Publications on Other Data Science Topics (including Basketball, Bibliometrics, Quantile Regression Trees, and Coevolution Models):

• H. S. Bhat, L.-H. Huang, and S. Rodriguez (2019)
  Driving Markov Chains to Desired Equilibria via Linear Programming.
  Proceedings of the 53rd Asilomar Conference on Signals, Systems, and Computers, pp. 741-748.
  [pdf] [proceedings]
• H. S. Bhat, R. W. M. A. Madushani, and S. Rawat (2017)
  Bayesian inference of stochastic pursuit models from basketball tracking data.
  In: Bayesian Statistics in Action. Springer Proceedings in Mathematics & Statistics. 194, pp.127-137.
  [pdf] [proceedings]
• T. Bergmann, R. Dale, N. Sattari, E. Heit, and H. S. Bhat (2016)
  The interdisciplinarity of collaborations in Cognitive Science.
  Cognitive Science, 41 (5), pp. 1412-1418.
  [journal]
• H. S. Bhat, L.-H. Huang, S. Rodriguez, R. Dale, and E. Heit (2015)
  Citation prediction using diverse features.
  IEEE Conference on Data Mining Workshop on Data Science and Big Data Analytics, pp. 589-596.
  [pdf] [proceedings]
• H. S. Bhat, N. Kumar, and G. J. Vaz (2015)
  Towards scalable quantile regression trees.
  Proc. 2015 IEEE Conference on Big Data, pp. 53-60.
  [pdf] [proceedings]
• H. S. Bhat, L.-H. Huang, and S. Rodriguez (2015)
  Learning stochastic models for basketball substitutions from play-by-play data.
  ECML/PKDD 2015 Workshop on Machine Learning and Data Mining for Sports Analytics (MLSA 2015).
  [pdf]
• P. J. Becich, B. P. Stark, H. S. Bhat, and D. H. Ardell (2013)
  CMCpy: Genetic code-message coevolution models in Python.
  Evolutionary Bioinformatics, 9, pp. 111-125.
  [journal]

Preprints

• H. S. Bhat and B. Sims (2012)
  InvestorRank and an inverse problem for PageRank.
  [pdf]
• H. S. Bhat and N. Kumar (2011)
  Comparing exact Bayesian and BIC Markov order classifiers.
  [pdf]
• H. S. Bhat and N. Kumar (2010)
  On the derivation of the Bayesian Information Criterion.
  [pdf]