Publications

  •  Thesis
  •  Journal article
  •  Conference article
  •  Workshop article
  •  Demonstration
  •  Preprint

2021

2020

2019

  • [Conference article (peer-reviewed)] D. Basu, P. Senellart, and S. Bressan, BelMan: An Information Geometric Approach to Stochastic Bandits. In Proc. ECML-PKDD, September,2019. (PDF | Code)
  • [Workshop] N. A. Arafat, D. Basu, and S. Bressan, ε-net Induced Lazy Witness Complex on Graphs. In Proc. ATDA at ECML-PKDD, September, 2019. (PDF)
  • [Preprint] D. Basu, C. Dimitrakakis, and A. C. Y. Toussou, Differential Privacy For Multi-Armed Bandits: What Is It And What Is Its Cost?. In CORR, abs/1905.12298, 2019. (PDF)
  • [Preprint] A. C. Y. Toussou, D. Basu, and C. Dimitrakakis, Near Optimal Reinforcement Learning Using Bayesian Quantiles. In CORR, abs/1906.09114, 2019. (PDF)
  • [Preprint] A. C. Y. Toussou, D. Basu, and C. Dimitrakakis, Near Optimal Reinforcement Learning using Empirical Bernstein Inequalities. In CORR, abs/1906.09114, 2019. (PDF)
  • [Conference article (peer-reviewed)] N. A. Arafat, D. Basu, and S. Bressan, Topological Data Analysis with ε-Net Induced Lazy Witness Complex. In Proc. DEXA, Linz, Austria, August, 2019. (PDF)
  • [Conference article (peer-reviewed)] A. Dandekar, D. Basu, and S. Bressan, Differentially Private Non-parametric Machine Learning as a Service. In Proc. DEXA, Linz, Austria, August, 2019. (PDF)
  • [Conference article (peer-reviewed)] A. Dandekar, D. Basu, T. Kister, G. S. Poh, J. Xu, and S. Bressan, Privacy as a Service: Publishing Data and Models. In Proc. DASFAA, Thailand, April, 2019. (PDF)
  • [Preprint] A. Dandekar, D. Basu, and S. Bressan, Evaluation of Differentially Private Non-parametric Machine Learning as a Service. In DSpace@NUS, 2019. (PDF)
  • [Journal article (peer-reviewed)] D. Basu, X. Wang, Y. Hong, H. Chen, and S. Bressan, Learn-as-you-go with Megh: Efficient Live Migration of Virtual Machines. In IEEE Transactions on Parallel and Distributed Systems, January, 2019. (PDF)

2018

  • [PhD Thesis] D. Basu, Learning to Make Decisions with Incomplete Information: Reinforcement Learning, Information Geometry, and Real-Life Applications. In ScholarBank@NUS, October 2018. (PDF)
  • [Conference article (peer-reviewed)] A. Dandekar, D. Basu, and S. Bressan, Differential Privacy for Regularised Linear Regression. In Proc. DEXA, Regensburg, Germany September 2018. (PDF)
  • [Preprint] D. Basu, P. Senellart, and S. Bressan, BelMan: Bayesian Bandits on the Belief–Reward Manifold. arXiv preprint arXiv:1805.01627 2018. (PDF | Code)

2017

2016

2015

2014

2013

  • [Conference article (peer-reviewed)] S. Debchoudhury, D. Basu, K. Z. Gao, and P. N. Sugnathan, Load Information Based Priority Dependent Heuristic for Manpower Scheduling Problem in Remanufacturing. In Proc. SEMCCO, Chennai, India, December 2013. (PDF)
  • [Conference article (peer-reviewed)] D. Basu, S. Debchoudhury, K. Z. Gao, and P. N. Sugnathan, A Novel Improved Discrete ABC Algorithm for Manpower Scheduling Problem in Remanufacturing. In Proc. SEMCCO, Chennai, India, December 2013. (PDF)

Thesis

  • [PhD Thesis] D. Basu, Learning to Make Decisions with Incomplete Information: Reinforcement Learning, Information Geometry, and Real-Life Applications. In ScholarBank, NUS, October 2018. (PDF)

Journal articles

Conference articles

Workshop Articles

Peer-reviewed

  • [Workshop] A. Dandekar, D. Basu, and S. Bressan, Differential Privacy at Risk: Bridging Randomness and Privacy Budget. In Proc. AAAI Workshop on Privacy Preserving AI (PPAI), Februray, 2020. (PDF)
  • [Workshop] N. A. Arafat, D. Basu, and S. Bressan, ε-net Induced Lazy Witness Complex on Graphs. In Proc. ATDA at ECML-PKDD, September, 2019. (PDF)

Preprint (Archived Articles)

Demonstration

  • [Conference article (peer-reviewed)] J. Wang, I. Trummer, and D. Basu, Demonstrating UDO: A Unified Approach for Optimizing Transaction Code, Physical Design, and System Parameters via Reinforcement Learning. In Proc. SIGMOD, June, 2021. (PDF)
  • [Conference article (peer-reviewed)] A. Dandekar, D. Basu, T. Kister, G. S. Poh, J. Xu, and S. Bressan, Privacy as a Service: Publishing Data and Models. In Proc. DASFAA, Thailand, April, 2019. (PDF)