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SIERRA - 2015
SIERRA - 2015
Project-Team Sierra
Members
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography
Project-Team Sierra
Members
Overall Objectives
Research Program
Application Domains
Highlights of the Year
New Software and Platforms
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Dissemination
Bibliography


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Bibliography

Publications of the year

Doctoral Dissertations and Habilitation Theses

Articles in International Peer-Reviewed Journals

  • 3F. Bach.

    Duality between subgradient and conditional gradient methods, in: SIAM Journal of Optimization, January 2015, vol. 25, no 1, pp. 115-129. [ DOI : 10.1137/130941961 ]

    https://hal.archives-ouvertes.fr/hal-00757696
  • 4F. Fogel, R. Jenatton, F. Bach, A. d'Aspremont.

    Convex Relaxations for Permutation Problems, in: SIAM Journal on Matrix Analysis and Applications, December 2015, vol. 36, no 4. [ DOI : 10.1137/130947362 ]

    https://hal.archives-ouvertes.fr/hal-01239317
  • 5R. Gribonval, R. Jenatton, F. Bach.

    Sparse and spurious: dictionary learning with noise and outliers, in: IEEE Transactions on Information Theory, 2015, 22 p, This is a substantially revised version of a first draft that appeared as a preprint titled "Local stability and robustness of sparse dictionary learning in the presence of noise", http://hal.inria.fr/hal-00737152. [ DOI : 10.1109/TIT.2015.2472522 ]

    https://hal.archives-ouvertes.fr/hal-01025503
  • 6R. Gribonval, R. Jenatton, F. Bach, M. Kleinsteuber, M. Seibert.

    Sample Complexity of Dictionary Learning and other Matrix Factorizations, in: IEEE Transactions on Information Theory, 2015, 18 p, forthcoming. [ DOI : 10.1109/TIT.2015.2424238 ]

    https://hal.inria.fr/hal-00918142
  • 7A. Osokin, D. P. Vetrov.

    Submodular Relaxation for Inference in Markov Random Fields, in: IEEE Transactions on Pattern Analysis and Machine Intelligence, July 2015, vol. 37, no 7, 14 p. [ DOI : 10.1109/TPAMI.2014.2369046 ]

    https://hal.archives-ouvertes.fr/hal-01103488
  • 8F. Pedregosa, M. Eickenberg, P. Ciuciu, B. Thirion, A. Gramfort.

    Data-driven HRF estimation for encoding and decoding models, in: NeuroImage, January 2015, pp. 209–220.

    https://hal.inria.fr/hal-00952554
  • 9N. Shervashidze, F. Bach.

    Learning the Structure for Structured Sparsity, in: IEEE Transactions on Signal Processing, September 2015, vol. 63, no 18, pp. 4894 - 4902. [ DOI : 10.1109/TSP.2015.2446432 ]

    https://hal.inria.fr/hal-00986380
  • 10I. Waldspurger, A. d'Aspremont, S. Mallat.

    Phase recovery, MaxCut and complex semidefinite programming, in: Mathematical Programming, February 2015, vol. 149, no 1-2. [ DOI : 10.1007/s10107-013-0738-9 ]

    https://hal.archives-ouvertes.fr/hal-01239328

International Conferences with Proceedings

  • 11A. Bietti, F. Bach, A. Cont.

    An online EM algorithm in hidden (semi-)Markov models for audio segmentation and clustering, in: ICASSP 2015 - 40th IEEE International Conference on Acoustics, Speech and Signal Processing, Brisbane, Australia, April 2015.

    https://hal.inria.fr/hal-01115826
  • 12P. Bojanowski, R. Lajugie, E. Grave, F. Bach, I. Laptev, J. Ponce, C. Schmid.

    Weakly-Supervised Alignment of Video With Text, in: ICCV 2015 - IEEE International Conference on Computer Vision, Santiago, Chile, December 2015.

    https://hal.inria.fr/hal-01154523
  • 13V. Chari, S. Lacoste-Julien, I. Laptev, J. Sivic.

    On Pairwise Cost for Multi-Object Network Flow Tracking, in: CVPR 2015 - 28th IEEE Conference on Computer Vision and Pattern Recognition, Boston, United States, June 2015.

    https://hal.inria.fr/hal-01110678
  • 14A. Défossez, F. Bach.

    Constant Step Size Least-Mean-Square: Bias-Variance Trade-offs and Optimal Sampling Distributions, in: International Conference on Artificial Intelligence and Statistics (AISTATS),, San Diego, United States, 2015.

    https://hal.inria.fr/hal-01081578
  • 15T. Hofmann, A. Lucchi, S. Lacoste-Julien, B. McWilliams.

