Nicholas Johnson
Ph.D. Candidate
Department of Computer Science and Engineering
University of Minnesota
njohnson [AT] cs.umn.edu
Google Scholar
Online Portfolio Selection Project

Currently on the job market. I am interested in postdoctoral positions in academia and industry.

Research

I am a Ph.D. candidate at the University of Minnesota being advised by Arindam Banerjee and Maria Gini. I'm broadly interested in Artificial Intelligence, Machine Learning, and Economics. My recent contributes in application have been designing online learning algorithms for stock market portfolio selection with particular emphasis on reducing exposure to risk through diversification and hedging strategies. My recent theoretical contributions have been on designing active sampling algorithms and showing sharper regret bounds for bandit problems.

Preprints

Publications

  1. Structured Stochastic Linear Bandits [arxiv]
    Accepted at the Workshop on Computational Frameworks for Personalization (ICML 2016).
    Nicholas Johnson, Vidyashankar Sivakumar, Arindam Banerjee

  2. Structured Hedging for Resource Allocations with Leverage [paper] [poster] [slides]
    In Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2015).
    Nicholas Johnson, Arindam Banerjee

  3. Online Resource Allocation with Structured Diversification [paper] [slides]
    In Proceedings of the 15th SIAM International Conference on Data Mining (SDM 2015).
    Nicholas Johnson, Arindam Banerjee

  4. SubPatCNV: approximate subspace pattern mining for mapping copy-number variations [paper] [Sourceforge]
    In BMC Bioinformatics, 16:16 2015.
    Nicholas Johnson, Huanan Zhang, Gang Fang, Vipin Kumar, Rui Kuang

  5. Online Portfolio Selection with Group Sparsity [paper] [poster]
    In Proceedings of the 28th Association for the Advancement of Artificial Intelligence Conference (AAAI 2014).
    Puja Das, Nicholas Johnson, Arindam Banerjee

  6. Fast Adaptive Learning in Repeated Stochastic Games by Game Abstraction [paper]
    In Proceedings of the 13th International Conference on Autonomous Agents and Multiagent Systems Conference (AAMAS 2014).
    Mohamed Elidrisi, Nicholas Johnson, Jacob Crandall, Maria Gini

  7. Online Lazy Updates for Portfolio Selection with Transaction Costs [paper] [poster]
    In Proceedings of the 27th Association for the Advancement of Artificial Intelligence Conference (AAAI 2013).
    Puja Das, Nicholas Johnson, Arindam Banerjee

  8. Approximate subspace pattern mining for mapping copy-number variations [poster]
    In Proceedings of the 3rd ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM-BCB 2012).
    Nicholas Johnson, Gang Fang, Rui Kuang

  9. Signed Network Propagation for Detecting Differential Gene Expressions and DNA Copy Number Variations [paper]
    In Proceedings of the 3rd ACM Conference on Bioinformatics, Computational Biology and Biomedicine (ACM-BCB 2012).
    Wei Zhang, Nicholas Johnson, Baolin Wu, Rui Kuang

  10. Fast Learning against Adaptive Adversarial Opponents [paper]
    In Proceedings of the Adaptive and Learning Agents Workshop (AAMAS 2012).
    Mohamed Elidrisi, Nicholas Johnson, Maria Gini

Awards

  1. Student Travel Award (ICML 2016)
    Awarded by: International Conference on Machine Learning

  2. Computer Science and Engineering Ph.D. Conference Travel Award, 2016
    Awarded by: University of Minnesota Computer Science and Engineering Department

  3. Doctoral Dissertation Award Nominee, 2015
    Nominated by: University of Minnesota Computer Science and Engineering Department

  4. Student Travel Award (KDD 2015)
    Awarded by: ACM SIGKDD Conference on Knowledge Discovery and Data Mining

  5. Computer Science and Engineering Ph.D. Conference Travel Award, 2015
    Awarded by: University of Minnesota Computer Science and Engineering Department

  6. Student Travel Award (SDM 2015)
    Awarded by: SIAM International Conference on Data Mining 2015

  7. Thank a Teacher Award, Fall 2013
    Awarded by: University of Minnesota Center for Teaching and Learning

  8. Minnesota Student Association Award for Graduate Student Teaching, 2012-2013
    Awarded by: Council of Graduate Students

  9. East Asia and Pacific Summer Institutes for U.S. Graduate Students (EAPSI) Fellowship
    Funded by: National Science Foundation (NSF)
    NSF Award 1311040
    Duration: June 12, 2013 - August 8, 2013
    Principal Investigator: Nicholas Johnson

Education

Service

Teaching

Learning to Predict blog (Not active)