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Regularization, Optimization, Kernels, and Support Vector Machines

1st, 2015

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A kernel-based framework to tensorial data analysis

Neural networks, 2011-10, Vol.24 (8), p.861-874

2011

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Tensor Versus Matrix Completion: A Comparison With Application to Spectral Data

IEEE signal processing letters, 2011-07, Vol.18 (7), p.403-406

2011

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Classification of Multichannel Signals With Cumulant-Based Kernels

IEEE transactions on signal processing, 2012-05, Vol.60 (5), p.2304-2314

2012

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A kernel-based framework to tensorial data analysis: Artificial Neural Networks: Selected papers from ICANN 2010

Neural networks, 2011, Vol.24 (8), p.861-874

2011

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The Why and How of Nonnegative Matrix Factorization

Regularization, Optimization, Kernels, and Support Vector Machines, 2015, p.275-310

2015

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Automatic Seizure Detection Incorporating Structural Information

Artificial Neural Networks and Machine Learning – ICANN 2011, p.233-240

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Kernel-Based Learning from Infinite Dimensional 2-Way Tensors

Artificial Neural Networks – ICANN 2010, p.59-69

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Quadratically Constrained Quadratic Programming for Subspace Selection in Kernel Regression Estimation

Artificial Neural Networks - ICANN 2008, p.175-184

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Hybrid Conditional Gradient-Smoothing Algorithms with Applications to Sparse and Low Rank Regularization

Regularization, Optimization, Kernels, and Support Vector Machines, 2015, p.71-100

2015

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High level high performance computing for multitask learning of time-varying models

2014 IEEE Symposium on Computational Intelligence in Big Data (CIBD), 2014, p.1-6

2014

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Semi-supervised Learning of Sparse Linear Models in Mass Spectral Imaging

Pattern Recognition in Bioinformatics, p.325-334

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An Equivalence between the Lasso and Support Vector Machines

Regularization, Optimization, Kernels, and Support Vector Machines, 2015, p.19-44

2015

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DynOpt: Incorporating dynamics into mean-variance portfolio optimization

2013 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr), 2013, p.48-54

2013

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Classification of Structured EEG Tensors Using Nuclear Norm Regularization: Improving P300 Classification

2013 International Workshop on Pattern Recognition in Neuroimaging, 2013, p.98-101

2013

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Learning Constrained Task Similarities in Graph-Regularized Multi-Task Learning

Regularization, Optimization, Kernels, and Support Vector Machines, 2015, p.121-148

2015

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Multi-Layer Support Vector Machines

Regularization, Optimization, Kernels, and Support Vector Machines, 2015, p.475-494

2015

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Nonconvex Proximal Splitting with Computational Errors Suvrit Sra

Regularization, Optimization, Kernels, and Support Vector Machines, 2015, p.101-120

2015

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Single-Source Domain Adaptation with Target and Conditional Shift Kun Zhang, Bernhard Schölkopf, Krikamol Muandet, Zhikun Wang

Regularization, Optimization, Kernels, and Support Vector Machines, 2015, p.445-474

2015

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Single-Source Domain Adaptation with Target and Conditional Shift

Regularization, Optimization, Kernels, and Support Vector Machines, 2014

2014

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On the Convergence Rate of Stochastic Gradient Descent for Strongly Convex Functions

Regularization, Optimization, Kernels, and Support Vector Machines, 2015, p.177-194

2015

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Detecting Ineffective Features for Nonparametric Regression

Regularization, Optimization, Kernels, and Support Vector Machines, 2015, p.195-212

2015

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Quadratic Basis Pursuit

Regularization, Optimization, Kernels, and Support Vector Machines, 2015, p.213-234

2015

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Learning Sets and Subspaces

Regularization, Optimization, Kernels, and Support Vector Machines, 2015, p.355-376

2015

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Regularized Dictionary Learning

Regularization, Optimization, Kernels, and Support Vector Machines, 2015, p.45-70

2015

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Regularization, Optimization, Kernels, and Support Vector Machines

A kernel-based framework to tensorial data analysis

Tensor Versus Matrix Completion: A Comparison With Application to Spectral Data

Classification of Multichannel Signals With Cumulant-Based Kernels

A kernel-based framework to tensorial data analysis: Artificial Neural Networks: Selected papers from ICANN 2010

The Why and How of Nonnegative Matrix Factorization

Automatic Seizure Detection Incorporating Structural Information

Kernel-Based Learning from Infinite Dimensional 2-Way Tensors

Quadratically Constrained Quadratic Programming for Subspace Selection in Kernel Regression Estimation

Hybrid Conditional Gradient-Smoothing Algorithms with Applications to Sparse and Low Rank Regularization

High level high performance computing for multitask learning of time-varying models

Semi-supervised Learning of Sparse Linear Models in Mass Spectral Imaging

An Equivalence between the Lasso and Support Vector Machines

DynOpt: Incorporating dynamics into mean-variance portfolio optimization

Classification of Structured EEG Tensors Using Nuclear Norm Regularization: Improving P300 Classification

Learning Constrained Task Similarities in Graph-Regularized Multi-Task Learning

Multi-Layer Support Vector Machines

Nonconvex Proximal Splitting with Computational Errors Suvrit Sra

Single-Source Domain Adaptation with Target and Conditional Shift Kun Zhang, Bernhard Schölkopf, Krikamol Muandet, Zhikun Wang

Single-Source Domain Adaptation with Target and Conditional Shift

On the Convergence Rate of Stochastic Gradient Descent for Strongly Convex Functions

Detecting Ineffective Features for Nonparametric Regression

Quadratic Basis Pursuit

Learning Sets and Subspaces

Regularized Dictionary Learning

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