-
1
-
-
1542367492
-
-
Technical, Statistics Department, University of California, Berkeley
-
P. L. Bartlett, M. I. Jordan, and J. D. McAuliffe. Convexity, classification, and risk bounds. Technical Report 638, Statistics Department, University of California, Berkeley, 2003.
-
(2003)
Convexity, Classification, and Risk Bounds
-
-
Bartlett, P.L.1
Jordan, M.I.2
McAuliffe, J.D.3
-
5
-
-
0010442827
-
On the algorithmic implementation of multiclass kernel-based vector machines
-
Koby Crammer and Yoram Singer. On the algorithmic implementation of multiclass kernel-based vector machines. Journal of Machine Learning Research, 2:265-292, 2001.
-
(2001)
Journal of Machine Learning Research
, vol.2
, pp. 265-292
-
-
Crammer, K.1
Singer, Y.2
-
6
-
-
84898949656
-
Data-dependent bounds for multi-category classification based on convex losses
-
Ilya Desyatnikov and Ron Meir. Data-dependent bounds for multi-category classification based on convex losses. In COLT, 2003.
-
(2003)
COLT
-
-
Desyatnikov, I.1
Meir, R.2
-
7
-
-
0034164230
-
Additive logistic regression: A statistical view of boosting
-
With discussion
-
J. Friedman, T. Hastie, and R. Tibshirani. Additive logistic regression: A statistical view of boosting. The Annals of Statistics, 28(2):337-407, 2000. With discussion.
-
(2000)
The Annals of Statistics
, vol.28
, Issue.2
, pp. 337-407
-
-
Friedman, J.1
Hastie, T.2
Tibshirani, R.3
-
8
-
-
26444545593
-
Process consistency for adaboost
-
with discussion
-
W. Jiang. Process consistency for adaboost. The Annals of Statistics, 32:13-29, 2004. with discussion.
-
(2004)
The Annals of Statistics
, vol.32
, pp. 13-29
-
-
Jiang, W.1
-
9
-
-
2142775432
-
Multicategory support vector machines, theory, and application to the classification of microarray data and satellite radiance data
-
Y. Lee, Y. Lin, and G. Wahba. Multicategory support vector machines, theory, and application to the classification of microarray data and satellite radiance data. Journal of American Statistical Association, 99:67-81, 2004.
-
(2004)
Journal of American Statistical Association
, vol.99
, pp. 67-81
-
-
Lee, Y.1
Lin, Y.2
Wahba, G.3
-
10
-
-
0036258405
-
Support vector machines and the bayes rule in classification
-
Yi Lin. Support vector machines and the bayes rule in classification. Data Mining and Knowledge Discovery, pages 259-275, 2002.
-
(2002)
Data Mining and Knowledge Discovery
, pp. 259-275
-
-
Lin, Y.1
-
12
-
-
9444269961
-
On the Bayes-risk consistency of regularized boosting methods
-
with discussion
-
G. Lugosi and N. Vayatis. On the Bayes-risk consistency of regularized boosting methods. The Annals of Statistics, 32:30-55, 2004. with discussion.
-
(2004)
The Annals of Statistics
, vol.32
, pp. 30-55
-
-
Lugosi, G.1
Vayatis, N.2
-
13
-
-
0033234630
-
Smooth discrimination analysis
-
E. Mammen and A. Tsybakov Smooth discrimination analysis. Annals of Statis., 27:1808-1829, 1999.
-
(1999)
Annals of Statis.
, vol.27
, pp. 1808-1829
-
-
Mammen, E.1
Tsybakov, A.2
-
14
-
-
2542488393
-
Greedy algorithms for classification - Consistency, convergence rates, and adaptivity
-
Shie Mannor, Ron Meir, and Tong Zhang. Greedy algorithms for classification - consistency, convergence rates, and adaptivity. Journal of Machine Learning Research, 4:713-741, 2003.
-
(2003)
Journal of Machine Learning Research
, vol.4
, pp. 713-741
-
-
Mannor, S.1
Meir, R.2
Zhang, T.3
-
16
-
-
0033281701
-
Improved boosting algorithms using confidence-rated predictions
-
Robert E. Schapire and Yoram Singer. Improved boosting algorithms using confidence-rated predictions. Machine Learning, 37:297-336, 1999.
-
(1999)
Machine Learning
, vol.37
, pp. 297-336
-
-
Schapire, R.E.1
Singer, Y.2
-
19
-
-
0036749277
-
Support vector machines are universally consistent
-
Ingo Steinwart. Support vector machines are universally consistent. J. Complexity, 18:768-791, 2002.
-
(2002)
J. Complexity
, vol.18
, pp. 768-791
-
-
Steinwart, I.1
-
21
-
-
21844437252
-
Consistency of support vector machines and other regularized kernel machines
-
to appear
-
Ingo Steinwart. Consistency of support vector machines and other regularized kernel machines. IEEE Transactions on Information Theory, 2004. to appear.
-
(2004)
IEEE Transactions on Information Theory
-
-
Steinwart, I.1
-
25
-
-
84925669872
-
-
CBMS-NSF Regional Conference series in applied mathematics. SIAM
-
Grace Wahba. Spline Models for Observational Data. CBMS-NSF Regional Conference series in applied mathematics. SIAM, 1990.
-
(1990)
Spline Models for Observational Data
-
-
Wahba, G.1
-
27
-
-
0347067948
-
Covering number bounds of certain regularized linear function classes
-
Tong Zhang. Covering number bounds of certain regularized linear function classes. Journal of Machine Learning Research, 2:527-550, 2002.
-
(2002)
Journal of Machine Learning Research
, vol.2
, pp. 527-550
-
-
Zhang, T.1
-
28
-
-
4644257995
-
Statistical behavior and consistency of classification methods based on convex risk minimization
-
with discussion
-
Tong Zhang. Statistical behavior and consistency of classification methods based on convex risk minimization. The Annals of Statitics, 32:56-85, 2004. with discussion.
-
(2004)
The Annals of Statitics
, vol.32
, pp. 56-85
-
-
Zhang, T.1
|