{"id":310,"date":"2020-05-28T17:32:00","date_gmt":"2020-05-28T17:32:00","guid":{"rendered":"https:\/\/quantml.lis-lab.fr\/?page_id=310"},"modified":"2023-10-08T01:53:38","modified_gmt":"2023-10-08T01:53:38","slug":"publications","status":"publish","type":"page","link":"https:\/\/quantml.lis-lab.fr\/index.php\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"\n<p><\/p>\n\n\n\n<p><\/p>\n\n\n\n<p><code><div class=\"wpbibtex-item\">Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri. Deep learning with kernels through RKHM and the Perron-Frobenius operator. <em>Proceedings of the Thirty-seventh Conference on Neural Information Processing Systems, NeurIPS-23<\/em>, 2023.<ul class=\"inline\"><li><a href='https:\/\/arxiv.org\/abs\/2305.13588' target='_blank'>[Download PDF]<\/a><\/li><li><a href=\"javascript:void(0);\" class=\"wpbibtex-trigger\">[BibTeX]<\/a><\/li><\/ul><div class=\"bibtex\"><pre><code>@inproceedings{hashimoto2023deep,\n  title={Deep learning with kernels through RKHM and the Perron-Frobenius operator},\n  author={Hashimoto, Yuka and Ikeda, Masahiro and Kadri, Hachem},\n  booktitle={Proceedings of the Thirty-seventh Conference on Neural Information Processing Systems, NeurIPS-23},\n  year={2023}\n}<\/code><\/pre><\/div><\/div><\/code><\/p>\n\n\n\n<p><code><div class=\"wpbibtex-item\">Mathieu Roget, Hachem Kadri, Giuseppe Di Molfetta. Optimality conditions for spatial search with multiple marked vertices. <em>Physical Review Research<\/em>: 1-7, 2023.<ul class=\"inline\"><li><a href='https:\/\/journals.aps.org\/prresearch\/abstract\/10.1103\/PhysRevResearch.5.033021' target='_blank'>[Download PDF]<\/a><\/li><li><a href=\"javascript:void(0);\" class=\"wpbibtex-trigger\">[BibTeX]<\/a><\/li><\/ul><div class=\"bibtex\"><pre><code>@article{roget2023optimality,\n  title={Optimality conditions for spatial search with multiple marked vertices},\n  author={Roget, Mathieu and Kadri, Hachem and Di Molfetta, Giuseppe},\n  journal={Physical Review Research},\n  year={2023},\n  pages={1--7}\n}<\/code><\/pre><\/div><\/div><\/code><\/p>\n\n\n\n<p><code><div class=\"wpbibtex-item\">Balthazar Casal\u00e9, Giuseppe Di Molfetta, S. Anthoine, Hachem Kadri. Large-scale quantum separability through a reproducible machine learning lens. <em>arXiv preprint arXiv:2306.0944<\/em>: 1-12, 2023.<ul class=\"inline\"><li><a href='https:\/\/arxiv.org\/abs\/2306.09444' target='_blank'>[Download PDF]<\/a><\/li><li><a href=\"javascript:void(0);\" class=\"wpbibtex-trigger\">[BibTeX]<\/a><\/li><\/ul><div class=\"bibtex\"><pre><code>@article{casal\u00e92023large,\n  title={Large-scale quantum separability through a reproducible machine learning lens},\n  author={Casal\u00e9, Balthazar and Di Molfetta, Giuseppe and Anthoine, S. and Kadri, Hachem },\n  journal={arXiv preprint arXiv:2306.0944},\n  year={2023},\n  pages={1--12}\n}<\/code><\/pre><\/div><\/div><\/code><\/p>\n\n\n\n<p><code><div class=\"wpbibtex-item\">Yuka Hashimoto, Masahiro Ikeda, Hachem Kadri. Learning in RKHM: a C*-algebraic twist for kernel machines. <em>Proceedings of the Twenty-sixth Conference on Artificial Intelligence and Statistics, AISTATS-23<\/em>, 2023.<ul class=\"inline\"><li><a href='https:\/\/arxiv.org\/abs\/2210.11855' target='_blank'>[Download PDF]<\/a><\/li><li><a href=\"javascript:void(0);\" class=\"wpbibtex-trigger\">[BibTeX]<\/a><\/li><\/ul><div class=\"bibtex\"><pre><code>@inproceedings{hashimoto2023learning,\n  title={Learning in RKHM: a C*-algebraic twist for kernel machines},\n  author={Hashimoto, Yuka and Ikeda, Masahiro and Kadri, Hachem},\n  booktitle={Proceedings of the Twenty-sixth Conference on Artificial Intelligence and Statistics, AISTATS-23},\n  year={2023}\n}<\/code><\/pre><\/div><\/div><\/code><\/p>\n\n\n\n<p><code><div class=\"wpbibtex-item\">Mathieu Roget, Giuseppe Di Molfetta, Hachem Kadri. Quantum perceptron revisited: computational-statistical tradeoffs. <em>Proceedings of the Thirty-Eigth Conference on Uncertainty in Artificial Intelligence, UAI-22<\/em>, 2022.