Publications by Volkan Cevher | EPFL Graph Search

Fixed Points of Generalized Approximate Message Passing with Arbitrary Matrices

The estimation of a random vector with independent components passed through a linear transform followed by a componentwise (possibly nonlinear) output map arises in a range of applications. Approximate message passing (AMP) methods, based on Gaussian appr ...

2016

Adaptive-Rate Sparse Signal Reconstruction With Application in Compressive Foreground Subtraction

Volkan Cevher

We propose and analyze an online algorithm for reconstructing a sequence of signals from a limited number of linear measurements. The signals are assumed sparse, with unknown support, and evolve over time according to a generic nonlinear dynamical model. O ...

Institute of Electrical and Electronics Engineers2016

Stochastic Spectral Descent for Discrete Graphical Models

Volkan Cevher, Ya-Ping Hsieh, Edo Collins

Interest in deep probabilistic graphical models has increased in recent years, due to their state-of-the-art perfor- mance on many machine learning applications. Such models are typically trained with the stochastic gradient method, which can take a signif ...

Ieee-Inst Electrical Electronics Engineers Inc2016

Adaptive-Rate Reconstruction of Time-Varying Signals with Application in Compressive Foreground Extraction

Volkan Cevher

We propose and analyze an online algorithm for reconstructing a sequence of signals from a limited number of linear measurements. The signals are assumed sparse, with unknown support, and evolve over time according to a generic nonlinear dynamical model. O ...

Institute of Electrical and Electronics Engineers2016

Time-Varying Gaussian Process Bandit Optimization

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic

We consider the sequential Bayesian optimization problem with bandit feedback, adopting a formulation that allows for the reward function to vary with time. We model the reward function using a Gaussian process whose evolution obeys a simple Markov model. ...

2016

Estimation Error of the Constrained Lasso

Volkan Cevher, Yen-Huan Li, Ya-Ping Hsieh, Nissim Zerbib

This paper presents a non-asymptotic upper bound for the estimation error of the constrained lasso, under the high-dimensional (

n \ll p

) setting. In contrast to existing results, the error bound in this paper is sharp, is valid when the parameter to be e ...

2016

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation

Volkan Cevher, Andreas Krause, Jonathan Mark Scarlett, Ilija Bogunovic

We present a new algorithm, truncated variance reduction (TruVaR), that treats Bayesian optimization (BO) and level-set estimation (LSE) with Gaussian processes in a unified fashion. The algorithm greedily shrinks a sum of truncated variances within a set ...

2016

Randomized Single-View Algorithms for Low-Rank Matrix Approximation

Volkan Cevher, Alp Yurtsever

This paper develops a suite of algorithms for constructing low-rank approximations of an input matrix from a random linear image of the matrix, called a sketch. These methods can preserve structural properties of the input matrix, such as positive-semideni ...

Under review2016

Phase Transitions in Group Testing

Volkan Cevher, Jonathan Mark Scarlett

The group testing problem consists of determining a sparse subset of a set of items that are ``defective'' based on a set of possibly noisy tests, and arises in areas such as medical testing, fault detection, communication protocols, pattern matching, and ...

2016

Computational Methods for Underdetermined Convolutive Speech Localization and Separation via Model-based Sparse Component Analysis

Hervé Bourlard, Volkan Cevher, Afsaneh Asaei, Mohammadjavad Taghizadeh

In this paper, the problem of speech source localization and separation from recordings of convolutive underdetermined mixtures is studied. The problem is cast as recovering the spatio-spectral speech information embedded in a microphone array compressed m ...

Elsevier Science Bv2016

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Fixed Points of Generalized Approximate Message Passing with Arbitrary Matrices

Adaptive-Rate Sparse Signal Reconstruction With Application in Compressive Foreground Subtraction

Stochastic Spectral Descent for Discrete Graphical Models

Adaptive-Rate Reconstruction of Time-Varying Signals with Application in Compressive Foreground Extraction

Time-Varying Gaussian Process Bandit Optimization

Estimation Error of the Constrained Lasso

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation

Randomized Single-View Algorithms for Low-Rank Matrix Approximation

Phase Transitions in Group Testing

Computational Methods for Underdetermined Convolutive Speech Localization and Separation via Model-based Sparse Component Analysis

Fixed Points of Generalized Approximate Message Passing with Arbitrary Matrices

Randomized Single-View Algorithms for Low-Rank Matrix Approximation

Computational Methods for Underdetermined Convolutive Speech Localization and Separation via Model-based Sparse Component Analysis

Adaptive-Rate Reconstruction of Time-Varying Signals with Application in Compressive Foreground Extraction

Truncated Variance Reduction: A Unified Approach to Bayesian Optimization and Level-Set Estimation

Time-Varying Gaussian Process Bandit Optimization

Estimation Error of the Constrained Lasso

Stochastic Spectral Descent for Discrete Graphical Models

Phase Transitions in Group Testing

Adaptive-Rate Sparse Signal Reconstruction With Application in Compressive Foreground Subtraction