Hachem Kadri

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

Achievements

+10 more ↓

🐣 Hot Topic Early Bird 🧭 Keyword Pioneer 🗺️ Taxonomy Completionist (14) 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (7)

🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🌱 Topic Pioneer 🏆 Keyword Champion (2) 🗃️ Keyword Collector (71) 📈 Trend Setter 💎 Century Club (18) 🔥 Unstoppable (7) 🚀 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) Stéphane Ayache (4) Cécile Capponi (3) Alain Rakotomamonjy (3) Yuka Hashimoto (3) Masahiro Ikeda (3) Thierry Artières (2) Sokol Koço (2) Stéphane 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