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Semantic ScholarFrancis R. Bach
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- affiliation: École Normale Supérieure, Computer Science Department
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2010 – today
- 2017
[j46]Francis R. Bach:
Breaking the Curse of Dimensionality with Convex Neural Networks. Journal of Machine Learning Research 18: 19:1-19:53 (2017)- [j45]Francis R. Bach:
On the Equivalence between Kernel Quadrature Rules and Random Feature Expansions. Journal of Machine Learning Research 18: 21:1-21:38 (2017) - [j44]Fabian Pedregosa, Francis R. Bach, Alexandre Gramfort:
On the Consistency of Ordinal Regression Methods. Journal of Machine Learning Research 18: 55:1-55:35 (2017) - [j43]Mark W. Schmidt, Nicolas Le Roux, Francis R. Bach:
Minimizing finite sums with the stochastic average gradient. Math. Program. 162(1-2): 83-112 (2017) - [j42]Mark W. Schmidt, Nicolas Le Roux, Francis R. Bach:
Erratum to: Minimizing finite sums with the stochastic average gradient. Math. Program. 162(1-2): 113 (2017) - [c100]Raman Sankaran, Francis R. Bach, Chiranjib Bhattacharyya:
Identifying Groups of Strongly Correlated Variables through Smoothed Ordered Weighted L1-norms. AISTATS 2017: 1123-1131 - [c99]Nicolas Flammarion, Francis R. Bach:
Stochastic Composite Least-Squares Regression with Convergence Rate $O(1/n)$. COLT 2017: 831-875 - [c98]Felipe Yanez, Francis R. Bach:
Primal-dual algorithms for non-negative matrix factorization with the Kullback-Leibler divergence. ICASSP 2017: 2257-2261 - [c97]Kevin Scaman, Francis R. Bach, Sébastien Bubeck, Yin Tat Lee, Laurent Massoulié:
Optimal Algorithms for Smooth and Strongly Convex Distributed Optimization in Networks. ICML 2017: 3027-3036 - [c96]Christophe Dupuy, Francis R. Bach, Christophe Diot:
Qualitative and Descriptive Topic Extraction from Movie Reviews Using LDA. MLDM 2017: 91-106 - [i81]Anton Osokin, Francis R. Bach, Simon Lacoste-Julien:
On Structured Prediction Theory with Calibrated Convex Surrogate Losses. CoRR abs/1703.02403 (2017) - [i80]Francis R. Bach:
Efficient Algorithms for Non-convex Isotonic Regression through Submodular Optimization. CoRR abs/1707.09157 (2017) - 2016
- [c95]Francis R. Bach, Vianney Perchet:
Highly-Smooth Zero-th Order Online Optimization. COLT 2016: 257-283 - [c94]Rémi Lajugie, Piotr Bojanowski, Philippe Cuvillier, Sylvain Arlot, Francis R. Bach:
A weakly-supervised discriminative model for audio-to-score alignment. ICASSP 2016: 2484-2488 - [c93]Anastasia Podosinnikova, Francis R. Bach, Simon Lacoste-Julien:
Beyond CCA: Moment Matching for Multi-View Models. ICML 2016: 458-467 - [c92]Sara El Aouad, Christophe Dupuy, Renata Teixeira, Francis R. Bach, Christophe Diot:
Exploiting Crowd Sourced Reviews to Explain Movie Recommendation. NETYS 2016: 193-201 - [c91]Damien Scieur, Alexandre d'Aspremont, Francis R. Bach:
Regularized Nonlinear Acceleration. NIPS 2016: 712-720 - [c90]Balamurugan Palaniappan, Francis R. Bach:
Stochastic Variance Reduction Methods for Saddle-Point Problems. NIPS 2016: 1408-1416 - [c89]Pascal Germain, Francis R. Bach, Alexandre Lacoste, Simon Lacoste-Julien:
PAC-Bayesian Theory Meets Bayesian Inference. NIPS 2016: 1876-1884 - [c88]Tatiana Shpakova, Francis R. Bach:
