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Adversarial Analytics

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Averaging Stochastic Gradient Descent on Riemannian Manifolds

Nicolas Henri Bernard Flammarion

We propose an estimator for the mean of a random vector in Rd that can be computed in time O(n3.5 + n2d) for n i.i.d. samples and that has error bounds matching the sub-Gaussian case. The only assumptions we make about the data distribution are that it has ...

2018

Local estimation of the global horizontal irradiance using an all-sky camera

Mario Paolone, Fabrizio Sossan, Enrica Scolari

Localised and high-frequency measurements of the global horizontal irradiance (GHI) are a key information to assess the level of power production of distributed photovoltaic generation. The paper presents a supervised machine learning-based procedure to es ...

PERGAMON-ELSEVIER SCIENCE LTD2018

Wasserstein Distributionally Robust Kalman Filtering

Daniel Kuhn, Viet Anh Nguyen, Soroosh Shafieezadeh Abadeh, Peyman Mohajerin Esfahani

We study a distributionally robust mean square error estimation problem over a nonconvex Wasserstein ambiguity set containing only normal distributions. We show that the optimal estimator and the least favorable distribution form a Nash equilibrium. Despit ...

2018

MATHICSE Technical Report : Multilevel Monte Carlo approximation of functions

Fabio Nobile, Sebastian Krumscheid

Many applications across sciences and technologies require a careful quantification of non-deterministic effects to a system output, for example when evaluating the system's reliability or when gearing it towards more robust operation conditions. At the he ...

MATHICSE2017

Since the 2008 Global Financial Crisis, the financial market has become more unpredictable than ever before, and it seems set to remain so in the forseeable future. This means an investor faces unprecedented risks, hence the increasing need for robust port ...

EPFL2017

Blowing in the Wind

Marta Martinez-Camara

Every day tons of pollutants are emitted into the atmosphere all around the world. These pollutants are altering the equilibrium of our planet, causing profound changes in its climate, increasing global temperatures, and raising the sea level. The need to ...

EPFL2017

Robust Bounds In Multivariate Extremes

Sebastian Engelke

Extreme value theory provides an asymptotically justified framework for estimation of exceedance probabilities in regions where few or no observations are available. For multivariate tail estimation, the strength of extremal dependence is crucial and it is ...

Institute of Mathematical Statistics2017

Diffusion adaptive networks tasked with solving estimation problems have attracted attention in recent years due to their reliability, scalability, resource efficiency, and resilience to node and link failure. Diffusion adaptation strategies that are based ...

2017

Model Uncertainty And Scenario Aggregation

Damir Filipovic, Mathieu Jacques David Cambou

This paper provides a coherent method for scenario aggregation addressing model uncertainty. It is based on divergence minimization from a reference probability measure subject to scenario constraints. An example from regulatory practice motivates the defi ...

Wiley-Blackwell2017

Long-Term Stable Control of Motor-Imagery BCI by a Locked-in User Through Adaptive Assistance

José del Rocio Millán Ruiz, Ricardo Andres Chavarriaga Lozano, Sareh Saeedi

Performance variation is one of the main challenges that BCIs are confronted with, when being used over extended periods of time. Shared control techniques could partially cope with such a problem. In this paper, we propose a taxonomy of shared control app ...

Institute of Electrical and Electronics Engineers2017