Statistical Learning
-
D. Russo and B. Van Roy,
``Learning
to Optimize Via Posterior Sampling.''
-
Y.-H. Kao and B. Van Roy,
``Directed
Principal Component Analysis,''
submitted.
-
Y.-H. Kao and B. Van Roy,
``Learning
a Factor Model via Regularized PCA,'' to appear in Machine Learning.
-
M. Ibrahimi, A. Javanmard, and B. Van Roy
``Efficient
Reinforcement Learning for High Dimensional Linear Systems,''
Advances in Neural Information Processing Systems 25,
MIT Press, 2012.
-
Y. H. Kao, B. Van Roy, and X. Yan,
``Directed
Regression,''
Advances in Neural Information Processing Systems 22,
MIT Press, pp. 889-897, 2009.
-
B. Van Roy and X. Yan,
``Manipulation
Robustness of Collaborative Filtering,''
Management Science, Vol. 56, No. 11, pp. 1911-1929, 2010.
-
V. F. Farias, C. C. Moallemi, B. Van Roy, and T. Weissman,
``Universal
Reinforcement Learning,'' IEEE Transactions on Information
Theory, Vol. 56, No. 5, pp. 2441-2454, 2010.
-
B. Van Roy
``Performance
Loss Bounds for Approximate Value Iteration with State Aggregation,''
Mathematics of Operations Research, Vol. 31, No. 2, pp. 234-244,
2006.
-
C. C. Moallemi and B. Van Roy
``Distributed
Optimization in Adaptive Networks,'' Advances in Neural Information
Processing Systems 16, MIT Press, 2004.
[appendix]
-
D. S. Choi and B. Van Roy,
``A
Generalized Kalman Filter for Fixed Point Approximation
and Efficient Temporal-Difference Learning,''
Discrete Event Dynamic Systems, Vol. 16, No. 2, April 2006.
- J. N. Tsitsiklis and B. Van Roy,
``
On Average Versus Discounted Reward Temporal-Difference
Learning,'' Machine Learning, Vol. 49, No. 2-3, 2002, pp. 179-191.
-
D. P. de Farias and B. Van Roy,
``
On the Existence of Fixed Points for Approximate Value
Iteration and Temporal-Difference Learning,''
Journal of Optimization Theory and Applications,
Vol. 105, No. 3, June, 2000.
- J. N. Tsitsiklis and B. Van Roy,
``Average Cost
Temporal-Difference Learning,'' Automatica,
Vol. 35, No. 11, November 1999, pp. 1799-1808.
- J. N. Tsitsiklis and B. Van Roy,
``An Analysis of
Temporal-Difference Learning with Function Approximation,''
IEEE Transactions on Automatic Control,
Vol. 42, No. 5, May 1997, pp. 674-690.