Parameter Learning for Log-supermodular Distributions. NIPS 2016: 3234-3242 - [c87]Aude Genevay, Marco Cuturi, Gabriel Peyré, Francis R. Bach:
Stochastic Optimization for Large-scale Optimal Transport. NIPS 2016: 3432-3440 - [i79]Aymeric Dieuleveut, Nicolas Flammarion, Francis R. Bach:
Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression. CoRR abs/1602.05419 (2016) - [i78]Anastasia Podosinnikova, Francis R. Bach, Simon Lacoste-Julien:
Beyond CCA: Moment Matching for Multi-View Models. CoRR abs/1602.09013 (2016) - [i77]Christophe Dupuy, Francis R. Bach:
Online but Accurate Inference for Latent Variable Models with Local Gibbs Sampling. CoRR abs/1603.02644 (2016) - [i76]Balamurugan P., Francis R. Bach:
Stochastic Variance Reduction Methods for Saddle-Point Problems. CoRR abs/1605.06398 (2016) - [i75]Francis R. Bach, Vianney Perchet:
Highly-Smooth Zero-th Order Online Optimization Vianney Perchet. CoRR abs/1605.08165 (2016) - [i74]Aude Genevay, Marco Cuturi, Gabriel Peyré, Francis R. Bach:
Stochastic Optimization for Large-scale Optimal Transport. CoRR abs/1605.08527 (2016) - [i73]Pascal Germain, Francis R. Bach, Alexandre Lacoste, Simon Lacoste-Julien:
PAC-Bayesian Theory Meets Bayesian Inference. CoRR abs/1605.08636 (2016) - [i72]Tatiana Shpakova, Francis R. Bach:
Parameter Learning for Log-supermodular Distributions. CoRR abs/1608.05258 (2016) - [i71]Nicolas Flammarion, Balamurugan Palanisamy, Francis R. Bach:
Robust Discriminative Clustering with Sparse Regularizers. CoRR abs/1608.08052 (2016) - [i70]Christophe Dupuy, Francis R. Bach:
Learning Determinantal Point Processes in Sublinear Time. CoRR abs/1610.05925 (2016) - 2015
- [j41]Julien Mairal, Michael Elad, Francis R. Bach:
Guest Editorial: Sparse Coding. International Journal of Computer Vision 114(2-3): 89-90 (2015) - [j40]Francis R. Bach:
Duality Between Subgradient and Conditional Gradient Methods. SIAM Journal on Optimization 25(1): 115-129 (2015) - [j39]Fajwel Fogel, Rodolphe Jenatton, Francis R. Bach, Alexandre d'Aspremont:
Convex Relaxations for Permutation Problems. SIAM J. Matrix Analysis Applications 36(4): 1465-1488 (2015) - [j38]Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach, Martin Kleinsteuber, Matthias Seibert:
Sample Complexity of Dictionary Learning and Other Matrix Factorizations. IEEE Trans. Information Theory 61(6): 3469-3486 (2015) - [j37]Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach:
Sparse and Spurious: Dictionary Learning With Noise and Outliers. IEEE Trans. Information Theory 61(11): 6298-6319 (2015) - [j36]Nino Shervashidze, Francis R. Bach:
Learning the Structure for Structured Sparsity. IEEE Trans. Signal Processing 63(18): 4894-4902 (2015) - [c86]Alexandre Défossez, Francis R. Bach:
Averaged Least-Mean-Squares: Bias-Variance Trade-offs and Optimal Sampling Distributions. AISTATS 2015 - [c85]Simon Lacoste-Julien, Fredrik Lindsten, Francis R. Bach:
Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering. AISTATS 2015 - [c84]Nicolas Flammarion, Francis R. Bach:
From Averaging to Acceleration, There is Only a Step-size. COLT 2015: 658-695 - [c83]Alberto Bietti, Francis R. Bach, Arshia Cont:
An online EM algorithm in hidden (semi-)Markov models for audio segmentation and clustering. ICASSP 2015: 1881-1885 - [c82]Piotr Bojanowski, Rémi Lajugie, Edouard Grave, Francis R. Bach, Ivan Laptev, Jean Ponce, Cordelia Schmid:
