2009 |
45 | EE | Francis Bach:
Model-Consistent Sparse Estimation through the Bootstrap
CoRR abs/0901.3202: (2009) |
2008 |
44 | EE | Julien Mairal,
Francis Bach,
Jean Ponce,
Guillermo Sapiro,
Andrew Zisserman:
Discriminative learned dictionaries for local image analysis.
CVPR 2008 |
43 | EE | Julien Mairal,
Marius Leordeanu,
Francis Bach,
Martial Hebert,
Jean Ponce:
Discriminative Sparse Image Models for Class-Specific Edge Detection and Image Interpretation.
ECCV (3) 2008: 43-56 |
42 | EE | Mikhail Zaslavskiy,
Francis Bach,
Jean-Philippe Vert:
A Path Following Algorithm for Graph Matching.
ICISP 2008: 329-337 |
41 | EE | Francis R. Bach:
Graph kernels between point clouds.
ICML 2008: 25-32 |
40 | EE | Francis R. Bach:
Bolasso: model consistent Lasso estimation through the bootstrap.
ICML 2008: 33-40 |
39 | EE | Julien Mairal,
Francis Bach,
Jean Ponce,
Guillermo Sapiro,
Andrew Zisserman:
Supervised Dictionary Learning.
NIPS 2008: 1033-1040 |
38 | EE | Francis Bach:
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning.
NIPS 2008: 105-112 |
37 | EE | Zaïd Harchaoui,
Francis Bach,
Eric Moulines:
Kernel Change-point Analysis.
NIPS 2008: 609-616 |
36 | EE | Cédric Archambeau,
Francis Bach:
Sparse probabilistic projections.
NIPS 2008: 73-80 |
35 | EE | Laurent Jacob,
Francis Bach,
Jean-Philippe Vert:
Clustered Multi-Task Learning: A Convex Formulation.
NIPS 2008: 745-752 |
34 | EE | Mikhail Zaslavskiy,
Francis Bach,
Jean-Philippe Vert:
Path following algorithm for the graph matching problem
CoRR abs/0801.3654: (2008) |
33 | EE | Francis Bach,
Jacob Abernethy,
Jean-Philippe Vert,
Theodoros Evgeniou:
A New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
CoRR abs/0802.1430: (2008) |
32 | EE | Francis Bach:
Bolasso: model consistent Lasso estimation through the bootstrap
CoRR abs/0804.1302: (2008) |
31 | EE | Francis Bach:
Exploring Large Feature Spaces with Hierarchical Multiple Kernel Learning
CoRR abs/0809.1493: (2008) |
30 | EE | Laurent Jacob,
Francis Bach,
Jean-Philippe Vert:
Clustered Multi-Task Learning: A Convex Formulation
CoRR abs/0809.2085: (2008) |
29 | EE | Julien Mairal,
Francis Bach,
Jean Ponce,
Guillermo Sapiro,
Andrew Zisserman:
Supervised Dictionary Learning
CoRR abs/0809.3083: (2008) |
28 | EE | Francis Bach,
Julien Mairal,
Jean Ponce:
Convex Sparse Matrix Factorizations
CoRR abs/0812.1869: (2008) |
2007 |
27 | EE | Zaïd Harchaoui,
Francis Bach:
Image Classification with Segmentation Graph Kernels.
CVPR 2007 |
26 | EE | Alexandre d'Aspremont,
Francis R. Bach,
Laurent El Ghaoui:
Full regularization path for sparse principal component analysis.
ICML 2007: 177-184 |
25 | EE | Alain Rakotomamonjy,
Francis Bach,
Stéphane Canu,
Yves Grandvalet:
More efficiency in multiple kernel learning.
ICML 2007: 775-782 |
24 | EE | Francis Bach,
Zaïd Harchaoui:
DIFFRAC: a discriminative and flexible framework for clustering.
