Publication

Wasserstein Distributionally Robust Learning

Publications associées (368)

Graph Chatbot

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Connectez-vous pour utiliser Chat avec Graph Search

Gaussian distribution for the divisor function and Hecke eigenvalues in arithmetic progressions

Philippe Michel

We show that, in a restricted range, the divisor function of integers in residue classes modulo a prime follows a Gaussian distribution, and a similar result for Hecke eigenvalues of classical holomorphic cusp forms. Furthermore, we obtain the joint distri ...

European Mathematical Soc2014

Analysis and Design of Large-scale Online Classes

Martin Vetterli, Paolo Prandoni, Tao-Chun Lee

Massive Open Online Courses (MOOCs) have become an emergent paradigm of large-scale knowledge distribution, have generated wide interest in the higher education community and are anticipated by many to bring impact to the future of higher education. In thi ...

2014

Large deviations analysis of adaptive distributed detection

Ali H. Sayed

In distributed inference, local cooperation among network nodes can be exploited to enhance the performance of each individual agent, but a challenging requirement for networks operating in dynamic real-world environments is that of adaptation. The interpl ...

IEEE2014

Damage prediction for regular reinforced concrete buildings using the decision tree algorithm

Pierino Lestuzzi, Amin Karbassi, Shaliz Rezaee

To overcome the problem of outlier data in the regression analysis for numerical-based damage spectra, the C4.5 decision tree learning algorithm is used to predict damage in reinforced concrete buildings in future earthquake scenarios. Reinforced concrete ...

Elsevier2014

On the probability distribution of distributed optimization strategies

Ali H. Sayed

We study the steady-state probability distribution of diffusion and consensus strategies that employ constant step-sizes to enable continuous adaptation and learning. We show that, in the small step-size regime, the estimation error at each agent approache ...

IEEE2013

A Probabilistic Framework for Multiple Speaker Localization

This paper presents a novel probabilistic framework for localizing multiple speakers with a microphone array. In this framework, the generalized cross correlation function (GCC) of each microphone pair is interpreted as a probability distribution of the ti ...

2013

Bayesian Estimation for Continuous-Time Sparse Stochastic Processes

Michaël Unser, Arash Amini, Emrah Bostan, Ulugbek Kamilov

We consider continuous-time sparse stochastic processes from which we have only a finite number of noisy/noiseless samples. Our goal is to estimate the noiseless samples (denoising) and the signal in-between (interpolation problem). By relying on tools fro ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Message-Passing Algorithms: Reparameterizations and Splittings

Nicholas Ruozzi

The max-product algorithm, a local message-passing scheme that attempts to compute the most probable assignment (MAP) of a given probability distribution, has been successfully employed as a method of approximate inference for applications arising in codin ...

Ieee-Inst Electrical Electronics Engineers Inc2013

MMSE Estimation of Sparse Levy Processes

Michaël Unser, Arash Amini, Ulugbek Kamilov, Pedram Pad

We investigate a stochastic signal-processing framework for signals with sparse derivatives, where the samples of a Levy process are corrupted by noise. The proposed signal model covers the well-known Brownian motion and piecewise-constant Poisson process; ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Optimal Classification In Sparse Gaussian Graphic Model

Zhigang Yao, Yingying Fan

Consider a two-class classification problem where the number of features is much larger than the sample size. The features are masked by Gaussian noise with mean zero and covariance matrix Sigma, where the precision matrix Omega = Sigma(-1) is unknown but ...

Institute of Mathematical Statistics2013