Weakly-Supervised Alignment of Video with Text. ICCV 2015: 4462-4470 - [c81]Anastasia Podosinnikova, Francis R. Bach, Simon Lacoste-Julien:
Rethinking LDA: Moment Matching for Discrete ICA. NIPS 2015: 514-522 - [c80]Rakesh Shivanna, Bibaswan K. Chatterjee, Raman Sankaran, Chiranjib Bhattacharyya, Francis R. Bach:
Spectral Norm Regularization of Orthonormal Representations for Graph Transduction. NIPS 2015: 2215-2223 - [e1]Francis R. Bach, David M. Blei:
Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, Lille, France, 6-11 July 2015. JMLR Workshop and Conference Proceedings 37, JMLR.org 2015 [contents] - [i69]Simon Lacoste-Julien, Fredrik Lindsten, Francis R. Bach:
Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering. CoRR abs/1501.02056 (2015) - [i68]Francis R. Bach:
On the Equivalence between Quadrature Rules and Random Features. CoRR abs/1502.06800 (2015) - [i67]K. S. Sesh Kumar, Álvaro Barbero Jiménez, Stefanie Jegelka, Suvrit Sra, Francis R. Bach:
Convex Optimization for Parallel Energy Minimization. CoRR abs/1503.01563 (2015) - [i66]Piotr Bojanowski, R. Lagugie, Edouard Grave, Francis R. Bach, Ivan Laptev, Jean Ponce, Cordelia Schmid:
Weakly-Supervised Alignment of Video With Text. CoRR abs/1505.06027 (2015) - [i65]Rémi Lajugie, Piotr Bojanowski, Sylvain Arlot, Francis R. Bach:
Semidefinite and Spectral Relaxations for Multi-Label Classification. CoRR abs/1506.01829 (2015) - [i64]Vincent Roulet, Fajwel Fogel, Alexandre d'Aspremont, Francis R. Bach:
Supervised Clustering in the Data Cube. CoRR abs/1506.04908 (2015) - [i63]Anastasia Podosinnikova, Francis R. Bach, Simon Lacoste-Julien:
Rethinking LDA: moment matching for discrete ICA. CoRR abs/1507.01784 (2015) - [i62]Francis R. Bach:
Submodular Functions: from Discrete to Continous Domains. CoRR abs/1511.00394 (2015) - 2014
- [j35]Toby Dylan Hocking, Valentina Boeva, Guillem Rigaill, Gudrun Schleiermacher, Isabelle Janoueix-Lerosey, Olivier Delattre, Wilfrid Richer, Franck Bourdeaut, Miyuki Suguro, Masao Seto, Francis R. Bach, Jean-Philippe Vert:
SegAnnDB: interactive Web-based genomic segmentation. Bioinformatics 30(11): 1539-1546 (2014) - [j34]Julien Mairal, Francis R. Bach, Jean Ponce:
Sparse Modeling for Image and Vision Processing. Foundations and Trends in Computer Graphics and Vision 8(2-3): 85-283 (2014) - [j33]Francis R. Bach:
Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression. Journal of Machine Learning Research 15(1): 595-627 (2014) - [j32]Alexandre d'Aspremont, Francis R. Bach, Laurent El Ghaoui:
Approximation bounds for sparse principal component analysis. Math. Program. 148(1-2): 89-110 (2014) - [j31]Georgios B. Giannakis, Francis R. Bach, Raphael Cendrillon, Michael Mahoney, Jennifer Neville:
Signal Processing for Big Data [From the Guest Editors]. IEEE Signal Process. Mag. 31(5): 15-16 (2014) - [c79]Edouard Grave, Guillaume Obozinski, Francis R. Bach:
A Markovian approach to distributional semantics with application to semantic compositionality. COLING 2014: 1447-1456 - [c78]Piotr Bojanowski, Rémi Lajugie, Francis R. Bach, Ivan Laptev, Jean Ponce, Cordelia Schmid, Josef Sivic:
