Hachem Kadri

According to our database1, Hachem Kadri authored at least 46 papers between 2006 and 2024.

Collaborative distances:

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
C<sup>*</sup>-Algebraic Machine Learning: Moving in a New Direction.
CoRR, 2024

2023
Orthogonal Random Features: Explicit Forms and Sharp Inequalities.
CoRR, 2023

Large-Scale Quantum Separability Through a Reproducible Machine Learning Lens.
CoRR, 2023

Deep learning with kernels through RKHM and the Perron-Frobenius operator.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Learning in RKHM: a C*-Algebraic Twist for Kernel Machines.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022
Cross-View kernel transfer.
Pattern Recognit., 2022

Toolbox for Multimodal Learn (scikit-multimodallearn).
J. Mach. Learn. Res., 2022

Learning in RKHM: a C<sup>*</sup>-Algebraic Twist for Kernel Machines.
CoRR, 2022

Spatial search with multiple marked vertices is optimal for almost all queries and its quantum advantage is not always guaranteed.
CoRR, 2022

Quantum perceptron revisited: Computational-statistical tradeoffs.
Proceedings of the Uncertainty in Artificial Intelligence, 2022

Implicit Regularization with Polynomial Growth in Deep Tensor Factorization.
Proceedings of the International Conference on Machine Learning, 2022

Scalable Ridge Leverage Score Sampling for the Nyström Method.
Proceedings of the IEEE International Conference on Acoustics, 2022

2021
QuicK-means: accelerating inference for K-means by learning fast transforms.
Mach. Learn., 2021

Entangled Kernels - Beyond Separability.
J. Mach. Learn. Res., 2021

Learning primal-dual sparse kernel machines.
CoRR, 2021

Implicit Regularization in Deep Tensor Factorization.
Proceedings of the International Joint Conference on Neural Networks, 2021

PSM-nets: Compressing Neural Networks with Product of Sparse Matrices.
Proceedings of the International Joint Conference on Neural Networks, 2021

2020
Quantum bandits.
Quantum Mach. Intell., 2020

Mapping individual differences in cortical architecture using multi-view representation learning.
Proceedings of the 2020 International Joint Conference on Neural Networks, 2020

Partial Trace Regression and Low-Rank Kraus Decomposition.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
Kernel transfer over multiple views for missing data completion.
CoRR, 2019

QuicK-means: Acceleration of K-means by learning a fast transform.
CoRR, 2019

Deep Networks with Adaptive Nyström Approximation.
Proceedings of the International Joint Conference on Neural Networks, 2019

Entangled Kernels.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018
Multi-view Metric Learning in Vector-valued Kernel Spaces.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
m-Power regularized least squares regression.
Proceedings of the 2017 International Joint Conference on Neural Networks, 2017

2016
Operator-valued Kernels for Learning from Functional Response Data.
J. Mach. Learn. Res., 2016

Higher-Order Low-Rank Regression.
CoRR, 2016

Low-Rank Regression with Tensor Responses.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016

2015
Operator-valued kernel recursive least squares algorithm.
Proceedings of the 23rd European Signal Processing Conference, 2015

Online Learning with Operator-valued Kernels.
Proceedings of the 23rd European Symposium on Artificial Neural Networks, 2015

2014
Equivalence of Learning Algorithms.
CoRR, 2014

2013
Multiple functional regression with both discrete and continuous covariates
CoRR, 2013

Functional Regularized Least Squares Classi cation with Operator-valued Kernels
CoRR, 2013

Online Learning with Multiple Operator-valued Kernels.
CoRR, 2013

A Generalized Kernel Approach to Structured Output Learning.
Proceedings of the 30th International Conference on Machine Learning, 2013

The Multi-Task Learning View of Multimodal Data.
Proceedings of the Asian Conference on Machine Learning, 2013

Stability of Multi-Task Kernel Regression Algorithms.
Proceedings of the Asian Conference on Machine Learning, 2013

2012
Multiple Operator-valued Kernel Learning.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

Nonparametric Bayesian supervised classification of functional data.
Proceedings of the 2012 IEEE International Conference on Acoustics, 2012

2011
Functional Regularized Least Squares Classication with Operator-valued Kernels.
Proceedings of the 28th International Conference on Machine Learning, 2011

Learning vocal tract variables with multi-task kernels.
Proceedings of the IEEE International Conference on Acoustics, 2011

2010
Nonlinear functional regression: a functional RKHS approach.
Proceedings of the Thirteenth International Conference on Artificial Intelligence and Statistics, 2010

2008
One-Class SVMs Challenges in Audio Detection and Classification Applications.
EURASIP J. Adv. Signal Process., 2008

Robust audio speaker segmentation using one class SVMS.
Proceedings of the 2008 16th European Signal Processing Conference, 2008

2006
Hybrid approach for unsupervised Audio Speaker Segmentation.
Proceedings of the 14th European Signal Processing Conference, 2006


  Loading...