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Related publications (28)

The Importance of Modeling Data Missingness in Algorithmic Fairness: A Causal Perspective

Naman Goel, Amit Sharma

Training datasets for machine learning often have some form of missingness. For example, to learn a model for deciding whom to give a loan, the available training data includes individuals who were given a loan in the past, but not those who were not. This ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2021

Locally Differentially-Private Randomized Response for Discrete Distribution Learning

Michael Christoph Gastpar, Adriano Pastore

We consider a setup in which confidential i.i.d. samples X1, . . . , Xn from an unknown finite-support distribution p are passed through n copies of a discrete privatization chan- nel (a.k.a. mechanism) producing outputs Y1, . . . , Yn. The channel law gua ...

2021

Learning from demonstration using products of experts: Applications to manipulation and task prioritization

Sylvain Calinon, Emmanuel Pignat

Probability distributions are key components of many learning from demonstration (LfD) approaches, with the spaces chosen to represent tasks playing a central role. Although the robot configuration is defined by its joint angles, end-effector poses are oft ...

2021

Bayesian Methods for the Identification of Distribution Networks

Giancarlo Ferrari Trecate, Jean-Sébastien Hubert Brouillon, Pulkit Nahata

The increasing integration of intermittent renewable generation, especially at the distribution level, necessitates advanced planning and optimisation methodologies contingent on the knowledge of the admittance matrix, capturing the topology and line param ...

IEEE2021

On the effect of a penetrating recirculation region on the bifurcations of the flow past a permeable sphere

François Gallaire, Pier Giuseppe Ledda, Giuseppe Antonio Zampogna, Matteo Ciuti

We study the flow past a permeable sphere modeled using homogenization theory. The flow through the porous medium is described by the Darcy law, in which the permeability quantifies the resistance for the fluid to pass through the microstructure. A slip co ...

AIP Publishing2021

Multivariate extremes over a random number of observations

Simone Padoan, Stefano Rizzelli

The classical multivariate extreme-value theory concerns the modeling of extremes in a multivariate random sample, suggesting the use of max-stable distributions. In this work, the classical theory is extended to the case where aggregated data, such as max ...

WILEY2021

Comparing spatio-temporal networks of intermittent avalanche events: Experiment, model, and empirical data

Anjali Bagunu Tarun

Relaxational processes in many complex systems often occur in the form of avalanches resulting from internal cascades from across the system scale. Here, we probe the space, time, and magnitude signatures of avalanching behavior using a network of temporal ...

2020

Study of B -> ppi pi

Olivier Schneider, Mingkui Wang, Chao Wang, Tagir Aushev, Sun Hee Kim, Donghyun Kim, Xiao Wang, Lei Li

Using a data sample of 772 x 10(6) B (B) over bar pairs collected on the Upsilon(4S) resonance with the Belle detector at the KEKB asymmetric energy e(+)e(-) collider, we report the observation of B-0 -> p (p) over bar pi(+)pi(-) and the first observation ...

American Physical Society2020

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