Weakly Supervised Action Labeling in Videos under Ordering Constraints. ECCV (5) 2014: 628-643 - [c77]Rémi Lajugie, Francis R. Bach, Sylvain Arlot:
Large-Margin Metric Learning for Constrained Partitioning Problems. ICML 2014: 297-305 - [c76]Thomas Schatz, Vijayaditya Peddinti, Xuan-Nga Cao, Francis R. Bach, Hynek Hermansky, Emmanuel Dupoux:
Evaluating speech features with the minimal-pair ABX task (II): resistance to noise. INTERSPEECH 2014: 915-919 - [c75]Aaron Defazio, Francis R. Bach, Simon Lacoste-Julien:
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives. NIPS 2014: 1646-1654 - [c74]Rémi Lajugie, Damien Garreau, Francis R. Bach, Sylvain Arlot:
Metric Learning for Temporal Sequence Alignment. NIPS 2014: 1817-1825 - [c73]Matthias Seibert, Martin Kleinsteuber, Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach:
On the sample complexity of sparse dictionary learning. SSP 2014: 244-247 - [i61]Aaron Defazio, Francis R. Bach, Simon Lacoste-Julien:
SAGA: A Fast Incremental Gradient Method With Support for Non-Strongly Convex Composite Objectives. CoRR abs/1407.0202 (2014) - [i60]Piotr Bojanowski, Rémi Lajugie, Francis R. Bach, Ivan Laptev, Jean Ponce, Cordelia Schmid, Josef Sivic:
Weakly Supervised Action Labeling in Videos Under Ordering Constraints. CoRR abs/1407.1208 (2014) - [i59]Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach:
Sparse and spurious: dictionary learning with noise and outliers. CoRR abs/1407.5155 (2014) - [i58]Fabian Pedregosa, Francis R. Bach, Alexandre Gramfort:
On the Consistency of Ordinal Regression Methods. CoRR abs/1408.2327 (2014) - [i57]Damien Garreau, Rémi Lajugie, Sylvain Arlot, Francis R. Bach:
Metric Learning for Temporal Sequence Alignment. CoRR abs/1409.3136 (2014) - [i56]Julien Mairal, Francis R. Bach, Jean Ponce:
Sparse Modeling for Image and Vision Processing. CoRR abs/1411.3230 (2014) - [i55]Alexandre Défossez, Francis R. Bach:
Constant Step Size Least-Mean-Square: Bias-Variance Trade-offs and Optimal Sampling Distributions. CoRR abs/1412.0156 (2014) - [i54]Felipe Yanez, Francis R. Bach:
Primal-Dual Algorithms for Non-negative Matrix Factorization with the Kullback-Leibler Divergence. CoRR abs/1412.1788 (2014) - [i53]Francis R. Bach:
Breaking the Curse of Dimensionality with Convex Neural Networks. CoRR abs/1412.8690 (2014) - 2013
- [j30]Toby Dylan Hocking, Gudrun Schleiermacher, Isabelle Janoueix-Lerosey, Valentina Boeva, Julie Cappo, Olivier Delattre, Francis R. Bach, Jean-Philippe Vert:
Learning smoothing models of copy number profiles using breakpoint annotations. BMC Bioinformatics 14: 164 (2013) - [j29]Francis R. Bach:
Learning with Submodular Functions: A Convex Optimization Perspective. Foundations and Trends in Machine Learning 6(2-3): 145-373 (2013) - [j28]Bamdev Mishra, Gilles Meyer, Francis R. Bach, Rodolphe Sepulchre:
Low-Rank Optimization with Trace Norm Penalty. SIAM Journal on Optimization 23(4): 2124-2149 (2013) - [j27]Zaïd Harchaoui, Francis R. Bach, Olivier Cappé, Eric Moulines:
Kernel-Based Methods for Hypothesis Testing: A Unified View. IEEE Signal Process. Mag. 30(4): 87-97 (2013) - [c72]
- [c71]Edouard Grave, Guillaume Obozinski, Francis R. Bach:
Hidden Markov tree models for semantic class induction. CoNLL 2013: 94-103 - [c70]Piotr Bojanowski, Francis R. Bach, Ivan Laptev, Jean Ponce, Cordelia Schmid, Josef Sivic:
