-
1
-
-
84896809023
-
Efficient first order methods for linear composite regularizers
-
A. Argyriou, C. Micchelli, M. Pontil, L. Shen, and Y. Xu. Efficient first order methods for linear composite regularizers. Computing Research Repository, 2011.
-
(2011)
Computing Research Repository
-
-
Argyriou, A.1
Micchelli, C.2
Pontil, M.3
Shen, L.4
Xu, Y.5
-
2
-
-
84896859134
-
Structured sparsity through convex optimization
-
abs/1109.2397
-
F. Bach, R. Jenatton, J. Mairal, and G. Obozinski. Structured sparsity through convex optimization. CoRR, abs/1109.2397, 2011.
-
(2011)
CoRR
-
-
Bach, F.1
Jenatton, R.2
Mairal, J.3
Obozinski, G.4
-
3
-
-
46249088758
-
Consistency of the group lasso and multiple kernel learning
-
F. R. Bach. Consistency of the group lasso and multiple kernel learning. Journal of Machine Learning Research, 9:1179-1225, 2008.
-
(2008)
Journal of Machine Learning Research
, vol.9
, pp. 1179-1225
-
-
Bach, F.R.1
-
4
-
-
85014561619
-
A fast iterative shrinkagethresholding algorithm for linear inverse problems
-
A. Beck and M. Teboulle. A fast iterative shrinkagethresholding algorithm for linear inverse problems. SIAM J. Imaging Sci., 2(1):183-202, 2009.
-
(2009)
SIAM J. Imaging Sci.
, vol.2
, Issue.1
, pp. 183-202
-
-
Beck, A.1
Teboulle, M.2
-
5
-
-
85014561619
-
A fast iterative shrinkagethresholding algorithm for linear inverse problems
-
A. Beck and M. Teboulle. A fast iterative shrinkagethresholding algorithm for linear inverse problems. SIAM J. Imaging Sciences, 2(1):183-202, 2009.
-
(2009)
SIAM J. Imaging Sciences
, vol.2
, Issue.1
, pp. 183-202
-
-
Beck, A.1
Teboulle, M.2
-
6
-
-
80051762104
-
Distributed optimization and statistical learning via the alternating direction method of multipliers
-
S. Boyd, N. Parikh, E. Chu, B. Peleato, and J. Eckstein. Distributed optimization and statistical learning via the alternating direction method of multipliers. Foundations and Trends in Machine Learning, 3(1):1-122, 2011.
-
(2011)
Foundations and Trends in Machine Learning
, vol.3
, Issue.1
, pp. 1-122
-
-
Boyd, S.1
Parikh, N.2
Chu, E.3
Peleato, B.4
Eckstein, J.5
-
7
-
-
84858788674
-
Sparse signal recovery using markov random fields
-
V. Cevher, M. F. Duarte, C. Hegde, and R. G. Baraniuk. Sparse signal recovery using markov random fields. In NIPS, pages 257-264, 2008.
-
(2008)
NIPS
, pp. 257-264
-
-
Cevher, V.1
Duarte, M.F.2
Hegde, C.3
Baraniuk, R.G.4
-
8
-
-
51449111119
-
Iteratively reweighted algorithms for compressive sensing
-
R. Chartrand and W. Yin. Iteratively reweighted algorithms for compressive sensing. In ICASSP, pages 3869-3872, 2008.
-
(2008)
ICASSP
, pp. 3869-3872
-
-
Chartrand, R.1
Yin, W.2
-
9
-
-
84896841059
-
Learning with forest sparsity
-
abs/1211.4657
-
C. Chen, Y. Li, and J. Huang. Learning with forest sparsity. CoRR, abs/1211.4657, 2012.
-
(2012)
CoRR
-
-
Chen, C.1
Li, Y.2
Huang, J.3
-
10
-
-
80053139009
-
Smoothing proximal gradient method for general structured sparse learning
-
X. Chen, Q. Lin, S. Kim, J. Carbonell, and E. Xing. Smoothing proximal gradient method for general structured sparse learning. In UAI, pages 105-114, 2011.
-
(2011)
UAI
, pp. 105-114
-
-
Chen, X.1
Lin, Q.2
Kim, S.3
Carbonell, J.4
Xing, E.5
-
11
-
-
35348891430
-
Networkbased classification of breast cancer metastasis
-
H. Chuang, E. Lee, Y.-T. Liu, D. Lee, and T. Ideker. Networkbased classification of breast cancer metastasis. Molecular Systems Biology, 3(140), 2007.
