-
2
-
-
80053151768
-
Graphical models for bandit problems
-
K. Amin, M. Kearns, and U. Syed. Graphical models for bandit problems. In UAI, 2011.
-
(2011)
UAI
-
-
Amin, K.1
Kearns, M.2
Syed, U.3
-
3
-
-
0041966002
-
Using confidence bounds for exploitation-exploration trade-offs
-
P. Auer. Using confidence bounds for exploitation-exploration trade-offs. JMLR, 3, 2003.
-
(2003)
JMLR
, vol.3
-
-
Auer, P.1
-
4
-
-
80053461043
-
Multiclass classification with bandit feedback using adaptive regularization
-
K. Crammer and C. Gentile. Multiclass classification with bandit feedback using adaptive regularization. In 28th ICML, 2011.
-
(2011)
28th ICML
-
-
Crammer, K.1
Gentile, C.2
-
5
-
-
77953110428
-
Stochastic linear optimization under bandit feedback
-
V. Dani, T. Hayes, and S. Kakade. Stochastic linear optimization under bandit feedback. In 21th Colt, 2008.
-
(2008)
21th Colt
-
-
Dani, V.1
Hayes, T.2
Kakade, S.3
-
7
-
-
85162071043
-
Parametric bandits: The generalized linear case
-
S. Filippi, O. Cappé, A. Garivier, and C. Szepesvári. Parametric bandits: The generalized linear case. In NIPS, pages 586-594, 2010.
-
(2010)
NIPS
, pp. 586-594
-
-
Filippi, S.1
Cappé, O.2
Garivier, A.3
Szepesvári, C.4
-
8
-
-
4644367942
-
An efficient boosting algorithm for combining preferences
-
Y. Freund, R. D. Iyer, R. E. Schapire, and Y. Singer. An efficient boosting algorithm for combining preferences. JMLR, 4:933-969, 2003.
-
(2003)
JMLR
, vol.4
, pp. 933-969
-
-
Freund, Y.1
Iyer, R.D.2
Schapire, R.E.3
Singer, Y.4
-
9
-
-
52949105710
-
Multilabel classification via calibrated label ranking
-
J. Furnkranz, E. Hullermeier, E. Loza Menca, and K. Brinker. Multilabel classification via calibrated label ranking. Machine Learning, 73:133-153, 2008.
-
(2008)
Machine Learning
, vol.73
, pp. 133-153
-
-
Furnkranz, J.1
Hullermeier, E.2
Loza Menca, E.3
Brinker, K.4
-
10
-
-
80053442097
-
Online submodular minimization
-
E. Hazan and S. Kale. Online submodular minimization. In NIPS 22, 2009.
-
(2009)
NIPS
, vol.22
-
-
Hazan, E.1
Kale, S.2
-
11
-
-
85162453290
-
Newtron: An efficient bandit algorithm for online multiclass prediction
-
E. Hazan and S. Kale. Newtron: an efficient bandit algorithm for online multiclass prediction. In NIPS, 2011.
-
(2011)
NIPS
-
-
Hazan, E.1
Kale, S.2
-
13
-
-
56449104477
-
Efficient bandit algorithms for online multiclass prediction
-
S. Kakade, S. Shalev-Shwartz, and A. Tewari. Efficient bandit algorithms for online multiclass prediction. In 25th ICML, 2008.
-
(2008)
25th ICML
-
-
Kakade, S.1
Shalev-Shwartz, S.2
Tewari, A.3
-
15
-
-
85162453120
-
Contextual gaussian process bandit optimization
-
A. Krause and C. S. Ong. Contextual gaussian process bandit optimization. In 25th NIPS, 2011.
-
(2011)
25th NIPS
-
-
Krause, A.1
Ong, C.S.2
-
16
-
-
0002899547
-
Asymptotically efficient adaptive allocation rules
-
T. H. Lai and H. Robbins. Asymptotically efficient adaptive allocation rules. Adv. Appl. Math, 6, 1985.
-
(1985)
Adv. Appl. Math
, vol.6
-
-
Lai, T.H.1
Robbins, H.2
-
18
-
-
70350446810
-
Improving multilabel analysis of music titles: A large-scale validation of the correction approach
-
February
-
F. Pachet and P. Roy. Improving multilabel analysis of music titles: A large-scale validation of the correction approach. IEEE Trans. on Audio, Speech, and Lang. Proc., 17(2):335-343, February 2009.
-
(2009)
IEEE Trans. on Audio, Speech, and Lang. Proc.
, vol.17
, Issue.2
, pp. 335-343
-
-
Pachet, F.1
Roy, P.2
-
19
-
-
84867138308
-
Online structured prediction via coactive learning
-
to appear
-
P. Shivaswamy and T. Joachims. Online structured prediction via coactive learning. In 29th ICML, 2012, to appear.
-
(2012)
29th ICML
-
-
Shivaswamy, P.1
Joachims, T.2
-
20
-
-
77956542736
-
Learning optimally diverse rankings over large document collections
-
A. Slivkins, F. Radlinski, and S. Gollapudi. Learning optimally diverse rankings over large document collections. In 27th ICML, 2010.
-
(2010)
27th ICML
-
-
Slivkins, A.1
Radlinski, F.2
Gollapudi, S.3
-
21
-
-
34547172608
-
The challenge problem for automated detection of 101 semantic concepts in multimedia
-
New York, NY, USA
-
C. G. M. Snoek, M. Worring, J.C. van Gemert, J.-M. Geusebroek, and A. W. M. Smeulders. The challenge problem for automated detection of 101 semantic concepts in multimedia. In Proc. of the 14th ACM international conference on Multimedia, MULTIMEDIA '06, pages 421-430, New York, NY, USA, 2006.
-
(2006)
Proc. of the 14th ACM International Conference on Multimedia, MULTIMEDIA '06
, pp. 421-430
-
-
Snoek, C.G.M.1
Worring, M.2
Van Gemert, J.C.3
Geusebroek, J.-M.4
Smeulders, A.W.M.5
|