Finding Actors and Actions in Movies. ICCV 2013: 2280-2287 - [c69]Toby Hocking, Guillem Rigaill, Jean-Philippe Vert, Francis R. Bach:
Learning Sparse Penalties for Change-point Detection using Max Margin Interval Regression. ICML (3) 2013: 172-180 - [c68]K. S. Sesh Kumar, Francis R. Bach:
Convex Relaxations for Learning Bounded-Treewidth Decomposable Graphs. ICML (1) 2013: 525-533 - [c67]Emile Richard, Francis R. Bach, Jean-Philippe Vert:
Intersecting singularities for multi-structured estimation. ICML (3) 2013: 1157-1165 - [c66]Thomas Schatz, Vijayaditya Peddinti, Francis R. Bach, Aren Jansen, Hynek Hermansky, Emmanuel Dupoux:
Evaluating speech features with the minimal-pair ABX task: analysis of the classical MFC/PLP pipeline. INTERSPEECH 2013: 1781-1785 - [c65]Francis R. Bach, Eric Moulines:
Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n). NIPS 2013: 773-781 - [c64]Fajwel Fogel, Rodolphe Jenatton, Francis R. Bach, Alexandre d'Aspremont:
Convex Relaxations for Permutation Problems. NIPS 2013: 1016-1024 - [c63]Stefanie Jegelka, Francis R. Bach, Suvrit Sra:
Reflection methods for user-friendly submodular optimization. NIPS 2013: 1313-1321 - [i52]
- [i51]Rémi Lajugie, Sylvain Arlot, Francis R. Bach:
Large-Margin Metric Learning for Partitioning Problems. CoRR abs/1303.1280 (2013) - [i50]Francis R. Bach:
Adaptivity of averaged stochastic gradient descent to local strong convexity for logistic regression. CoRR abs/1303.6149 (2013) - [i49]Francis R. Bach, Eric Moulines:
Non-strongly-convex smooth stochastic approximation with convergence rate O(1/n). CoRR abs/1306.2119 (2013) - [i48]Mark W. Schmidt, Nicolas Le Roux, Francis R. Bach:
Minimizing Finite Sums with the Stochastic Average Gradient. CoRR abs/1309.2388 (2013) - [i47]K. S. Sesh Kumar, Francis R. Bach:
Maximizing submodular functions using probabilistic graphical models. CoRR abs/1309.2593 (2013) - [i46]
- [i45]Stefanie Jegelka, Francis R. Bach, Suvrit Sra:
Reflection methods for user-friendly submodular optimization. CoRR abs/1311.4296 (2013) - [i44]Rémi Gribonval, Rodolphe Jenatton, Francis R. Bach, Martin Kleinsteuber, Matthias Seibert:
Sample Complexity of Dictionary Learning and other Matrix Factorizations. CoRR abs/1312.3790 (2013) - [i43]Edouard Grave, Guillaume Obozinski, Francis R. Bach:
Domain adaptation for sequence labeling using hidden Markov models. CoRR abs/1312.4092 (2013) - 2012
- [j26]Francis R. Bach, Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski:
Optimization with Sparsity-Inducing Penalties. Foundations and Trends in Machine Learning 4(1): 1-106 (2012) - [j25]Matthieu Solnon, Sylvain Arlot, Francis R. Bach:
Multi-task regression using minimal penalties. Journal of Machine Learning Research 13: 2773-2812 (2012) - [j24]Julien Mairal, Francis R. Bach, Jean Ponce:
Task-Driven Dictionary Learning. IEEE Trans. Pattern Anal. Mach. Intell. 34(4): 791-804 (2012) - [j23]Rodolphe Jenatton, Alexandre Gramfort, Vincent Michel, Guillaume Obozinski, Evelyn Eger, Francis R. Bach, Bertrand Thirion:
Multiscale Mining of fMRI Data with Hierarchical Structured Sparsity. SIAM J. Imaging Sciences 5(3): 835-856 (2012) - [c62]
- [c61]Francis R. Bach, Simon Lacoste-Julien, Guillaume Obozinski:
On the Equivalence between Herding and Conditional Gradient Algorithms. ICML 2012 - [c60]
