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Overall Objectives
Application Domains
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Bibliography
Overall Objectives
Application Domains
New Results
Bilateral Contracts and Grants with Industry
Partnerships and Cooperations
Bibliography


Bibliography

Publications of the year

Articles in International Peer-Reviewed Journals

International Conferences with Proceedings

  • 2J.-B. Alayrac, P. Bojanowski, N. Agrawal, J. Sivic, I. Laptev, S. Lacoste-Julien.

    Unsupervised Learning from Narrated Instruction Videos, in: CVPR2016 - 29th IEEE Conference on Computer Vision and Pattern Recognition, Las Vegas, United States, June 2016.

    https://hal.inria.fr/hal-01171193
  • 3F. Bach, V. Perchet.

    Highly-Smooth Zero-th Order Online Optimization Vianney Perchet, in: Conference on Learning Theory (COLT), New York, United States, June 2016.

    https://hal.archives-ouvertes.fr/hal-01321532
  • 4S. Bartunov, D. Kondrashkin, A. Osokin, D. Vetrov.

    Breaking Sticks and Ambiguities with Adaptive Skip-gram, in: Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), Cadiz, Spain, May 2016, pp. 130–138.

    https://hal.archives-ouvertes.fr/hal-01404056
  • 5A. Genevay, M. Cuturi, G. Peyré, F. Bach.

    Stochastic Optimization for Large-scale Optimal Transport, in: NIPS 2016 - Thirtieth Annual Conference on Neural Information Processing System, Barcelona, Spain, NIPS (editor), Proc. NIPS 2016, December 2016.

    https://hal.archives-ouvertes.fr/hal-01321664
  • 6P. Germain, F. Bach, A. Lacoste, S. Lacoste-Julien.

    PAC-Bayesian Theory Meets Bayesian Inference, in: Neural Information Processing Systems (NIPS 2016), Barcelone, Spain, Proceedings of the Neural Information Processing Systems Conference, December 2016.

    https://hal.archives-ouvertes.fr/hal-01324072
  • 7P. Germain, A. Habrard, F. Laviolette, E. Morvant.

    A New PAC-Bayesian Perspective on Domain Adaptation, in: 33rd International Conference on Machine Learning (ICML 2016), New York, NY, United States, Proceedings of the 33rd International Conference on Machine Learning, June 2016.

    https://hal.archives-ouvertes.fr/hal-01307045
  • 8A. Kirillov, M. Gavrikov, E. Lobacheva, A. Osokin, D. Vetrov.

    Deep Part-Based Generative Shape Model with Latent Variables, in: 27th British Machine Vision Conference (BMVC 2016), York, United Kingdom, September 2016.

    https://hal.archives-ouvertes.fr/hal-01404071
  • 9R. 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, Proceedings of the 41st International Conference on Acoustics, Speech, and Signal Processing (ICASSP), March 2016.

    https://hal.archives-ouvertes.fr/hal-01251018
  • 10A. Osokin, J.-B. Alayrac, I. Lukasewitz, P. K. Dokania, S. Lacoste-Julien.

    Minding the Gaps for Block Frank-Wolfe Optimization of Structured SVMs, in: International Conference on Machine Learning (ICML 2016), New York, United States, 2016, Appears in Proceedings of the 33rd International Conference on Machine Learning (ICML 2016). 31 pages.

    https://hal.archives-ouvertes.fr/hal-01323727
  • 11T. Shpakova, F. Bach.

    Parameter Learning for Log-supermodular Distributions, in: NIPS 2016 - Thirtieth Annual Conference on Neural Information Processing System, Barcelona, Spain, December 2016.

    https://hal.inria.fr/hal-01354789

Conferences without Proceedings

  • 12P. Balamurugan, F. Bach.

    Stochastic Variance Reduction Methods for Saddle-Point Problems, in: Neural Information Processing Systems (NIPS), Barcelona, Spain, Advances in Neural Information Processing Systems, December 2016.

    https://hal.archives-ouvertes.fr/hal-01319293
  • 13L. Bégin, P. Germain, F. Laviolette, J.-F. Roy.

    PAC-Bayesian Bounds based on the Rényi Divergence, in: International Conference on Artificial Intelligence and Statistics (AISTATS 2016), Cadiz, Spain, Proceedings of the 19th International Conference on Artificial Intelligence and Statistics, May 2016.

    https://hal.inria.fr/hal-01384783
  • 14I. Colin, C. Dupuy.

    Decentralized Topic Modelling with Latent Dirichlet Allocation, in: NIPS 2016 - 30th Conference on Neural Information Processing Systems, Barcelone, Spain, December 2016.

    https://hal.archives-ouvertes.fr/hal-01383111
  • 15A. Goyal, E. Morvant, P. Germain, M.-R. Amini.

    Théorèmes PAC-Bayésiens pour l'apprentissage multi-vues, in: Conférence Francophone sur l'Apprentissage Automatique (CAp), Marseille, France, July 2016.

    https://hal.archives-ouvertes.fr/hal-01329763
  • 16L. Landrieu, G. Obozinski.

    Cut Pursuit: fast algorithms to learn piecewise constant functions, in: 19th International Conference on Artificial Intelligence and Statistics (AISTATS 2016), Cadix, Spain, May 2016.

    https://hal.archives-ouvertes.fr/hal-01306786

Internal Reports

  • 17P. Germain, A. Habrard, F. Laviolette, E. Morvant.

