Causal Inference/Randomizations

Randomization tests of causal effects under interference, with Basse, G; Feller, A. (Biometrika, 2019) (pdf / slides)

Long-term causal effects via behavioral game theory, with Parkes, DC. (NIPS'16) (pdf / slides)

Estimation of Causal Peer Influence Effects, with Kao, E. (ICML'13, oral) (pdf)

Machine Learning

Convergence diagnostics for stochastic gradient descent with constant step size, with Chee, J., (AISTATS'18, oral) (pdf / slides)

sgd: Stochastic gradient methods for estimation with large datasets, with Tran, D.; Airoldi, EM (Journal of Statistical Software, 2018) (pdf)

Asymptotic and finite-sample properties of estimators based on stochastic gradients, with Airoldi, EM. (Annals of Statistics, 2017) (pdf / slides / errata / supplement-errata)

Towards stability and optimality in stochastic gradient descent, with Tran, D., Airoldi, EM. (AISTATS' 16) (pdf)

Scalable estimation strategies based on stochastic approximations, with Airoldi, EM. (Statistics and Computing, 2015) (pdf)

Statistical analysis of stochastic gradient methods for generalized linear models, with Rennie, J., Airoldi, EM, (ICML' 14, oral) (pdf / slides)

Microeconomics/Networks

Design and analysis of multi-hospital kidney-exchanges using random graphs, with Parkes, DC. (Games and Economic Behavior, 2015) (pdf)

Incentive-compatible experimental design, with Parkes, DC., Pfeffer, E., Zhou, J. (EC'15) (pdf)

A Random Graph Model of Kidney Exchanges: Efficiency, Individual Rationality, Incentives, with Parkes, DC, (EC'11) (pdf)

Online social networking, Face Recognition, and Interactive Robotics, w/ Mavridis, N., Kazmi, W., Ben-AbdelKader, C. (CASoN'09) (pdf)

Other

A useful pivotal quantity (American Statistician, 2016) (pdf)

Mertacor, a successful trading agent, with Kehagias, D., Mitkas, P., (AAMAS'06) (pdf)

A Long-Term Profit Seeking Strategy for Continuous Double Auctions, with Kehagias, D., Mitkas, P. (HCAI'04) (pdf)

Book chapters

Stochastic gradient methods for estimation with large datasets, with Airoldi, EM. (Handbook of Big Data, CRC Press, 2016, eds. Buhlmann et. al.) (pdf)

Friends with Faces: How Social Networks Can Enhance Face Recognition and Vice Versa, with Mavridis, N., Kazmi, W. (Computational Social Network Analysis, Springer London, eds. A. Ajith et. al.) (pdf)

Short papers, Workshops, and Tutorials

Introduction to Stochastic Gradient Descent (2013). This is a short intro to SGD taking both an optimization and statistical perspective. It covers classical literature in stochastic approximation, as well as recent developments.

Statistical perspectives of stochastic optimization (2016), with Bonakdarpour, M. (Probabilistic Numerics Workshop, NIPS'16)

Implicit temporal differences, with Tamar, A., Mannor, S., Airoldi, EM. (Reinforcement Learning, NIPS'14)

Software Engineering With R. Intro to software engineering practices with R: unit testing, debugging, logging, profiling.