OPTIMIZING EXPECTATIONS: FROM DEEP REINFORCEMENT LEARNING TO STOCHASTIC COMPUTATION GRAPHS

PDF Publication Title:

OPTIMIZING EXPECTATIONS: FROM DEEP REINFORCEMENT LEARNING TO STOCHASTIC COMPUTATION GRAPHS ( optimizing-expectations-from-deep-reinforcement-learning-to- )

Previous Page View | Next Page View | Return to Search List

Text from PDF Page: 095

BIBLIOGRAPHY [BS03] [BB11] [BSA83] [BB01] [Bel+13] [BLC13] [Ber+10] [Ber05] [Ber12] That which has been is that which will be, And that which has been done is that which will be done. So there is nothing new under the sun. — Ecclesiastes 1:9, NASB J. A. Bagnell and J. Schneider. “Covariant policy search.” In: IJCAI. 2003 (cit. on pp. 6, 24). P. L. Bartlett and J. Baxter. “Infinite-horizon policy-gradient estimation.” In: arXiv preprint arXiv:1106.0665 (2011) (cit. on p. 25). A. G. Barto, R. S. Sutton, and C. W. Anderson. “Neuronlike adaptive elements that can solve difficult learning control problems.” In: Systems, Man and Cybernetics, IEEE Transactions on 5 (1983), pp. 834–846 (cit. on pp. 31, 57). J. Baxter and P. L. Bartlett. “Infinite-horizon policy-gradient estimation.” In: Journal of Artificial Intelligence Research (2001), pp. 319–350 (cit. on p. 81). M. G. Bellemare, Y. Naddaf, J. Veness, and M. Bowling. “The Arcade Learning Envi- ronment: An Evaluation Platform for General Agents.” In: Journal of Artificial Intelli- gence Research 47 (2013), pp. 253–279 (cit. on p. 32). Y. Bengio, N. Léonard, and A. Courville. “Estimating or propagating gradients through stochastic neurons for conditional computation.” In: arXiv preprint arXiv:1308.3432 (2013) (cit. on p. 76). J. Bergstra, O. Breuleux, F. Bastien, P. Lamblin, R. Pascanu, G. Desjardins, J. Turian, D. Warde-Farley, and Y. Bengio. “Theano: a CPU and GPU math expression compiler.” In: Proceedings of the Python for scientific computing conference (SciPy). Vol. 4. Austin, TX. 2010, p. 3 (cit. on p. 41). D. Bertsekas. Dynamic programming and optimal control. Vol. 1. 2005 (cit. on p. 26). D. P. Bertsekas. Dynamic programming and optimal control. Vol. 2. 2. Athena Scientific, 2012 (cit. on p. 53). 87

PDF Image | OPTIMIZING EXPECTATIONS: FROM DEEP REINFORCEMENT LEARNING TO STOCHASTIC COMPUTATION GRAPHS

PDF Search Title:

OPTIMIZING EXPECTATIONS: FROM DEEP REINFORCEMENT LEARNING TO STOCHASTIC COMPUTATION GRAPHS

Original File Name Searched:

thesis-optimizing-deep-learning.pdf

DIY PDF Search: Google It | Yahoo | Bing

Cruise Ship Reviews | Luxury Resort | Jet | Yacht | and Travel Tech More Info

Cruising Review Topics and Articles More Info

Software based on Filemaker for the travel industry More Info

The Burgenstock Resort: Reviews on CruisingReview website... More Info

Resort Reviews: World Class resorts... More Info

The Riffelalp Resort: Reviews on CruisingReview website... More Info

CONTACT TEL: 608-238-6001 Email: greg@cruisingreview.com (Standard Web Page)