Hybrid approach for unsupervised Audio Speaker Segmentation. - Hachem Kadri; Zied Lachiri; Noureddine Ellouze (EUSIPCO, 2006)

Robust audio speaker segmentation using one class SVMS. - Hachem Kadri; Manuel Davy; Asma Rabaoui; Zied Lachiri; Noureddine Ellouze (EUSIPCO, 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)

Nonlinear functional regression: a functional RKHS approach. - Hachem Kadri; Emmanuel Duflos; Philippe Preux; Stéphane Canu; Manuel Davy (AISTATS, 2010)

Learning vocal tract variables with multi-task kernels. - Hachem Kadri; Emmanuel Duflos; Philippe Preux (ICASSP, 2011)

Functional Regularized Least Squares Classication with Operator-valued Kernels. - Hachem Kadri; Asma Rabaoui; Philippe Preux; Emmanuel Duflos; Alain Rakotomamonjy (ICML, 2011)

Nonparametric Bayesian supervised classification of functional data. - Asma Rabaoui; Hachem Kadri; Manuel Davy (ICASSP, 2012)

Multiple Operator-valued Kernel Learning. - Hachem Kadri; Alain Rakotomamonjy; Francis R. Bach; Philippe Preux (NIPS, 2012)

Stability of Multi-Task Kernel Regression Algorithms. - Julien Audiffren; Hachem Kadri (ACML, 2013)

The Multi-Task Learning View of Multimodal Data. - Hachem Kadri; Stéphane Ayache; Cécile Capponi; Sokol Koço; François-Xavier Dupé; Emilie Morvant (ACML, 2013)

A Generalized Kernel Approach to Structured Output Learning. - Hachem Kadri; Mohammad Ghavamzadeh; Philippe Preux (ICML (1), 2013)

Online Learning with Multiple Operator-valued Kernels. - Julien Audiffren; Hachem Kadri (CoRR, 2013)

Functional Regularized Least Squares Classi cation with Operator-valued Kernels - Hachem Kadri; Asma Rabaoui; Philippe Preux; Emmanuel Duflos; Alain Rakotomamonjy (CoRR, 2013)

Multiple functional regression with both discrete and continuous covariates - Hachem Kadri; Philippe Preux; Emmanuel Duflos; Stéphane Canu (CoRR, 2013)

Equivalence of Learning Algorithms. - Julien Audiffren; Hachem Kadri (CoRR, 2014)

Online Learning with Operator-valued Kernels. - Julien Audiffren; Hachem Kadri (ESANN, 2015)

Operator-valued kernel recursive least squares algorithm. - Pierre-Olivier Amblard; Hachem Kadri (EUSIPCO, 2015)

Low-Rank Regression with Tensor Responses. - Guillaume Rabusseau; Hachem Kadri (NIPS, 2016)

Higher-Order Low-Rank Regression. - Guillaume Rabusseau; Hachem Kadri (CoRR, 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)

m-Power regularized least squares regression. - Julien Audiffren; Hachem Kadri (IJCNN, 2017)

Multi-view Metric Learning in Vector-valued Kernel Spaces. - Riikka Huusari; Hachem Kadri; Cécile Capponi (AISTATS, 2018)

Entangled Kernels. - Riikka Huusari; Hachem Kadri (IJCAI, 2019)

Deep Networks with Adaptive Nyström Approximation. - Luc Giffon; Stéphane Ayache; Thierry Artières; Hachem Kadri (IJCNN, 2019)

QuicK-means: Acceleration of K-means by learning a fast transform. - Luc Giffon; Valentin Emiya; Liva Ralaivola; Hachem Kadri (CoRR, 2019)

Kernel transfer over multiple views for missing data completion. - Riikka Huusari; Cécile Capponi; Paul Villoutreix; Hachem Kadri (CoRR, 2019)

Partial Trace Regression and Low-Rank Kraus Decomposition. - Hachem Kadri; Stéphane Ayache; Riikka Huusari; Alain Rakotomamonjy; Liva Ralaivola (ICML, 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 (IJCNN, 2020)

