Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri. Deep learning with kernels through RKHM and the Perron-Frobenius operator. Proceedings of the Thirty-seventh Conference on Neural Information Processing Systems, NeurIPS-23, 2023.@inproceedings{hashimoto2023deep,
title={Deep learning with kernels through RKHM and the Perron-Frobenius operator},
author={Hashimoto, Yuka and Ikeda, Masahiro and Kadri, Hachem},
booktitle={Proceedings of the Thirty-seventh Conference on Neural Information Processing Systems, NeurIPS-23},
year={2023}
}
Mathieu Roget, Hachem Kadri, Giuseppe Di Molfetta. Optimality conditions for spatial search with multiple marked vertices. Physical Review Research: 1-7, 2023.@article{roget2023optimality,
title={Optimality conditions for spatial search with multiple marked vertices},
author={Roget, Mathieu and Kadri, Hachem and Di Molfetta, Giuseppe},
journal={Physical Review Research},
year={2023},
pages={1--7}
}
Balthazar Casalé, Giuseppe Di Molfetta, S. Anthoine, Hachem Kadri. Large-scale quantum separability through a reproducible machine learning lens. arXiv preprint arXiv:2306.0944: 1-12, 2023.@article{casalé2023large,
title={Large-scale quantum separability through a reproducible machine learning lens},
author={Casalé, Balthazar and Di Molfetta, Giuseppe and Anthoine, S. and Kadri, Hachem },
journal={arXiv preprint arXiv:2306.0944},
year={2023},
pages={1--12}
}
Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri. Learning in RKHM: a C*-algebraic twist for kernel machines. Proceedings of the Twenty-sixth Conference on Artificial Intelligence and Statistics, AISTATS-23, 2023.@inproceedings{hashimoto2023learning,
title={Learning in RKHM: a C*-algebraic twist for kernel machines},
author={Hashimoto, Yuka and Ikeda, Masahiro and Kadri, Hachem},
booktitle={Proceedings of the Twenty-sixth Conference on Artificial Intelligence and Statistics, AISTATS-23},
year={2023}
}
Mathieu Roget, Giuseppe Di Molfetta, Hachem Kadri. Quantum perceptron revisited: computational-statistical tradeoffs. Proceedings of the Thirty-Eigth Conference on Uncertainty in Artificial Intelligence, UAI-22, 2022.@inproceedings{roget2022quantum,
title={Quantum perceptron revisited: computational-statistical tradeoffs},
author={Roget, Mathieu and Di Molfetta, Giuseppe and Kadri, Hachem},
booktitle={Proceedings of the Thirty-Eigth Conference on Uncertainty in Artificial Intelligence, UAI-22},
year={2022}
}
Riikka Huusari, Hachem Kadri. Entangled kernels -- beyond separability. Journal of Machine Learning Research (JMLR), 2021.@article{huusari2021entangled,
title={Entangled kernels -- beyond separability},
author={Huusari, Riikka and Kadri, Hachem },
journal={Journal of Machine Learning Research (JMLR)},
year={2021}
}
Balthazar Casalé, Giuseppe Di Molfetta, Hachem Kadri, Liva Ralaivola. Quantum bandits. Quantum Machine Intelligence, 2: 1-7, 2020.@article{casalé2020quantum,
title={Quantum bandits},
author={Casalé, Balthazar and Di Molfetta, Giuseppe and Kadri, Hachem and Ralaivola, Liva},
journal={Quantum Machine Intelligence},
year={2020},
volume={2},
pages={1--7}
}
Hachem Kadri, Stéphane Ayache, Riikka Huusari, Alain Rakotomamonjy, Liva Ralaivola. Partial trace regression and low-rank Kraus decomposition. Proceedings of the Thirty-Seventh International Conference on Machine Learning, ICML-20, 2020.@inproceedings{kadri2020partial,
title={Partial trace regression and low-rank Kraus decomposition},
author={Kadri, Hachem and Ayache, Stéphane and Huusari, Riikka and Rakotomamonjy, Alain and Ralaivola, Liva},
booktitle={Proceedings of the Thirty-Seventh International Conference on Machine Learning, ICML-20},
year={2020}
}
Riikka Huusari, Hachem Kadri. Entangled kernels. Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI-19, 2019.@inproceedings{huusari2019entangled,
title={Entangled kernels},
author={Huusari, Riikka and Kadri, Hachem},
booktitle={Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI-19},
year={2019}
}