    PAC-Bayesian Theorems for Domain Adaptation with Specialization to Linear Classifiers, Université Jean Monnet, Saint-Étienne (42) ; Département d'Informatique et de Génie Logiciel, Université Laval (Québec) ; ENS Paris ; IST Austria, August 2016, This report is a long version of our paper entitled A PAC-Bayesian Approach for Domain Adaptation with Specialization to Linear Classifiers published in the proceedings of the International Conference on Machine Learning (ICML) 2013. We improved our main results, extended our experiments, and proposed an extension to multisource domain adaptation.

    https://hal.archives-ouvertes.fr/hal-01134246

Other Publications

  • 18D. Babichev, F. Bach.

    Slice inverse regression with score functions, October 2016, working paper or preprint.

    https://hal.inria.fr/hal-01388498
  • 19F. Bach.

    Submodular Functions: from Discrete to Continous Domains, February 2016, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01222319
  • 20A. Dieuleveut, N. Flammarion, F. Bach.

    Harder, Better, Faster, Stronger Convergence Rates for Least-Squares Regression, February 2016, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01275431
  • 21C. Dupuy, F. Bach.

    Learning Determinantal Point Processes in Sublinear Time, October 2016, Under review for AISTATS 2017.

    https://hal.archives-ouvertes.fr/hal-01383742
  • 22C. Dupuy, F. Bach.

    Online but Accurate Inference for Latent Variable Models with Local Gibbs Sampling, July 2016, Under submission in JMLR.

    https://hal.inria.fr/hal-01284900
  • 23N. Flammarion, C. Mao, P. Rigollet.

    Optimal Rates of Statistical Seriation, November 2016, V2 corrects an error in Lemma A.1, v3 corrects appendix F on unimodal regression where the bounds now hold with polynomial probability rather than exponential.

    https://hal.archives-ouvertes.fr/hal-01405738
  • 24N. Flammarion, B. Palaniappan, F. Bach.

    Robust Discriminative Clustering with Sparse Regularizers, August 2016, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01357666
  • 25D. Garreau, S. Arlot.

    Consistent change-point detection with kernels, December 2016, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01416704
  • 26G. Gidel, T. Jebara, S. Lacoste-Julien.

    Frank-Wolfe Algorithms for Saddle Point Problems, October 2016, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01403348
  • 27A. Goyal, E. Morvant, P. Germain, M.-R. Amini.

    PAC-Bayesian Theorems for Multiview Learning, November 2016, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01336260
  • 28S. Lacoste-Julien.

    Convergence Rate of Frank-Wolfe for Non-Convex Objectives, June 2016, 6 pages.

    https://hal.inria.fr/hal-01415335
  • 29R. Leblond, F. Pedregosa, S. Lacoste-Julien.

    Asaga: Asynchronous Parallel Saga, December 2016, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01407833
  • 30A. Meurer​, C. P. Smith, M. Paprocki, O. Čertík, S. B. Kirpichev, M. Rocklin, A. Kumar, S. Ivanov, J. K. Moore, S. Singh, T. Rathnayake, S. Vig, B. E. Granger, R. P. Muller, F. Bonazzi, H. Gupta, S. Vats, F. Johansson, F. Pedregosa, M. J. Curry, A. R. Terrel, Š. Roučka, A. Saboo, I. Fernando, S. Kulal, R. Cimrman, A. Scopatz.

    SymPy: Symbolic computing in Python, May 2016, working paper or preprint. [ DOI : 10.7287/peerj.preprints.2083v3 ]

    https://hal.inria.fr/hal-01404156
  • 31A. Podosinnikova, F. Bach, S. Lacoste-Julien.

    Beyond CCA: Moment Matching for Multi-View Models, March 2016, working paper or preprint.

    https://hal.inria.fr/hal-01291060
  • 32V. Roulet, F. Fogel, A. D'Aspremont, F. Bach.

    Learning with Clustering Structure, October 2016, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01239305
  • 33M. Schmidt, N. Le Roux, F. Bach.

    Minimizing Finite Sums with the Stochastic Average Gradient, May 2016, Revision from January 2015 submission. Major changes: updated literature follow and discussion of subsequent work, additional Lemma showing the validity of one of the formulas, somewhat simplified presentation of Lyapunov bound, included code needed for checking proofs rather than the polynomials generated by the code, added error regions to the numerical experiments.

    https://hal.inria.fr/hal-00860051
  • 34D. Scieur, A. D'Aspremont, F. Bach.

    Regularized Nonlinear Acceleration, November 2016, working paper or preprint.

    https://hal.archives-ouvertes.fr/hal-01384682
  • 35G. Seguin, P. Bojanowski, R. Lajugie, I. Laptev.

    Instance-level video segmentation from object tracks, January 2016, working paper or preprint.

    https://hal.inria.fr/hal-01255765
  • 36K. S. Sesh Kumar, F. Bach.

    Active-set Methods for Submodular Minimization Problems, November 2016, working paper or preprint.

    https://hal.inria.fr/hal-01161759
References in notes
  • 37A. Hyvärinen.

    Estimation of non-normalized statistical models by score matching, in: Journal of Machine Learning Research, 2005, vol. 6, pp. 695–709.
  • 38K.-C. Li.

    Sliced Inverse Regression for Dimensional Reduction, in: Journal of the American Statistical Association, 1991, vol. 86, pp. 316–327.
  • 39T. M. Stoker.

    Consistent estimation of scaled coefficients, in: Econometrica, 1986, vol. 54, pp. 1461–1481.