Quantum bandits. - Balthazar Casalé; Giuseppe Di Molfetta; Hachem Kadri; Liva Ralaivola (Quantum Mach. Intell., 2020)

PSM-nets: Compressing Neural Networks with Product of Sparse Matrices. - Luc Giffon; Stéphane Ayache; Hachem Kadri; Thierry Artières; Ronan Sicre (IJCNN, 2021)

Implicit Regularization in Deep Tensor Factorization. - Paolo Milanesi; Hachem Kadri; Stéphane Ayache; Thierry Artières (IJCNN, 2021)

Learning primal-dual sparse kernel machines. - Riikka Huusari; Sahely Bhadra; Cécile Capponi; Hachem Kadri; Juho Rousu (CoRR, 2021)

Entangled Kernels - Beyond Separability. - Riikka Huusari; Hachem Kadri (J. Mach. Learn. Res., 2021)

QuicK-means: accelerating inference for K-means by learning fast transforms. - Luc Giffon; Valentin Emiya; Hachem Kadri; Liva Ralaivola (Mach. Learn., 2021)

Scalable Ridge Leverage Score Sampling for the Nyström Method. - Farah Cherfaoui; Hachem Kadri; Liva Ralaivola (ICASSP, 2022)

Implicit Regularization with Polynomial Growth in Deep Tensor Factorization. - Kais Hariz; Hachem Kadri; Stéphane Ayache; Maher Moakher; Thierry Artières (ICML, 2022)

Quantum perceptron revisited: Computational-statistical tradeoffs. - Mathieu Roget; Giuseppe Di Molfetta; Hachem Kadri (UAI, 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)

Learning in RKHM: a C*-Algebraic Twist for Kernel Machines. - Yuka Hashimoto; Masahiro Ikeda; Hachem Kadri (CoRR, 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)

Cross-View kernel transfer. - Riikka Huusari; Cécile Capponi; Paul Villoutreix; Hachem Kadri (Pattern Recognit., 2022)

Learning in RKHM: a C*-Algebraic Twist for Kernel Machines. - Yuka Hashimoto; Masahiro Ikeda; Hachem Kadri (AISTATS, 2023)

Deep learning with kernels through RKHM and the Perron-Frobenius operator. - Yuka Hashimoto; Masahiro Ikeda; Hachem Kadri (NeurIPS, 2023)

Large-Scale Quantum Separability Through a Reproducible Machine Learning Lens. - Balthazar Casalé; Giuseppe Di Molfetta; Sandrine Anthoine; Hachem Kadri (CoRR, 2023)

Implicit Regularization in Deep Tucker Factorization: Low-Rankness via Structured Sparsity. - Kais Hariz; Hachem Kadri; Stéphane Ayache; Maher Moakher; Thierry Artières (AISTATS, 2024)

Position: C∗-Algebraic Machine Learning - Moving in a New Direction. - Yuka Hashimoto; Masahiro Ikeda; Hachem Kadri (ICML, 2024)

Measuring hallucination in disentangled representations. - Hamed Benazha; Stéphane Ayache; Hachem Kadri; Thierry Artières (IJCNN, 2024)

C*-Algebraic Machine Learning: Moving in a New Direction. - Yuka Hashimoto; Masahiro Ikeda; Hachem Kadri (CoRR, 2024)

Spectral Truncation Kernels: Noncommutativity in C*-algebraic Kernel Machines. - Yuka Hashimoto; Ayoub Hafid; Masahiro Ikeda; Hachem Kadri (CoRR, 2024)

Orthogonal Random Features: Explicit Forms and Sharp Inequalities. - Nizar Demni; Hachem Kadri (Trans. Mach. Learn. Res., 2024)

Benign Overfitting with Quantum Kernels. - Joachim Tomasi; Sandrine Anthoine; Hachem Kadri (CoRR, 2025)

On Quantum Perceptron Learning via Quantum Search. - Xiaoyu Sun; Mathieu Roget; Giuseppe Di Molfetta; Hachem Kadri (CoRR, 2025)

Towards Quantum Operator-Valued Kernels. - Hachem Kadri; Joachim Tomasi; Yuka Hashimoto; Sandrine Anthoine (CoRR, 2025)