Hachem Kadri

According to our database, Hachem Kadri authored at least 50 papers between 2006 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Spectral Truncation Kernels: Noncommutativity in C^*-algebraic Kernel Machines.

Yuka Hashimoto, Ayoub Hafid, Masahiro Ikeda, Hachem Kadri

CoRR, 2024

C^*-Algebraic Machine Learning: Moving in a New Direction.

Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri

CoRR, 2024

Measuring hallucination in disentangled representations.

Hamed Benazha, Stéphane Ayache, Hachem Kadri, Thierry Artières

Proceedings of the International Joint Conference on Neural Networks, 2024

Position: C∗-Algebraic Machine Learning - Moving in a New Direction.

Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Implicit Regularization in Deep Tucker Factorization: Low-Rankness via Structured Sparsity.

Kais Hariz, Hachem Kadri, Stéphane Ayache, Maher Moakher, Thierry Artières

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

Orthogonal Random Features: Explicit Forms and Sharp Inequalities.

Nizar Demni, Hachem Kadri

CoRR, 2023

Large-Scale Quantum Separability Through a Reproducible Machine Learning Lens.

Balthazar Casalé, Giuseppe Di Molfetta, Sandrine Anthoine, Hachem Kadri

CoRR, 2023

Deep learning with kernels through RKHM and the Perron-Frobenius operator.

Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning in RKHM: a C*-Algebraic Twist for Kernel Machines.

Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Cross-View kernel transfer.

Riikka Huusari, Cécile Capponi, Paul Villoutreix, Hachem Kadri

Pattern Recognit., 2022

Toolbox for Multimodal Learn (scikit-multimodallearn).

Dominique Benielli, Baptiste Bauvin, Sokol Koço, Riikka Huusari, Cécile Capponi, Hachem Kadri, François Laviolette

J. Mach. Learn. Res., 2022

Learning in RKHM: a C^*-Algebraic Twist for Kernel Machines.

Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri

CoRR, 2022

Spatial search with multiple marked vertices is optimal for almost all queries and its quantum advantage is not always guaranteed.

Mathieu Roget, Hachem Kadri, Giuseppe Di Molfetta

CoRR, 2022

Quantum perceptron revisited: Computational-statistical tradeoffs.

Mathieu Roget, Giuseppe Di Molfetta, Hachem Kadri

Proceedings of the Uncertainty in Artificial Intelligence, 2022

Implicit Regularization with Polynomial Growth in Deep Tensor Factorization.

Kais Hariz, Hachem Kadri, Stéphane Ayache, Maher Moakher, Thierry Artières

Proceedings of the International Conference on Machine Learning, 2022

Scalable Ridge Leverage Score Sampling for the Nyström Method.

Farah Cherfaoui, Hachem Kadri, Liva Ralaivola

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

QuicK-means: accelerating inference for K-means by learning fast transforms.

Luc Giffon, Valentin Emiya, Hachem Kadri, Liva Ralaivola

Mach. Learn., 2021

Entangled Kernels - Beyond Separability.

Riikka Huusari, Hachem Kadri

J. Mach. Learn. Res., 2021

Learning primal-dual sparse kernel machines.

Riikka Huusari, Sahely Bhadra, Cécile Capponi, Hachem Kadri, Juho Rousu

CoRR, 2021

Implicit Regularization in Deep Tensor Factorization.

Paolo Milanesi, Hachem Kadri, Stéphane Ayache, Thierry Artières

Proceedings of the International Joint Conference on Neural Networks, 2021

PSM-nets: Compressing Neural Networks with Product of Sparse Matrices.

Luc Giffon, Stéphane Ayache, Hachem Kadri, Thierry Artières, Ronan Sicre

Proceedings of the International Joint Conference on Neural Networks, 2021

2020

Quantum bandits.

Balthazar Casalé, Giuseppe Di Molfetta, Hachem Kadri, Liva Ralaivola

Quantum Mach. Intell., 2020

Mapping individual differences in cortical architecture using multi-view representation learning.

Akrem Sellami, François-Xavier Dupé, Bastien Cagna, Hachem Kadri, Stéphane Ayache, Thierry Artières, Sylvain Takerkart

Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Partial Trace Regression and Low-Rank Kraus Decomposition.

Hachem Kadri, Stéphane Ayache, Riikka Huusari, Alain Rakotomamonjy, Liva Ralaivola

Proceedings of the 37th International Conference on Machine Learning, 2020

2019

Kernel transfer over multiple views for missing data completion.

