Publications related to Distinguishing Distributions Using Chernoff Information

Learning Robust and Adaptive Representations: from Interactions, for Interactions

Interactions are ubiquitous in our world, spanning from social interactions between human individuals to physical interactions between robots and objects to mechanistic interactions among different components of an intelligent system. Despite their prevale ...

EPFL2023

RUM: Reconfigurable Umbrella Mesh

Mark Pauly, Florin Isvoranu, Uday Kusupati, Seiichi Eduardo Suzuki Erazo

We propose Reconfigurable Umbrella Meshes (RUMs), a new class of preassembled deployable structures. A RUM has a compact rest state that can be easily altered to deploy into different bending-active 3D target shapes. RUMs consist of elastic beams and rigid ...

De Gruyter2023

Assessment of the Lightning Performance of overhead distribution lines based on Lightning Location Systems data

This article presents the Lightning Performance (LP) assessment of a realistic portion of the Italian distribution network with the use of probability distributions for lightning parameters inferred from local data recorded by a Lightning Location System ( ...

2022

Serial Lightweight Implementation Techniques for Block Ciphers

Muhammed Fatih Balli

Most of the cryptographic protocols that we use frequently on the internet are designed in a fashion that they are not necessarily suitable to run in constrained environments. Applications that run on limited-battery, with low computational power, or area ...

EPFL2021

A Current Propagation Type Return Stroke Model Consistent with the Leader Charge Distribution

Marcos Rubinstein, Farhad Rachidi-Haeri

We describe a current propagation type return stroke model which is consistent with the estimated distribution of the charge on the leader channel. The model takes into account the dispersion of the return stroke current along the return stroke channel. Th ...

2021

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

Serge Vaudenay

The maximal achievable advantage of a (computationally unbounded) distinguisher to determine whether a source

Z

is distributed according to distribution

P_0

or

P_1

, when given access to one sample of

Z

, is characterized by the statistical distance ...

Springer, Cham2020

From Data to Decisions: Distributionally Robust Optimization is Optimal

Daniel Kuhn, Peyman Mohajerin Esfahani

We study stochastic programs where the decision-maker cannot observe the distribution of the exogenous uncertainties but has access to a finite set of independent samples from this distribution. In this setting, the goal is to find a procedure that transfo ...

2020

Variational Inference with Mixture Model Approximation for Applications in Robotics

Sylvain Calinon, Emmanuel Pignat, Teguh Santoso Lembono

We propose to formulate the problem of repre-senting a distribution of robot configurations (e.g. joint angles)as that of approximating a product of experts. Our approach uses variational inference, a popular method in Bayesian computation, which has sever ...

2020

On Design of Robust Lightweight Stream Cipher with Short Internal State

Subhadeep Banik

The stream cipher Sprout with a short internal state was proposed in FSE 2015. Although the construction guaranteed resistance to generic Time Memory Data Tradeoff attacks, there were some weaknesses in the design and the cipher was completely broken. In t ...

2018

An Analysis of the Distribution of Inter-Flash Time Intervals in the Area of the Santis Tower

Marcos Rubinstein, Antonio Sunjerga

In this paper we analyzed the time intervals between flashes in the Santis area for three highly active storms and also for a period of 21 months. The overall distributions of inter-flash time interval are found to be very similar and reasonably represente ...

IEEE2018

Distinguishing Distributions Using Chernoff Information

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Learning Robust and Adaptive Representations: from Interactions, for Interactions

RUM: Reconfigurable Umbrella Mesh

Assessment of the Lightning Performance of overhead distribution lines based on Lightning Location Systems data

Serial Lightweight Implementation Techniques for Block Ciphers

A Current Propagation Type Return Stroke Model Consistent with the Leader Charge Distribution

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

From Data to Decisions: Distributionally Robust Optimization is Optimal

Variational Inference with Mixture Model Approximation for Applications in Robotics

On Design of Robust Lightweight Stream Cipher with Short Internal State

An Analysis of the Distribution of Inter-Flash Time Intervals in the Area of the Santis Tower

Assessment of the Lightning Performance of overhead distribution lines based on Lightning Location Systems data

Serial Lightweight Implementation Techniques for Block Ciphers

A Current Propagation Type Return Stroke Model Consistent with the Leader Charge Distribution

Sublinear Bounds on the Distinguishing Advantage for Multiple Samples

Learning Robust and Adaptive Representations: from Interactions, for Interactions

RUM: Reconfigurable Umbrella Mesh

Variational Inference with Mixture Model Approximation for Applications in Robotics

On Design of Robust Lightweight Stream Cipher with Short Internal State

From Data to Decisions: Distributionally Robust Optimization is Optimal

An Analysis of the Distribution of Inter-Flash Time Intervals in the Area of the Santis Tower