Publications related to Asymptotically Optimal Matching of Multiple Sequences to Source Distributions and Training Sequences

On Approximations of Data-Driven Chance Constrained Programs over Wasserstein Balls

Daniel Kuhn, Zhi Chen, Wolfram Wiesemann

Distributionally robust chance constrained programs minimize a deterministic cost function subject to the satisfaction of one or more safety conditions with high probability, given that the probability distribution of the uncertain problem parameters affec ...

2022

fGOT: Graph Distances Based on Filters and Optimal Transport

Pascal Frossard, Mireille El Gheche, Hermina Petric Maretic, Giovanni Chierchia

Graph comparison deals with identifying similarities and dissimilarities between graphs. A major obstacle is the unknown alignment of graphs, as well as the lack of accurate and inexpensive comparison metrics. In this work we introduce the filter graph dis ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2022

Tighter thermodynamic bound on the speed limit in systems with unidirectional transitions

Daniel Maria Busiello, Deepak Gupta

We consider a general discrete state-space system with both unidirectional and bidirectional links. In contrast to bidirectional links, there is no reverse transition along the unidirectional links Herein, we first compute the statistical length and the th ...

2020

The probability of intransitivity in dice and close elections

Jan Hazla

We study the phenomenon of intransitivity in models of dice and voting. First, we follow a recent thread of research for n-sided dice with pairwise ordering induced by the probability, relative to 1/2, that a throw from one die is higher than the other. We ...

2020

Statistical Aspects of Wasserstein Distances

Victor Panaretos, Yoav Zemel

Wasserstein distances are metrics on probability distributions inspired by the problem of optimal mass transportation. Roughly speaking, they measure the minimal effort required to reconfigure the probability mass of one distribution in order to recover th ...

ANNUAL REVIEWS2019

Extracting the Critical Rooting Length in Plant Uprooting by Flow From Pullout Experiments

Paolo Perona, Giulio Calvani

The growth and establishment of riparian vegetation on river bedforms is of hydrological as well as ecological importance as it helps in enhancing spatial heterogeneity and thus the biodiversity of river corridors. Yet, during floods, flow drag and scourin ...

AGU2019

Scalable Byzantine Reliable Broadcast

Rachid Guerraoui, Dragos-Adrian Seredinschi, Matej Pavlovic, Matteo Monti

Byzantine reliable broadcast is a powerful primitive that allows a set of processes to agree on a message from a designated sender, even if some processes (including the sender) are Byzantine. Existing broadcast protocols for this setting scale poorly, as ...

Schloss Dagstuhl--Leibniz-Zentrum fer Informatik2019

Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation

Daniel Kuhn, Viet Anh Nguyen, Soroosh Shafieezadeh Abadeh, Wolfram Wiesemann

The likelihood function is a fundamental component in Bayesian statistics. However, evaluating the likelihood of an observation is computationally intractable in many applications. In this paper, we propose a non-parametric approximation of the likelihood ...

2019

Rationally almost periodic sequences, polynomial multiple recurrence and symbolic dynamics

Florian Karl Richter

A set

R\subset \mathbb{N}

is called rational if it is well approximable by finite unions of arithmetic progressions, meaning that for every

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there exists a set

B=\bigcup _{i=1}^{r}a_{i}\mathbb{N}+b_{i}

, where $a_{1},\ldots ,a_ ...

2019

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

Fei Pu

In this thesis, we study systems of linear and/or non-linear stochastic heat equations and fractional heat equations in spatial dimension

1

driven by space-time white noise. The main topic is the study of hitting probabilities for the solutions to these ...

EPFL2018

Asymptotically Optimal Matching of Multiple Sequences to Source Distributions and Training Sequences

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On Approximations of Data-Driven Chance Constrained Programs over Wasserstein Balls

fGOT: Graph Distances Based on Filters and Optimal Transport

Tighter thermodynamic bound on the speed limit in systems with unidirectional transitions

The probability of intransitivity in dice and close elections

Statistical Aspects of Wasserstein Distances

Extracting the Critical Rooting Length in Plant Uprooting by Flow From Pullout Experiments

Scalable Byzantine Reliable Broadcast

Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation

Rationally almost periodic sequences, polynomial multiple recurrence and symbolic dynamics

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

On Approximations of Data-Driven Chance Constrained Programs over Wasserstein Balls

Statistical Aspects of Wasserstein Distances

Extracting the Critical Rooting Length in Plant Uprooting by Flow From Pullout Experiments

Scalable Byzantine Reliable Broadcast

Tighter thermodynamic bound on the speed limit in systems with unidirectional transitions

The probability of intransitivity in dice and close elections

The stochastic heat equation: hitting probabilities and the probability density function of the supremum via Malliavin calculus

Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation

Rationally almost periodic sequences, polynomial multiple recurrence and symbolic dynamics

fGOT: Graph Distances Based on Filters and Optimal Transport