Riikka Huusari, Cécile Capponi, Paul Villoutreix, Hachem Kadri

CoRR, 2019

QuicK-means: Acceleration of K-means by learning a fast transform.

Luc Giffon, Valentin Emiya, Liva Ralaivola, Hachem Kadri

CoRR, 2019

Deep Networks with Adaptive Nyström Approximation.

Luc Giffon, Stéphane Ayache, Thierry Artières, Hachem Kadri

Proceedings of the International Joint Conference on Neural Networks, 2019

Entangled Kernels.

Riikka Huusari, Hachem Kadri

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

Multi-view Metric Learning in Vector-valued Kernel Spaces.

Riikka Huusari, Hachem Kadri, Cécile Capponi

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

m-Power regularized least squares regression.

Julien Audiffren, Hachem Kadri

Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2016

Operator-valued Kernels for Learning from Functional Response Data.

Hachem Kadri, Emmanuel Duflos, Philippe Preux, Stéphane Canu, Alain Rakotomamonjy, Julien Audiffren

J. Mach. Learn. Res., 2016

Higher-Order Low-Rank Regression.

Guillaume Rabusseau, Hachem Kadri

CoRR, 2016

Low-Rank Regression with Tensor Responses.

Guillaume Rabusseau, Hachem Kadri

Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015

Operator-valued kernel recursive least squares algorithm.

Pierre-Olivier Amblard, Hachem Kadri

Proceedings of the 23rd European Signal Processing Conference, 2015

Online Learning with Operator-valued Kernels.

Julien Audiffren, Hachem Kadri

Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014

Equivalence of Learning Algorithms.

Julien Audiffren, Hachem Kadri

CoRR, 2014

2013

Multiple functional regression with both discrete and continuous covariates

Hachem Kadri, Philippe Preux, Emmanuel Duflos, Stéphane Canu

CoRR, 2013

Functional Regularized Least Squares Classi cation with Operator-valued Kernels

Hachem Kadri, Asma Rabaoui, Philippe Preux, Emmanuel Duflos, Alain Rakotomamonjy

CoRR, 2013

Online Learning with Multiple Operator-valued Kernels.

Julien Audiffren, Hachem Kadri

CoRR, 2013

A Generalized Kernel Approach to Structured Output Learning.

Hachem Kadri, Mohammad Ghavamzadeh, Philippe Preux

Proceedings of the 30th International Conference on Machine Learning, 2013

The Multi-Task Learning View of Multimodal Data.

Hachem Kadri, Stéphane Ayache, Cécile Capponi, Sokol Koço, François-Xavier Dupé, Emilie Morvant

Proceedings of the Asian Conference on Machine Learning, 2013

Stability of Multi-Task Kernel Regression Algorithms.

Julien Audiffren, Hachem Kadri

Proceedings of the Asian Conference on Machine Learning, 2013

2012

Multiple Operator-valued Kernel Learning.

Hachem Kadri, Alain Rakotomamonjy, Francis R. Bach, Philippe Preux

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Nonparametric Bayesian supervised classification of functional data.

Asma Rabaoui, Hachem Kadri, Manuel Davy

Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011

Functional Regularized Least Squares Classication with Operator-valued Kernels.

Hachem Kadri, Asma Rabaoui, Philippe Preux, Emmanuel Duflos, Alain Rakotomamonjy

Proceedings of the 28th International Conference on Machine Learning, 2011

Learning vocal tract variables with multi-task kernels.

Hachem Kadri, Emmanuel Duflos, Philippe Preux

Proceedings of the IEEE International Conference on Acoustics, 2011

2010

Nonlinear functional regression: a functional RKHS approach.

Hachem Kadri, Emmanuel Duflos, Philippe Preux, Stéphane Canu, Manuel Davy

Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

2008

One-Class SVMs Challenges in Audio Detection and Classification Applications.

Asma Rabaoui, Hachem Kadri, Zied Lachiri, Noureddine Ellouze

EURASIP J. Adv. Signal Process., 2008

Robust audio speaker segmentation using one class SVMS.

Hachem Kadri, Manuel Davy, Asma Rabaoui, Zied Lachiri, Noureddine Ellouze

Proceedings of the 2008 16th European Signal Processing Conference, 2008

2006

Hybrid approach for unsupervised Audio Speaker Segmentation.

Hachem Kadri, Zied Lachiri, Noureddine Ellouze

Proceedings of the 14th European Signal Processing Conference, 2006