-
(2007)
Molecular Systems Biology
, vol.3
, Issue.140
-
-
Chuang, H.1
Lee, E.2
Liu, Y.-T.3
Lee, D.4
Ideker, T.5
-
12
-
-
52049096603
-
Iteratively re-weighted least squares minimization: Proof of faster than linear rate for sparse recovery
-
I. Daubechies, R. DeVore, M. Fornasier, and C. S. Güntürk. Iteratively re-weighted least squares minimization: Proof of faster than linear rate for sparse recovery. In CISS, pages 26-29, 2008.
-
(2008)
CISS
, pp. 26-29
-
-
Daubechies, I.1
Devore, R.2
Fornasier, M.3
Güntürk, C.S.4
-
13
-
-
84867615673
-
Nonnegative matrix factorization using a robust error function
-
C. H. Q. Ding and D. Kong. Nonnegative matrix factorization using a robust error function. In ICASSP, pages 2033-2036, 2012.
-
(2012)
ICASSP
, pp. 2033-2036
-
-
Ding, C.H.Q.1
Kong, D.2
-
15
-
-
79960138168
-
Nonparametric independence screening in sparse ultra-high dimensional additive models
-
J. Fan, Y. Feng, and R. Song. Nonparametric independence screening in sparse ultra-high dimensional additive models. J. Amer. Statist. Assoc., 106:544-557, 2011.
-
(2011)
J. Amer. Statist. Assoc.
, vol.106
, pp. 544-557
-
-
Fan, J.1
Feng, Y.2
Song, R.3
-
18
-
-
71149113559
-
Group lasso with overlap and graph lasso
-
L. Jacob, G. Obozinski, and J.-p. Vert. Group lasso with overlap and graph lasso. In ICML, page 55, 2009.
-
(2009)
ICML
, pp. 55
-
-
Jacob, L.1
Obozinski, G.2
Vert, J.-P.3
-
19
-
-
70049092408
-
Structured variable selection with sparsity-inducing norms
-
arXiv:0904.3523
-
R. Jenatton, J. Audibert, and F. Bach. Structured variable selection with sparsity-inducing norms. Technical report, arXiv:0904.3523, 2009.
-
(2009)
Technical Report
-
-
Jenatton, R.1
Audibert, J.2
Bach, F.3
-
20
-
-
77956506018
-
Proximal methods for sparse hierarchical dictionary learning
-
R. Jenatton, J. Mairal, G. Obozinski, and F. Bach. Proximal methods for sparse hierarchical dictionary learning. In ICML, 2010.
-
(2010)
ICML
-
-
Jenatton, R.1
Mairal, J.2
Obozinski, G.3
Bach, F.4
-
21
-
-
70450177775
-
Learning invariant features through topographic filter maps
-
K. Kavukcuoglu, M. Ranzato, R. Fergus, and Y. LeCun. Learning invariant features through topographic filter maps. In CVPR, pages 1605-1612, 2009.
-
(2009)
CVPR
, pp. 1605-1612
-
-
Kavukcuoglu, K.1
Ranzato, M.2
Fergus, R.3
Lecun, Y.4
-
22
-
-
66349089385
-
A multivariate regression approach to association analysis of a quantitative trait network
-
S. Kim, K. Sohn, and E. Xing. A multivariate regression approach to association analysis of a quantitative trait network. Bioinformatics, 25(12):204-212, 2009.
-
(2009)
Bioinformatics
, vol.25
, Issue.12
, pp. 204-212
-
-
Kim, S.1
Sohn, K.2
Xing, E.3
-
23
-
-
77956548668
-
Tree-guided group lasso for multi-task regression with structured sparsity
-
S. Kim and E. Xing. Tree-guided group lasso for multi-task regression with structured sparsity. In ICML, 2010.
-
(2010)
ICML
-
-
Kim, S.1
Xing, E.2
-
24
-
-
84867132501
-
An iterative locally linear embedding algorithm
-
D. Kong and C. H. Q. Ding. An iterative locally linear embedding algorithm. In ICML, 2012.
-
(2012)
ICML
-
-
Kong, D.1
Ding, C.H.Q.2
-
25
-
-
83055187059
-
Robust nonnegative matrix factorization using 121-norm
-
D. Kong, C. H. Q. Ding, and H. Huang. Robust nonnegative matrix factorization using 121-norm. In CIKM, pages 673-682, 2011.
-
(2011)
CIKM
, pp. 673-682
-
-
Kong, D.1
Ding, C.H.Q.2
Huang, H.3
-
26
-
-
84866673280
-
Multi-label relieff and f-statistic feature selections for image annotation
-
D. Kong, C. H. Q. Ding, H. Huang, and H. Zhao. Multi-label relieff and f-statistic feature selections for image annotation. In CVPR, pages 2352-2359, 2012.
