Publications in Venue "AISTATS"
| 1. | R. Vega, P. Gorji, Z. Zhang, X. Qin, A. Hareendranathan, J. Kapur, J. Jaremko, R. Greiner. "Sample Efficient Learning of Image-Based Diagnostic Classifiers". Artificial Intelligence and Statistics, March 2021.  |
| 2. | H. Cheng, Y. Yu, X. Zhang, E. Xing, D. Schuurmans. "Scalable and sound low rank tensor learning". Artificial Intelligence and Statistics, (ed: Arthur Gretton, Christian C. Robert), pp 1114-1123, May 2016. |
| 3. | S. Ravanbakhsh, B. Poczos, J. Schneider, D. Schuurmans, R. Greiner. "Stochastic Neural Networks with Monotonic Activation Functions". Artificial Intelligence and Statistics, (ed: Arthur Gretton, Christian C. Robert), pp 809-818, May 2016.  |
| 4. | J. Neufeld, D. Schuurmans, M. Bowling. "Variance Reduction via Antithetic Markov Chains". Artificial Intelligence and Statistics, (ed: Guy Lebanon, S. V. N. Vishwanathan), pp 708-716, May 2015. |
| 5. | M. White, D. Schuurmans. "Generalized Optimal Reverse Prediction". Artificial Intelligence and Statistics, (ed: Neil D. Lawrence, Mark A. Girolami), pp 1305-1313, April 2012. |
| 6. | M. Johanson, M. Bowling. "Data Biased Robust Counter Strategies". Artificial Intelligence and Statistics, (ed: David van Dyk and Max Welling), pp 264-271, April 2009. |
| 7. | M. Yang, Y. Li, D. Schuurmans. "Dual temporal difference learning". Artificial Intelligence and Statistics, April 2009. |
| 8. | Y. Li, C. Szepesvari, D. Schuurmans. "Learning exercise policies for American options". Artificial Intelligence and Statistics, April 2009. |
| 9. | N. Ratliff, J. Bagnell, M. Zinkevich. "Subgradient Methods for Structured Prediction". Artificial Intelligence and Statistics, August 2007. |