- [c59]
- [c58]Augustin Lefèvre, Francis R. Bach, Cédric Févotte:
Semi-supervised NMF with Time-frequency Annotations for Single-channel Source Separation. ISMIR 2012: 115-120 - [c57]Hachem Kadri, Alain Rakotomamonjy, Francis R. Bach, Philippe Preux:
Multiple Operator-valued Kernel Learning. NIPS 2012: 2438-2446 - [c56]Nicolas Le Roux, Mark W. Schmidt, Francis R. Bach:
A Stochastic Gradient Method with an Exponential Convergence Rate for Finite Training Sets. NIPS 2012: 2672-2680 - [i42]Nicolas Le Roux, Mark W. Schmidt, Francis R. Bach:
A Stochastic Gradient Method with an Exponential Convergence Rate for Strongly-Convex Optimization with Finite Training Sets. CoRR abs/1202.6258 (2012) - [i41]Hachem Kadri, Alain Rakotomamonjy, Francis R. Bach, Philippe Preux:
Multiple Operator-valued Kernel Learning. CoRR abs/1203.1596 (2012) - [i40]Francis R. Bach, Simon Lacoste-Julien, Guillaume Obozinski:
On the Equivalence between Herding and Conditional Gradient Algorithms. CoRR abs/1203.4523 (2012) - [i39]Guillaume Obozinski, Francis R. Bach:
Convex Relaxation for Combinatorial Penalties. CoRR abs/1205.1240 (2012) - [i38]
- [i37]Rodolphe Jenatton, Rémi Gribonval, Francis R. Bach:
Local stability and robustness of sparse dictionary learning in the presence of noise. CoRR abs/1210.0685 (2012) - [i36]Francis R. Bach:
Duality between subgradient and conditional gradient methods. CoRR abs/1211.6302 (2012) - [i35]Simon Lacoste-Julien, Mark W. Schmidt, Francis R. Bach:
A simpler approach to obtaining an O(1/t) convergence rate for the projected stochastic subgradient method. CoRR abs/1212.2002 (2012) - [i34]K. S. Sesh Kumar, Francis R. Bach:
Convex Relaxations for Learning Bounded Treewidth Decomposable Graphs. CoRR abs/1212.2573 (2012) - 2011
- [j22]Rodolphe Jenatton, Julien Mairal, Guillaume Obozinski, Francis R. Bach:
Proximal Methods for Hierarchical Sparse Coding. Journal of Machine Learning Research 12: 2297-2334 (2011) - [j21]Julien Mairal, Rodolphe Jenatton, Guillaume Obozinski, Francis R. Bach:
Convex and Network Flow Optimization for Structured Sparsity. Journal of Machine Learning Research 12: 2681-2720 (2011) - [j20]Rodolphe Jenatton, Jean-Yves Audibert, Francis R. Bach:
Structured Variable Selection with Sparsity-Inducing Norms. Journal of Machine Learning Research 12: 2777-2824 (2011) - [j19]Alexandre d'Aspremont, Francis R. Bach, Inderjit S. Dhillon, Bin Yu:
Preface. Math. Program. 127(1): 1-2 (2011) - [j18]Olivier Duchenne, Francis R. Bach, In-So Kweon, Jean Ponce:
A Tensor-Based Algorithm for High-Order Graph Matching. IEEE Trans. Pattern Anal. Mach. Intell. 33(12): 2383-2395 (2011) - [c55]Louise Benoît, Julien Mairal, Francis R. Bach, Jean Ponce:
Sparse image representation with epitomes. CVPR 2011: 2913-2920 - [c54]Augustin Lefèvre, Francis R. Bach, Cédric Févotte:
Itakura-Saito nonnegative matrix factorization with group sparsity. ICASSP 2011: 21-24 - [c53]Y-Lan Boureau, Nicolas Le Roux, Francis R. Bach, Jean Ponce, Yann LeCun:
Ask the locals: Multi-way local pooling for image recognition. ICCV 2011: 2651-2658 - [c52]Toby Hocking, Jean-Philippe Vert, Francis R. Bach, Armand Joulin:
Clusterpath: an Algorithm for Clustering using Convex Fusion Penalties. ICML 2011: 745-752 - [c51]