Publications by Volkan Cevher | EPFL Graph Search

Composite convex minimization involving self-concordant-like cost functions

Volkan Cevher, Quoc Tran Dinh, Yen-Huan Li

Abstract. The self-concordant-like property of a smooth convex func- tion is a new analytical structure that generalizes the self-concordant notion. While a wide variety of important applications feature the self- concordant-like property, this concept has ...

2015

Composite Self-Concordant Minimization

Volkan Cevher, Quoc Tran Dinh, Anastasios Kyrillidis

We propose a variable metric framework for minimizing the sum of a self-concordant function and a possibly non-smooth convex function endowed with a computable proximal operator. We theoretically establish the convergence of our framework without relying o ...

Massachusetts Institute of Technology Press2015

What’s the Frequency, Kenneth?: Sublinear Fourier Sampling Off the Grid

Volkan Cevher, Yen-Huan Li

We design a sublinear Fourier sampling algorithm for a case of sparse off-grid frequency recovery. These are signals with the form f(t)=∑kj=1ajeiωjt+ν^ , t∈Z ; i.e., exponential polynomials with a noise term. The frequencies {ω j } satisfy ω j ∈ [η,2π − η ...

Springer Verlag2015

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Volkan Cevher, Jonathan Mark Scarlett, Yen-Huan Li

We consider the model selection consistency or sparsistency of a broad set of

\ell_1

-regularized

M

-estimators for linear and non-linear statistical models in a unified fashion. For this purpose, we propose the local structured smoothness condition (LSS ...

2015

Stochastic Spectral Descent for Restricted Boltzmann Machines.

Volkan Cevher

Restricted Boltzmann Machines (RBMs) are widely used as building blocks for deep learning models. Learning typically proceeds by using stochastic gradient descent, and the gradients are estimated with sampling methods. However, the gradient estimation is a ...

2015

WASP: Scalable Bayes via barycenters of subset posteriors

Volkan Cevher, Quoc Tran Dinh

The promise of Bayesian methods for big data sets has not fully been realized due to the lack of scalable computational algorithms. For massive data, it is necessary to store and process subsets on different machines in a distributed manner. We propose a s ...

2015

Active Learning of Self-concordant like Multi-index Functions

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic

We study the problem of actively learning a multi-index function of the form f (x) = g_0 (A_0 x) from its point evaluations, where A_0 ∈ R_{k×d} with k ≪ d. We build on the assumptions and techniques of an existing approach based on low-rank matrix recover ...

2015

A Universal Primal-Dual Convex Optimization Framework

Volkan Cevher, Quoc Tran Dinh, Alp Yurtsever

We propose a new primal-dual algorithmic framework for a prototypical con- strained convex optimization template. The algorithmic instances of our frame- work are universal since they can automatically adapt to the unknown Ho ̈lder con- tinuity properties ...

2015

Consistency of $\ell_1$-Regularized Maximum-Likelihood for Compressive Poisson Regression

Volkan Cevher, Yen-Huan Li

We consider Poisson regression with the canonical link function. This regression model is widely used in regression analysis involving count data; one important application in electrical engineering is transmission tomography. In this paper, we establish t ...

2015

A 5.9mW/Gb/s 7Gb/s/pin 8-Lane Single-Ended RX with Crosstalk Cancellation Scheme using a XCTLE and 56-tap XDFE in 32nm SOI CMOS

Volkan Cevher, Cosimo Aprile, Yusuf Leblebici, Alessandro Cevrero, Lukas Kull, Ilter Ozkaya, Thomas Toifl

This work reports an 8-lane single-ended RX featuring compact and low power far-end crosstalk (FEXT) cancellation circuits. The RX data-path consists of a cross continuous-time linear equalizer (XCTLE) to remove FEXT by nearest aggressors within the channe ...

2015

Volkan Cevher

Graph Chatbot

Chat with Graph Search

Composite convex minimization involving self-concordant-like cost functions

Composite Self-Concordant Minimization

What’s the Frequency, Kenneth?: Sublinear Fourier Sampling Off the Grid

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Stochastic Spectral Descent for Restricted Boltzmann Machines.

WASP: Scalable Bayes via barycenters of subset posteriors

Active Learning of Self-concordant like Multi-index Functions

A Universal Primal-Dual Convex Optimization Framework

Consistency of $\ell_1$-Regularized Maximum-Likelihood for Compressive Poisson Regression

A 5.9mW/Gb/s 7Gb/s/pin 8-Lane Single-Ended RX with Crosstalk Cancellation Scheme using a XCTLE and 56-tap XDFE in 32nm SOI CMOS

Composite Self-Concordant Minimization

Stochastic Spectral Descent for Restricted Boltzmann Machines.

Consistency of $\ell_1$-Regularized Maximum-Likelihood for Compressive Poisson Regression

What’s the Frequency, Kenneth?: Sublinear Fourier Sampling Off the Grid

Composite convex minimization involving self-concordant-like cost functions

WASP: Scalable Bayes via barycenters of subset posteriors

Active Learning of Self-concordant like Multi-index Functions

A Universal Primal-Dual Convex Optimization Framework

Sparsistency of $\ell_1$-Regularized $M$-Estimators

A 5.9mW/Gb/s 7Gb/s/pin 8-Lane Single-Ended RX with Crosstalk Cancellation Scheme using a XCTLE and 56-tap XDFE in 32nm SOI CMOS