    Variance Reduced Stochastic Gradient Descent with Neighbors, in: NIPS 2015 - Advances in Neural Information Processing Systems 28, Montreal, Canada, December 2015.

    https://hal.inria.fr/hal-01248672
  • 16R. G. Krishnan, S. Lacoste-Julien, D. Sontag.

    Barrier Frank-Wolfe for Marginal Inference, in: NIPS 2015 - Advances in Neural Information Processing Systems 28, Montreal, Canada, December 2015.

    https://hal.inria.fr/hal-01248674
  • 17S. Lacoste-Julien, M. Jaggi.

    On the Global Linear Convergence of Frank-Wolfe Optimization Variants, in: NIPS 2015 - Advances in Neural Information Processing Systems 28, Montreal, Canada, December 2015.

    https://hal.inria.fr/hal-01248675
  • 18S. Lacoste-Julien, F. Lindsten, F. Bach.

    Sequential Kernel Herding: Frank-Wolfe Optimization for Particle Filtering, in: 18th International Conference on Artificial Intelligence and Statistics (AISTATS), San Diego, United States, JMLR Workshop and Conference Proceedings, May 2015, vol. 38.

    https://hal.archives-ouvertes.fr/hal-01099197
  • 19R. Lajugie, P. Bojanowski, P. Cuvillier, S. Arlot, F. Bach.

    A weakly-supervised discriminative model for audio-to-score alignment, in: 41st International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Shanghai, China, March 2016.

    https://hal.archives-ouvertes.fr/hal-01251018
  • 20A. Novikov, D. Podoprikhin, A. Osokin, D. Vetrov.

    Tensorizing Neural Networks, in: The 29-th Conference on Natural Information Processing Systems (NIPS), Montréal, Canada, December 2015.

    https://hal.archives-ouvertes.fr/hal-01237600
  • 21A. Podosinnikova, F. Bach, S. Lacoste-Julien.

    Rethinking LDA: Moment Matching for Discrete ICA, in: NIPS 2015 - Advances in Neural Information Processing Systems 28, Montreal, Canada, December 2015.

    https://hal.inria.fr/hal-01225271
  • 22R. Shapovalov, D. Vetrov, A. Osokin, P. Kohli.

    Multi-utility Learning: Structured-Output Learning with Multiple Annotation-Specific Loss Functions, in: Energy Minimization Methods in Computer Vision and Pattern Recognition, Hong Kong, China, Lecture Notes in Computer Science, January 2015, vol. 8932, pp. 406-420. [ DOI : 10.1007/978-3-319-14612-6_30 ]

    https://hal.archives-ouvertes.fr/hal-01237571
  • 23T.-H. Vu, A. Osokin, I. Laptev.

    Context-aware CNNs for person head detection, in: ICCV 2015 - IEEE International Conference on Computer Vision, Santiago, Chile, December 2015.

    https://hal.archives-ouvertes.fr/hal-01237618

Conferences without Proceedings

  • 24S. El Aouad, C. Dupuy, R. Teixeira, C. Diot, F. Bach.

    Exploiting crowd sourced reviews to explain movie recommendation, in: 2nd Workshop on Recommendation Systems for Television and Online Video, Vienna, Austria, September 2015.

    https://hal.inria.fr/hal-01193308
  • 25R. Shivanna, B. Chatterjee, R. Sankaran, C. Bhattacharyya, F. Bach.

    Spectral Norm Regularization of Orthonormal Representations for Graph Transduction, in: Neural Information Processing Systems, Montreal, Canada, December 2015.

    https://hal.archives-ouvertes.fr/hal-01265524
  • 26B. Thirion, F. Pedregosa, M. Eickenberg, G. Varoquaux.

    Correlations of correlations are not reliable statistics: implications for multivariate pattern analysis, in: ICML Workshop on Statistics, Machine Learning and Neuroscience (Stamlins 2015), Lille, France, Bertrand Thirion, Lars Kai Hansen, Sanmi Koyejo, July 2015.

    https://hal.inria.fr/hal-01187297

Internal Reports

Scientific Popularization

  • 28G. Varoquaux, E. Gouillart, O. Vahtras, V. Haenel, N. P. Rougier, R. Gommers, F. Pedregosa, Z. Jędrzejewski-Szmek, P. Virtanen, C. Combelles, D. Pinte, R. Cimrman, A. Espaze, A. Chauve, C. Burns.

    Scipy Lecture Notes, Zenodo, 2015. [ DOI : 10.5281/zenodo.31736 ]

    https://hal.inria.fr/hal-01206546

Other Publications



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