-
1
-
-
21844440820
-
Generalization bounds for the area under the roc curve
-
Agarwal, S., Graepel, T., Herbrich, R., Har-Peled, S., & Roth, D. (2005). Generalization bounds for the area under the roc curve. Journal of Machine Learning Research, 6, 393-425.
-
(2005)
Journal of Machine Learning Research
, vol.6
, pp. 393-425
-
-
Agarwal, S.1
Graepel, T.2
Herbrich, R.3
Har-Peled, S.4
Roth, D.5
-
2
-
-
84864063089
-
Multi-task feature learning
-
Argyriou, A., Evgeniou, T., & Pontil, M. (2007). Multi-task feature learning. Advances in Neural Information Processing Systems 19 (pp. 41-48).
-
(2007)
Advances in Neural Information Processing Systems
, vol.19
, pp. 41-48
-
-
Argyriou, A.1
Evgeniou, T.2
Pontil, M.3
-
4
-
-
29144489844
-
For most large underdetermined systems of linear equations the minimal l1-norm solution is also the sparsest solution
-
Statistics Dept, Stanford University
-
Donoho, D. (2004). For most large underdetermined systems of linear equations the minimal l1-norm solution is also the sparsest solution. (Technical Report). Statistics Dept., Stanford University.
-
(2004)
Technical Report
-
-
Donoho, D.1
-
5
-
-
56449092085
-
Efficient projections onto the l1-ball for learning in high dimensions
-
Duchi, J., Shalev-Shwartz, S., Singer, Y., & Chandra, T. (2008). Efficient projections onto the l1-ball for learning in high dimensions. Proc. of Intl. Conf. on Machine Learning (pp. 272-279).
-
(2008)
Proc. of Intl. Conf. on Machine Learning
, pp. 272-279
-
-
Duchi, J.1
Shalev-Shwartz, S.2
Singer, Y.3
Chandra, T.4
-
6
-
-
34247576789
-
The pyramid match kernel: Efficient learning with sets of features
-
Grauman, K., & Darrell, T. (2008). The pyramid match kernel: Efficient learning with sets of features. Journal of Machine Learning Research, 8, 725-760.
-
(2008)
Journal of Machine Learning Research
, vol.8
, pp. 725-760
-
-
Grauman, K.1
Darrell, T.2
-
7
-
-
70049111780
-
Effcient structure learning of markov networks using l1-regularization
-
Lee, S. I., Ganapathi, V., & Koller, D. (2007). Effcient structure learning of markov networks using l1-regularization. Advances in Neural Information Processing Systems 19 (pp. 817-824).
-
(2007)
Advances in Neural Information Processing Systems
, vol.19
, pp. 817-824
-
-
Lee, S.I.1
Ganapathi, V.2
Koller, D.3
-
9
-
-
14344249889
-
Feature selection, l1 vs. l2 regularization, and rotational invariance
-
Ng, A. Y. (2004). Feature selection, l1 vs. l2 regularization, and rotational invariance. Proc. of Intl. Conf. on Machine Learning.
-
(2004)
Proc. of Intl. Conf. on Machine Learning
-
-
Ng, A.Y.1
-
11
-
-
34948865158
-
-
Technical Report, Statistics Dept, University of California, Berkeley
-
Obozinski, G., Taskar, B., & Jordan, M. (2006). Multitask feature selection (Technical Report). Statistics Dept., University of California, Berkeley.
-
(2006)
Multitask feature selection
-
-
Obozinski, G.1
Taskar, B.2
Jordan, M.3
-
13
-
-
51949094374
-
-
Qu1attoni, A., Collins, M., & Darrell, T. (2008). Transfer learning for image classification with sparse prototype representations. Proc. of Conf. on Computer Vision and Pattern Recognition.
-
Qu1attoni, A., Collins, M., & Darrell, T. (2008). Transfer learning for image classification with sparse prototype representations. Proc. of Conf. on Computer Vision and Pattern Recognition.
-
-
-
-
14
-
-
51949118201
-
Structure learning in random fields for heart motion abnormality detection
-
Schmidt, M., Murphy, K., Fung, G., & Rosale, R. (2008). Structure learning in random fields for heart motion abnormality detection. Proc. of Conf. on Computer Vision and Pattern Recognition.
-
(2008)
Proc. of Conf. on Computer Vision and Pattern Recognition
-
-
Schmidt, M.1
Murphy, K.2
Fung, G.3
Rosale, R.4
-
15
-
-
84862276986
-
Optimizing costly functionswith simple constraints: A limited-memory projected quasi-newton algorithm
-
Schmidt, M., van den Berg, E., Friedlander, M., & Murphy, K. (2009). Optimizing costly functionswith simple constraints: A limited-memory projected quasi-newton algorithm. Proc. of Conf. on Artificial Intelligence and Statistics (pp. 456-463).
-
(2009)
Proc. of Conf. on Artificial Intelligence and Statistics
, pp. 456-463
-
-
Schmidt, M.1
van den Berg, E.2
Friedlander, M.3
Murphy, K.4
-
17
-
-
34548232392
-
Input selection and shrinkage in multiresponse linear regression
-
Similä, T., & Tikka, J. (2007). Input selection and shrinkage in multiresponse linear regression. Computational Statistics and Data Analysis, 52, 406-422.
-
(2007)
Computational Statistics and Data Analysis
, vol.52
, pp. 406-422
-
-
Similä, T.1
Tikka, J.2
-
18
-
-
30844461481
-
Algorithms for simultaneous sparse approximation, part ii: Convex relaxation
-
Tropp, J. (2006). Algorithms for simultaneous sparse approximation, part ii: convex relaxation. Signal Processing (pp. 589-602).
-
(2006)
Signal Processing
, pp. 589-602
-
-
Tropp, J.1
-
19
-
-
23844431650
-
Simultaneous variable selection
-
Turlach, B., Venables, W., & Wright, S. (2005). Simultaneous variable selection. Technometrics, 47, 349-363.
-
(2005)
Technometrics
, vol.47
, pp. 349-363
-
-
Turlach, B.1
Venables, W.2
Wright, S.3
-
20
-
-
33645035051
-
Model selection and estimation in regression with grouped variables
-
Yuan, M., & Lin, Y. (2006). Model selection and estimation in regression with grouped variables. J. Royal Statistical Society Series B, 68, 49-67.
-
(2006)
J. Royal Statistical Society Series B
, vol.68
, pp. 49-67
-
-
Yuan, M.1
Lin, Y.2
-
21
-
-
1942484421
-
Online convex programming and generalized infinitesimal gradient ascent
-
Zinkevich, M. (2003). Online convex programming and generalized infinitesimal gradient ascent. Proc. of Intl. Conf. on Machine Learning (pp. 928-936).
-
(2003)
Proc. of Intl. Conf. on Machine Learning
, pp. 928-936
-
-
Zinkevich, M.1
|