
Learning primaldual sparse kernel machines
Traditionally, kernel methods rely on the representer theorem which stat...
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Quantum Perceptron Revisited: ComputationalStatistical Tradeoffs
Quantum machine learning algorithms could provide significant speedups ...
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Implicit Regularization in Deep Tensor Factorization
Attempts of studying implicit regularization associated to gradient desc...
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Entangled Kernels – Beyond Separability
We consider the problem of operatorvalued kernel learning and investiga...
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Partial Trace Regression and LowRank Kraus Decomposition
The trace regression model, a direct extension of the wellstudied linea...
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Mapping individual differences in cortical architecture using multiview representation learning
In neuroscience, understanding interindividual differences has recently...
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Quantum Bandits
We consider the quantum version of the bandit problem known as best arm...
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Deep Networks with Adaptive Nyström Approximation
Recent work has focused on combining kernel methods and deep learning to...
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Kernel transfer over multiple views for missing data completion
We consider the kernel completion problem with the presence of multiple ...
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QuicKmeans: Acceleration of Kmeans by learning a fast transform
Kmeans  and the celebrated Lloyd algorithm  is more than the cluste...
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Multiview Metric Learning in Vectorvalued Kernel Spaces
We consider the problem of metric learning for multiview data and prese...
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Operatorvalued Kernels for Learning from Functional Response Data
In this paper we consider the problems of supervised classification and ...
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MPower Regularized Least Squares Regression
Regularization is used to find a solution that both fits the data and is...
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Stability of MultiTask Kernel Regression Algorithms
We study the stability properties of nonlinear multitask regression in ...
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Multiple functional regression with both discrete and continuous covariates
In this paper we present a nonparametric method for extending functional...
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Functional Regularized Least Squares Classi cation with Operatorvalued Kernels
Although operatorvalued kernels have recently received increasing inter...
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A Generalized Kernel Approach to Structured Output Learning
We study the problem of structured output learning from a regression per...
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Multiple Operatorvalued Kernel Learning
Positive definite operatorvalued kernels generalize the wellknown noti...
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Hachem Kadri
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