-
1
-
-
0037709910
-
The nonstochastic multiarmed bandit problem
-
P. AUER, N. CESA-BIANCHI, Y. FREUND, AND R. E. SCHAPIRE, The nonstochastic multiarmed bandit problem, SIAM J. Computing, 32 (2002), pp. 48-77.
-
(2002)
SIAM J. Computing
, vol.32
, pp. 48-77
-
-
Auer, P.1
Cesa-Bianchi, N.2
Freund, Y.3
Schapire, R.E.4
-
5
-
-
4444253732
-
Online learning in online auctions
-
A. BLUM, V. KUMAR, A. RUDRA, AND F. WU, Online learning in online auctions, Theoretical Computer Science, 324 (2004), pp. 137-146.
-
(2004)
Theoretical Computer Science
, vol.324
, pp. 137-146
-
-
Blum, A.1
Kumar, V.2
Rudra, A.3
Wu, F.4
-
8
-
-
20744454447
-
Online convex optimization in the bandit setting: Gradient descent without a gradient
-
A. D. FLAXMAN, A. T. KALAI, AND H. B. MCMAHAN, Online convex optimization in the bandit setting: Gradient descent without a gradient, in Proceedings of the 16th ACM-SIAM Symposium on Discrete Algorithms (SODA), 2005, pp. 385-394.
-
(2005)
Proceedings of the 16th ACM-SIAM Symposium on Discrete Algorithms (SODA)
, pp. 385-394
-
-
Flaxman, A.D.1
Kalai, A.T.2
Mcmahan, H.B.3
-
9
-
-
0031211090
-
A decision-theoretic generalization of on-line learning and an application to boosting
-
Y. FREUND AND R. E. SCHAPIRE, A decision-theoretic generalization of on-line learning and an application to boosting, Journal of Computer and System Sciences, 55 (1997), pp. 119-139.
-
(1997)
Journal of Computer and System Sciences
, vol.55
, pp. 119-139
-
-
Freund, Y.1
Schapire, R.E.2
-
10
-
-
0002955623
-
A dynamic allocation index for the sequential design of experiments
-
J. G. et al., ed., North-Holland
-
J. C. GITTINS AND D. M. JONES, A dynamic allocation index for the sequential design of experiments, in Progress in Statistics, J. G. et al., ed., North-Holland, 1974, pp. 241-266.
-
(1974)
Progress in Statistics
, pp. 241-266
-
-
Gittins, J.C.1
Jones, D.M.2
-
11
-
-
84898981061
-
Nearly tight bounds for the continuum-armed bandit problem
-
L. K. Saul, Y. Weiss, and L. Bottou, eds., MIT Press, Cambridge, MA
-
R. KLEINBERG, Nearly tight bounds for the continuum-armed bandit problem, in Advances in Neural Information Processing Systems 17, L. K. Saul, Y. Weiss, and L. Bottou, eds., MIT Press, Cambridge, MA, 2005, pp. 697-704.
-
(2005)
Advances in Neural Information Processing Systems 17
, pp. 697-704
-
-
Kleinberg, R.1
-
14
-
-
9444257628
-
Online geometric optimization in the bandit setting against an adaptive adversary
-
Proceedings of the 17th Annual Conference on Learning Theory (COLT)
-
H. B. MCMAHAN AND A. BLUM, Online geometric optimization in the bandit setting against an adaptive adversary, in Proceedings of the 17th Annual Conference on Learning Theory (COLT), vol. 3120 of Lecture Notes in Computer Science, Springer Verlag, 2004, pp. 109-123.
-
(2004)
Lecture Notes in Computer Science, Springer Verlag
, vol.3120
, pp. 109-123
-
-
Mcmahan, H.B.1
Blum, A.2
|