-
(2012)
CVPR
, pp. 2352-2359
-
-
Kong, D.1
Ding, C.H.Q.2
Huang, H.3
Zhao, H.4
-
27
-
-
84886493829
-
Minimal shrinkage for noisy data recovery using schatten-p norm objective
-
D. Kong, M. Zhang, and C. H. Q. Ding. Minimal shrinkage for noisy data recovery using schatten-p norm objective. In ECML/PKDD, pages 177-193, 2013.
-
(2013)
ECML/PKDD
, pp. 177-193
-
-
Kong, D.1
Zhang, M.2
Ding, C.H.Q.3
-
28
-
-
80053145416
-
Multi-task feature learning via efficient l2,1-norm minimization
-
J. Liu, S. Ji, and J. Ye. Multi-task feature learning via efficient l2,1-norm minimization. In UAI, pages 339-348, 2009.
-
(2009)
UAI
, pp. 339-348
-
-
Liu, J.1
Ji, S.2
Ye, J.3
-
29
-
-
85161968806
-
Moreau-yosida regularization for grouped tree structure learning
-
J. Liu and J. Ye. Moreau-yosida regularization for grouped tree structure learning. In NIPS, pages 1459-1467, 2010.
-
(2010)
NIPS
, pp. 1459-1467
-
-
Liu, J.1
Ye, J.2
-
31
-
-
80055058907
-
Gradient methods for minimizing composite objective function
-
Y. Nesterov. Gradient methods for minimizing composite objective function. ECORE Discussion Paper, 2007.
-
(2007)
ECORE Discussion Paper
-
-
Nesterov, Y.1
-
33
-
-
84856264699
-
Convex approaches to model wavelet sparsity patterns
-
N. S. Rao, R. D. Nowak, S. Wright, and N. Kingsbury. Convex approaches to model wavelet sparsity patterns. In ICIP, pages 1917-1920, 2011.
-
(2011)
ICIP
, pp. 1917-1920
-
-
Rao, N.S.1
Nowak, R.D.2
Wright, S.3
Kingsbury, N.4
-
35
-
-
27344435774
-
Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles
-
A. Subramanian, p. Tamayo, and et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proceedings of the National Academy of Sciences, 102(43):15545-15550, 2005.
-
(2005)
Proceedings of the National Academy of Sciences
, vol.102
, Issue.43
, pp. 15545-15550
-
-
Subramanian, A.1
Tamayo, P.2
-
37
-
-
12844266177
-
Sparsity and smoothness via the fused lasso
-
R. Tibshirani, M. Saunders, and S. Rosset. Sparsity and smoothness via the fused lasso. Journal of the Royal Sta-tistical Society, Series B, 67(1):91-108, 2005.
-
(2005)
Journal of the Royal Sta-tistical Society, Series B
, vol.67
, Issue.1
, pp. 91-108
-
-
Tibshirani, R.1
Saunders, M.2
Rosset, S.3
-
38
-
-
0037137519
-
A gene-expression signature as a predictor of survival in breast cancer
-
M. Vijver, Y. He, and et al. A gene-expression signature as a predictor of survival in breast cancer. New England Journal of Medicine, 347(25), 2002.
-
(2002)
New England Journal of Medicine
, vol.347
, Issue.25
-
-
Vijver, M.1
He, Y.2
-
39
-
-
84867131829
-
Group sparse additive models
-
J. Yin, X. Chen, and E. p. Xing. Group sparse additive models. In ICML, 2012.
-
(2012)
ICML
-
-
Yin, J.1
Chen, X.2
Xing, E.P.3
-
40
-
-
85162375080
-
Efficient methods for overlapping group lasso
-
L. Yuan, J. Liu, and J. Ye. Efficient methods for overlapping group lasso. In NIPS, pages 352-360, 2011.
-
(2011)
NIPS
, pp. 352-360
-
-
Yuan, L.1
Liu, J.2
Ye, J.3
-
42
-
-
69949155103
-
D the composite absolute penalties family for grouped and hierarchical variable selection
-
p. Zhao, G. Rocha, and B. Yu. D the composite absolute penalties family for grouped and hierarchical variable selection. Annals of Statistics, 37(6A):3468-3497, 2009.
-
(2009)
Annals of Statistics
, vol.37
, Issue.6 A
, pp. 3468-3497
-
-
Zhao, P.1
Rocha, G.2
Yu, B.3
|