Publications related to Probability distribution

Distributionally Robust Mechanism Design

Daniel Kuhn, Cagil Kocyigit, Wolfram Wiesemann

We study a mechanism design problem where an indivisible good is auctioned to multiple bidders, for each of whom it has a private value that is unknown to the seller and the other bidders. The agents perceive the ensemble of all bidder values as a random v ...

2020

Strong convergence of multivariate maxima

Simone Padoan, Stefano Rizzelli

It is well known and readily seen that the maximum of n independent and uniformly on [0, 1] distributed random variables, suitably standardised, converges in total variation distance, as n increases, to the standard negative exponential distribution. We ex ...

CAMBRIDGE UNIV PRESS2020

Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions

Lenka Zdeborová

p>We study the dynamics of optimization and the generalization properties of one-hidden layer neural networks with quadratic activation function in the overparametrized regime where the layer width m is larger than the input dimension d. We conside ...

Curran Associates, Inc.2020

Data-Aware Privacy-Preserving Machine Learning

Aleksei Triastcyn

In this thesis, we focus on the problem of achieving practical privacy guarantees in machine learning (ML), where the classic differential privacy (DP) fails to maintain a good trade-off between user privacy and data utility. Differential privacy guarantee ...

EPFL2020

Characterization of myelodysplastic syndromes progressing to acute lymphoblastic leukemia

Filipe Amândio Brandão Sanches Vong Martins

Myelodysplastic syndromes (MDS) are a heterogeneous group of diseases, with a variable probability of transformation into acute leukemia, which is, in the vast majority of cases, of myeloid lineage. Nevertheless, rare cases of acute lymphoblastic leukemia ...

SPRINGER2020

A t-distribution based operator for enhancing out of distribution robustness of neural network classifiers

Philip Neil Garner

Neural Network (NN) classifiers can assign extreme probabilities to samples that have not appeared during training (out-of-distribution samples) resulting in erroneous and unreliable predictions. One of the causes for this unwanted behaviour lies in the us ...

IEEE2020

R2D2: A Region-Based Recursive Doppler Dealiasing Algorithm for Operational Weather Radar

Alexis Berne, Marco Gabella, Monika Feldmann, Daniel Wolfensberger

Region-based Recursive Doppler Dealiasing (R2D2) is a novel dealiasing algorithm to unfold Doppler velocity fields obtained by operational radar measurements. It specializes in resolving issues when the magnitude of the gate-to-gate velocity shear approach ...

2020

Thermal stability of size-selected copper nanoparticles: Effect of size, support and CO2 hydrogenation atmosphere

Andreas Züttel, Wen Luo, Mostapha Dakhchoune, Kun Zhao, Mo Li, Alexandre Borsay

Metal nanoparticles with a precisely controlled particle size distribution are ideal model catalysts for fundamental studies in catalysis. In this work, the thermal stability of size-selected Cu nanoparticles (Cu NPs) were deposited by magnetron sputtering ...

2020

Uncertainty and sensitivity analysis of PWR mini-core transients in the presence of nuclear data uncertainty using non-parametric tolerance limits

Andreas Pautz, Winfried Zwermann, Alexander Aures

The impact of nuclear data uncertainties is studied for the reactor power and the reactivity during control rod withdrawal transients with reactivity insertions of 0.5

and 0.97

, respectively, for a PWR mini-core model. Multi-group cross sections, the mul ...

PERGAMON-ELSEVIER SCIENCE LTD2020

Robust Generalization via f−Mutual Information

Michael Christoph Gastpar, Amedeo Roberto Esposito, Ibrahim Issa

Given two probability measures P and Q and an event E, we provide bounds on P(E) in terms of Q(E) and f-divergences. In particular, the bounds are instantiated when the measures considered are a joint distribution and the corresponding product of marginals ...

IEEE2020

Probability distribution

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Distributionally Robust Mechanism Design

Strong convergence of multivariate maxima

Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions

Data-Aware Privacy-Preserving Machine Learning

Characterization of myelodysplastic syndromes progressing to acute lymphoblastic leukemia

A t-distribution based operator for enhancing out of distribution robustness of neural network classifiers

R2D2: A Region-Based Recursive Doppler Dealiasing Algorithm for Operational Weather Radar

Thermal stability of size-selected copper nanoparticles: Effect of size, support and CO2 hydrogenation atmosphere

Uncertainty and sensitivity analysis of PWR mini-core transients in the presence of nuclear data uncertainty using non-parametric tolerance limits

Robust Generalization via f−Mutual Information

A t-distribution based operator for enhancing out of distribution robustness of neural network classifiers

Optimization and Generalization of Shallow Neural Networks with Quadratic Activation Functions

Data-Aware Privacy-Preserving Machine Learning

Distributionally Robust Mechanism Design

Characterization of myelodysplastic syndromes progressing to acute lymphoblastic leukemia

Uncertainty and sensitivity analysis of PWR mini-core transients in the presence of nuclear data uncertainty using non-parametric tolerance limits

Strong convergence of multivariate maxima

Thermal stability of size-selected copper nanoparticles: Effect of size, support and CO2 hydrogenation atmosphere

R2D2: A Region-Based Recursive Doppler Dealiasing Algorithm for Operational Weather Radar

Robust Generalization via f−Mutual Information