NIPS 2007 |
23 | EE | Zaïd Harchaoui,
Francis Bach,
Eric Moulines:
Testing for Homogeneity with Kernel Fisher Discriminant Analysis.
NIPS 2007 |
22 | EE | Yoshihiro Yamanishi,
Francis Bach,
Jean-Philippe Vert:
Glycan classification with tree kernels.
Bioinformatics 23(10): 1211-1216 (2007) |
21 | EE | Alexandre d'Aspremont,
Francis R. Bach,
Laurent El Ghaoui:
Optimal Solutions for Sparse Principal Component Analysis
CoRR abs/0707.0705: (2007) |
20 | EE | Francis Bach:
Consistency of the group Lasso and multiple kernel learning
CoRR abs/0707.3390: (2007) |
19 | EE | Francis Bach:
Consistency of trace norm minimization
CoRR abs/0710.2848: (2007) |
18 | EE | Francis Bach:
Graph kernels between point clouds
CoRR abs/0712.3402: (2007) |
2006 |
17 | EE | Francis R. Bach:
Active learning for misspecified generalized linear models.
NIPS 2006: 65-72 |
16 | EE | Jacob Abernethy,
Francis Bach,
Theodoros Evgeniou,
Jean-Philippe Vert:
Low-rank matrix factorization with attributes
CoRR abs/cs/0611124: (2006) |
15 | EE | Francis R. Bach,
David Heckerman,
Eric Horvitz:
Considering Cost Asymmetry in Learning Classifiers.
Journal of Machine Learning Research 7: 1713-1741 (2006) |
14 | EE | Francis R. Bach,
Michael I. Jordan:
Learning Spectral Clustering, With Application To Speech Separation.
Journal of Machine Learning Research 7: 1963-2001 (2006) |
2005 |
13 | EE | Francis R. Bach,
Michael I. Jordan:
Predictive low-rank decomposition for kernel methods.
ICML 2005: 33-40 |
12 | EE | Kenji Fukumizu,
Francis R. Bach,
Arthur Gretton:
Statistical Convergence of Kernel CCA.
NIPS 2005 |
2004 |
11 | EE | Francis R. Bach,
Gert R. G. Lanckriet,
Michael I. Jordan:
Multiple kernel learning, conic duality, and the SMO algorithm.
ICML 2004 |
10 | EE | Francis R. Bach,
Michael I. Jordan:
Blind One-microphone Speech Separation: A Spectral Learning Approach.
NIPS 2004 |
9 | EE | Francis R. Bach,
Romain Thibaux,
Michael I. Jordan:
Computing regularization paths for learning multiple kernels.
NIPS 2004 |
8 | EE | Kenji Fukumizu,
Francis R. Bach,
Michael I. Jordan:
Dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces.
Journal of Machine Learning Research 5: 73-99 (2004) |
2003 |
7 | EE | Kenji Fukumizu,
Francis R. Bach,
Michael I. Jordan:
Kernel Dimensionality Reduction for Supervised Learning.
NIPS 2003 |
6 | EE | Francis R. Bach,
Michael I. Jordan:
Learning Spectral Clustering.
NIPS 2003 |
5 | EE | Francis R. Bach,
Michael I. Jordan:
Beyond Independent Components: Trees and Clusters.
Journal of Machine Learning Research 4: 1205-1233 (2003) |
2002 |
4 | EE | Francis R. Bach,
Michael I. Jordan:
Learning Graphical Models with Mercer Kernels.
NIPS 2002: 1009-1016 |
3 | | Francis R. Bach,
Michael I. Jordan:
Tree-dependent Component Analysis.
UAI 2002: 36-44 |
2 | EE | Francis R. Bach,
Michael I. Jordan:
Kernel Independent Component Analysis.
Journal of Machine Learning Research 3: 1-48 (2002) |
2001 |
1 | EE | Francis R. Bach,
Michael I. Jordan:
Thin Junction Trees.
NIPS 2001: 569-576 |