<ul class=\"inline\"><li><a href='https:\/\/arxiv.org\/abs\/2106.02496' target='_blank'>[Download PDF]<\/a><\/li><li><a href='https:\/\/github.com\/mroget\/Quantum-perceptron-models' target='_blank'>[Download Code]<\/a><\/li><li><a href=\"javascript:void(0);\" class=\"wpbibtex-trigger\">[BibTeX]<\/a><\/li><\/ul><div class=\"bibtex\"><pre><code>@inproceedings{roget2022quantum,\n  title={Quantum perceptron revisited: computational-statistical tradeoffs},\n  author={Roget, Mathieu and Di Molfetta, Giuseppe and Kadri, Hachem},\n  booktitle={Proceedings of the Thirty-Eigth Conference on Uncertainty in Artificial Intelligence, UAI-22},\n  year={2022}\n}<\/code><\/pre><\/div><\/div><\/code><\/p>\n\n\n\n<p><code><div class=\"wpbibtex-item\">Riikka Huusari, Hachem Kadri. Entangled kernels -- beyond separability. <em>Journal of Machine Learning Research (JMLR)<\/em>, 2021.<ul class=\"inline\"><li><a href='https:\/\/jmlr.org\/papers\/v22\/19-665.html' target='_blank'>[Download PDF]<\/a><\/li><li><a href=\"javascript:void(0);\" class=\"wpbibtex-trigger\">[BibTeX]<\/a><\/li><\/ul><div class=\"bibtex\"><pre><code>@article{huusari2021entangled,\n  title={Entangled kernels -- beyond separability},\n  author={Huusari, Riikka and Kadri, Hachem },\n  journal={Journal of Machine Learning Research (JMLR)},\n  year={2021}\n}<\/code><\/pre><\/div><\/div><\/code><\/p>\n\n\n\n<p><code><div class=\"wpbibtex-item\">Balthazar Casal\u00e9, Giuseppe Di Molfetta, Hachem Kadri, Liva Ralaivola. Quantum bandits. <em>Quantum Machine Intelligence<\/em>, 2: 1-7, 2020.<ul class=\"inline\"><li><a href='https:\/\/doi.org\/10.1007\/s42484-020-00024-8' target='_blank'>[Download PDF]<\/a><\/li><li><a href=\"javascript:void(0);\" class=\"wpbibtex-trigger\">[BibTeX]<\/a><\/li><\/ul><div class=\"bibtex\"><pre><code>@article{casal\u00e92020quantum,\n  title={Quantum bandits},\n  author={Casal\u00e9, Balthazar and Di Molfetta, Giuseppe and Kadri, Hachem and Ralaivola, Liva},\n  journal={Quantum Machine Intelligence},\n  year={2020},\n  volume={2},\n  pages={1--7}\n}<\/code><\/pre><\/div><\/div><\/code><\/p>\n\n\n\n<p><code><div class=\"wpbibtex-item\">Hachem Kadri, St\u00e9phane Ayache, Riikka Huusari, Alain Rakotomamonjy, Liva Ralaivola. Partial trace regression and low-rank Kraus decomposition. <em>Proceedings of the Thirty-Seventh International Conference on Machine Learning, ICML-20<\/em>, 2020.<ul class=\"inline\"><li><a href='http:\/\/proceedings.mlr.press\/v119\/kadri20a.html' target='_blank'>[Download PDF]<\/a><\/li><li><a href='https:\/\/github.com\/Stef-hub\/partial_trace_kraus' target='_blank'>[Download Code]<\/a><\/li><li><a href=\"javascript:void(0);\" class=\"wpbibtex-trigger\">[BibTeX]<\/a><\/li><\/ul><div class=\"bibtex\"><pre><code>@inproceedings{kadri2020partial,\n  title={Partial trace regression and low-rank Kraus decomposition},\n  author={Kadri, Hachem and Ayache, St\u00e9phane and Huusari, Riikka and Rakotomamonjy, Alain and Ralaivola, Liva},\n  booktitle={Proceedings of the Thirty-Seventh International Conference on Machine Learning, ICML-20},\n  year={2020}\n}<\/code><\/pre><\/div><\/div><\/code><\/p>\n\n\n\n<p><code><div class=\"wpbibtex-item\">Riikka Huusari, Hachem Kadri. Entangled kernels. <em>Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI-19<\/em>, 2019.<ul class=\"inline\"><li><a href='https:\/\/www.ijcai.org\/Proceedings\/2019\/358' target='_blank'>[Download PDF]<\/a><\/li><li><a href=\"javascript:void(0);\" class=\"wpbibtex-trigger\">[BibTeX]<\/a><\/li><\/ul><div class=\"bibtex\"><pre><code>@inproceedings{huusari2019entangled,\n  title={Entangled kernels},\n  author={Huusari, Riikka and Kadri, Hachem},\n  booktitle={Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI-19},\n  year={2019}\n}<\/code><\/pre><\/div><\/div><\/code><\/p>\n","protected":false},"excerpt":{"rendered":"","protected":false},"author":2,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-310","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/quantml.lis-lab.fr\/index.php\/wp-json\/wp\/v2\/pages\/310","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/quantml.lis-lab.fr\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/quantml.lis-lab.fr\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/quantml.lis-lab.fr\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/quantml.lis-lab.fr\/index.php\/wp-json\/wp\/v2\/comments?post=310"}],"version-history":[{"count":101,"href":"https:\/\/quantml.lis-lab.fr\/index.php\/wp-json\/wp\/v2\/pages\/310\/revisions"}],"predecessor-version":[{"id":625,"href":"https:\/\/quantml.lis-lab.fr\/index.php\/wp-json\/wp\/v2\/pages\/310\/revisions\/625"}],"wp:attachment":[{"href":"https:\/\/quantml.lis-lab.fr\/index.php\/wp-json\/wp\/v2\/media?parent=310"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}