- PT, Alexander Volfovsky, Edoardo M. Airoldi, "Causal inference with entangled treatments" (2015)
- PT, Edoardo M. Airoldi, Donald B. Rubin, "Causal inference under partially revealed interference" (2015)
- PT, Edoardo M. Airoldi, "Implicit stochastic approximation" (2015, pdf)
- Dustin Tran, PT, Edoardo M. Airoldi, "Stochastic gradient methods for estimation with large datasets" (2015, pdf, minor revision)
- PT, Edoardo M. Airoldi, "Asymptotic and finite-sample properties of estimators based on stochastic gradients", Annals of Statistics, 2017, forthcoming ( pdf)
- PT, "A useful pivotal quantity", American Statistician, 2016, forthcoming ( www | pdf | bib)
- PT, Edoardo M. Airoldi, "Scalable estimation strategies based on stochastic approximations: Classical results and new insights", Statistics and Computing, 2015 ( www | pdf | bib).
- PT, David Parkes, "Design and analysis of multi-hospital kidney-exchanges using random graphs", Games and Economic Behavior, 2015 ( pdf | www | bib)
- PT, David Parkes, "Long-term causal effects via behavioral game theory", Neural Information Processing Systems, 2016, Barcelona, Spain, (NIPS'16, www | bib)
- PT, Dustin Tran, Edoardo M. Airoldi, "Towards stability and optimality in stochastic gradient descent" , AI and Statistics, 2016, Cadiz, Spain (AISTATS' 16, pdf | bib)
- PT, David Parkes, Elery Pfeffer, James Zou, "Incentive-compatible experimental design", Economics and Computation, 2015, Portland, Oregon (EC'15, pdf | bib)
- PT, Jason Rennie, Edoardo Airoldi, "Statistical analysis of stochastic gradient methods for generalized linear models", International Conference of Machine Learning, 2014, Beijing, China (ICML' 14, www, pdf | bib)
- PT, Edward Kao, "Estimation of Causal Peer Influence Effects", International Conference of Machine Learning, 2013, Atlanta, Georgia (ICML'13, www, pdf | bib)
- PT, David Parkes, "A Random Graph Model of Kidney Exchanges: Efficiency, Individual-Rationality and Incentives", Economics and Computation, 2011, San Jose, California (EC'11, pdf | bib)
- Nikolaos Mavridis, Wajahat Kazmi, PT, C. Ben-AbdelKader, "On the synergies between online social networking, Face Recognition, and Interactive Robotics", International Conference on Computational Aspects of Social Networks, 2009, Fontainebleau, France (CASoN'09, pdf | bib)
- PT, Dionisis Kehagias, Pericles Mitkas, "Mertacor, a successful trading agent", Autonomous Agents and Multi-Agent Systems, 2006, Hakodate, Japan (AAMAS'06, pdf | bib)
- Dionisis Kehagias, PT, Pericles Mitkas, "A Long-Term Profit Seeking Strategy for Continuous Double Auctions in a Trading Agent Competition", Fourth Hellenic Conference on Artificial Intelligence, 2006, Heraklion, Crete ( www | pdf | bib)
- PT, Edoardo Airoldi, "Stochastic gradient methods for principled estimation with large datasets", in "Handbook of Big Data", CRC Press, 2016 (eds. Buhlmann et. al.)-( www | pdf )
- Nikolaos Mavridis, Wajahat Kazmi, PT, "Friends with Faces: How Social Networks Can Enhance Face Recognition and Vice Versa", Computational Social Network Analysis (eds. A. Ajith & H. Aboul-Ella & S. Vaclav), pp. 453-482, Springer London
Short papers, Workshops, and Tutorials
- Introduction to Stochastic Gradient Descent. This is a short introduction to Stochastic Gradient Descent, trying to cover both the optimization and statistical perspective. It covers classical literature in stochastic approximation, as well as recent developments.
- Matt Bonakdarpour, PT, "Statistical perspectives of stochastic optimization" (NIPS'16, Probabilistic Numerics Workshop, pdf)
- Implicit temporal differences ( pdf) - Using ideas from implicit stochastic gradient descent to improve the stability of the Temporal Differences algorithm (TD) in reinforcement learning. Neural Information and Processing Systems (NIPS 2014, Montreal, Canada).
- Software Engineering With R, 2013 ( pdf) - Intro to software engineering practices with R: unit testing, debugging, logging, profiling.