Symposium Papers (Less Competitive: Typical Acceptance Rate > 30%)

    1. Learning to Explore Scientific Workflow Repositories
      Julia Stoyanovich, Paramveer Dhillon, Brian Lyons and Susan Davidson.
      SSDBM 2013 (International Conference on Scientific and Statistical Database Management), Baltimore, MD, U.S.A.
      Paper |BibTeX

    2. Anatomically-Constrained PCA for Image Parcellation
      Paramveer Dhillon, James Gee, Lyle Ungar and Brian Avants.
      PRNI 2013 (3rd International Workshop on Pattern Recognition in NeuroImaging), Philadelphia, PA, U.S.A.
      Paper |BibTeX

    3. Inference Driven Metric Learning for Graph Construction
      Paramveer Dhillon, Partha Pratim Talukdar and Koby Crammer.
      NESCAI 2010 (North East Student Symposium on Artificial Intelligence), Amherst, MA, U.S.A.
      Paper |BibTeX

    4. Combining Appearance and Motion for Human Action Classification in Videos
      Paramveer Dhillon, Sebastian Nowozin and Christoph Lampert.
      ViSU 2009 (International Workshop on Visual Scene Understanding at CVPR), Miami, Florida, U.S.A.
      Paper |BibTeX

    5. Robust Real-Time Face Tracking Using an Active Camera
      Paramveer Dhillon
      International Workshop on CISIS (Springer-Lecture Notes in Computer Science (LNCS)), Burgos, Spain
      Paper |BibTeX