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Hachem Kadri

18 papers · 2010–2024 · 7 conferences · across top CS/AI conferences

Achievements

๐Ÿƒ Academic Marathon (14) ๐Ÿ Cross-Pollinator (9) ๐ŸŒ Conference Polyglot (7) ๐Ÿ—บ๏ธ Taxonomy Completionist (14) ๐ŸŒˆ Renaissance Researcher (6) ๐Ÿงญ Keyword Pioneer ๐Ÿฃ Hot Topic Early Bird ๐ŸŒ‰ Interdisciplinary Bridge ๐ŸŒฑ Topic Pioneer ๐Ÿ† Keyword Champion (2) ๐Ÿ—ƒ๏ธ Keyword Collector (71) ๐Ÿ“ˆ Trend Setter ๐Ÿ’Ž Century Club (18) ๐Ÿ”ฅ Unstoppable (7) ๐Ÿš€ Conference Pioneer

Conferences

AISTATS (4) ICML (4) JMLR (3) NIPS (3) ACML (2) IJCAI (1) UAI (1)

Top co-authors

Riikka Huusari (5) Philippe Preux (4) Stรฉphane Ayache (4) Cรฉcile Capponi (3) Alain Rakotomamonjy (3) Yuka Hashimoto (3) Masahiro Ikeda (3) Thierry Artiรจres (2) Sokol Koรงo (2) Stรฉphane Canu (2)

Research topics

Applications (1)

Keywords

kernel methods (7) operator-valued kernel (6) reproducing kernel hilbert space (5) kernel learning (3) generalization bound (3) low-rank approximation (2) quantum computing (2) representer theorem (2) functional regression (2) implicit regularization (2) kernel alignment (2) tensor factorization (2) multimodal learning (2) functional data analysis (2) convolutional neural network (2) kraus decomposition (1) quantum machine learning (1) low-rank decomposition (1) partial trace regression (1) multi-task learning (1)

Papers

Implicit Regularization in Deep Tucker Factorization: Low-Rankness via Structured Sparsity AISTATS 2024
Position: $C^*$-Algebraic Machine Learning $-$ Moving in a New Direction ICML 2024
Deep learning with kernels through RKHM and the Perron-Frobenius operator NIPS 2023
Learning in RKHM: a C*-Algebraic Twist for Kernel Machines AISTATS 2023
Toolbox for Multimodal Learn (scikit-multimodallearn) JMLR 2022
Quantum perceptron revisited: Computational-statistical tradeoffs UAI 2022
Implicit Regularization with Polynomial Growth in Deep Tensor Factorization ICML 2022
Entangled Kernels - Beyond Separability JMLR 2021
Partial Trace Regression and Low-Rank Kraus Decomposition ICML 2020
Entangled Kernels IJCAI 2019
Multi-view Metric Learning in Vector-valued Kernel Spaces AISTATS 2018
Low-Rank Regression with Tensor Responses NIPS 2016
Operator-valued Kernels for Learning from Functional Response Data JMLR 2016
A Generalized Kernel Approach to Structured Output Learning ICML 2013
Stability of Multi-Task Kernel Regression Algorithms ACML 2013
The Multi-Task Learning View of Multimodal Data ACML 2013
Multiple Operator-valued Kernel Learning NIPS 2012
Nonlinear functional regression: a functional RKHS approach AISTATS 2010