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Edited Series

Book Chapters

  • S. McQuade and C.Monteleoni, “Spatiotemporal Global Climate Model Tracking,” Chapter 3, in Large-Scale Machine Learning in the Earth Sciences, Srivastava, Nemani, Steinhaeuser (Eds.), Data Mining and Knowledge Discovery Series, V. Kumar (Series Ed.), Chapman & Hall/CRC, pp. 33–54, August 2017. Invited.
  • C. Tang and C. Monteleoni, “On the Convergence Rate of Stochastic Gradient Descent for Strongly Convex Functions,” in Regularization, Optimization, Kernels, and Support Vector Machines. Johan A. K. Suykens, Marco Signoretto, and Andreas Argyriou. (Eds.), CRC Press, Taylor & Francis Group. Chapter 7, pp. 159–175, 2014.  Invited. 
  • C. Monteleoni, G.A. Schmidt, F. Alexander, A. Niculescu-Mizil, K. Steinhaeuser, M. TippettA. Banerjee, M.B. Blumenthal, A.R. Ganguly, J.E. Smerdon, and M. Tedesco, “Climate Informatics,” in Computational Intelligent Data Analysis for Sustainable Development; Data Mining and Knowledge Discovery Series. Yu, T., Chawla, N., and Simoff, S. (Eds.), CRC Press, Taylor & Francis Group. Chapter 4, pp. 81–126, 2013.  Invited.

Journals & Periodicals

  • L. Alexander, S. Das, Z. Ives, H.V. Jagadish, and C. Monteleoni, “Research Challenges in Financial Data Modeling and Analysis.” In Big Data, Sep 2017, 5(3): 177-188.
  • R. L. Glicksman, D. L. Markell, and C. Monteleoni, “Technological Innovation, Data Analytics, and Environmental Enforcement,” in Ecology Law Quarterly, University of California, Berkeley, School of Law, Volume 44, Issue 1, 2017.  Invited. 
  • A. Choromanska, K. Choromanski, G. Jagannathan, and C. Monteleoni, “Differentially-Private Learning of Low Dimensional Manifolds,” in Theoretical Computer Science (TCS), Volume 620, pp. 91–104, March 2016.  Invited. 
  • C. Tang and C. Monteleoni, “Can Topic Modeling Shed Light on Climate Extremes?” in IEEE Computing in Science and Engineering (CISE) Magazine, Special Issue on Computing & Climate. Vol. 17, no. 6, pp. 43–52, Nov./Dec. 2015. 
  • C. Monteleoni, G. Schmidt, S. McQuade, “Climate Informatics: Accelerating Discovery in Climate Science with Machine Learning,” in IEEE Computing in Science and Engineering (CISE) Magazine, Special Issue on Machine Learning. Vol. 15, no. 5, pp. 32–40, Sept.-Oct. 2013.  Invited.
  • C. Monteleoni, G. Schmidt, S. Saroha, and E. Asplund, “Tracking Climate Models,” in Journal of Statistical Analysis and Data Mining:  Special Issue: Best of CIDU 2010. Volume 4, Issue 4, pp. 72–392, August 2011.  Invited.
  • K. Chaudhuri, C. Monteleoni, and A. Sarwate, “Differentially Private Empirical Risk Minimization,” in Journal of Machine Learning Research (JMLR), 12(Mar):1069–1109, 2011.  
  • S. DasguptaA.T. Kalai, and C. Monteleoni, “Analysis of Perceptron-Based Active Learning,” in Journal of Machine Learning Research (JMLR), 10(Feb):281–
    299, 2009. 

Refereed Proceedings

Workshop Papers