Hachem Kadri
20 papers · 2010–2026 · 7 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
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🗺️ Taxonomy Completionist (30) 🏃 Academic Marathon · Full 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Silver 🐣 Hot Topic Early Bird
🌱
Topic Pioneer
🔬
Deep Specialist
(10)
🏆
Keyword Champion
(7)
📈
Trend Setter
🚀
Conference Pioneer
🔥
Unstoppable · Bronze
🗃️
Keyword Collector
(84)
💎
Century Club · Bronze
Top co-authors
Research topics
Machine Learning
(19)
Core Methods
(16)
Optimization & Theory · Machine Learning
(9)
Mathematics & Optimization
(8)
Deep Learning
(7)
Mathematics
(5)
Optimization
(4)
Optimization & Theory · Deep Learning
(4)
Artificial Intelligence
(3)
Interdisciplinary
(3)
Core AI
(3)
Learning Types · Machine Learning
(3)
Learning Types · Deep Learning
(3)
Science
(3)
Architectures
(2)
Keywords
kernel methods
(9)
operator-valued kernel
(7)
reproducing kernel hilbert space
(6)
generalization bound
(3)
kernel learning
(3)
quantum computing
(3)
tensor factorization
(2)
low-rank approximation
(2)
implicit regularization
(2)
multimodal learning
(2)
functional regression
(2)
functional data analysis
(2)
representer theorem
(2)
convolutional neural network
(2)
kernel alignment
(2)
kraus decomposition
(1)
low-rank decomposition
(1)
partial trace regression
(1)
computational complexity
(1)
supervised learning
(1)
Papers
Benign Overfitting with Quantum Kernels
UAI 2026
Spectral Truncation Kernels: Noncommutativity in C*-algebraic Kernel Machines
JMLR 2026
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
NeurIPS 2023
Learning in RKHM: a C*-Algebraic Twist for Kernel Machines
AISTATS 2023
Implicit Regularization with Polynomial Growth in Deep Tensor Factorization
ICML 2022
Quantum perceptron revisited: Computational-statistical tradeoffs
UAI 2022
Toolbox for Multimodal Learn (scikit-multimodallearn)
JMLR 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
NeurIPS 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
NeurIPS 2012
Nonlinear functional regression: a functional RKHS approach
AISTATS 2010