Publications related to When Is Amplification Necessary for Composition in Randomized Query Complexity?

Predicting involuntary hospitalization in psychiatry: A machine learning investigation

Background Coercion in psychiatry is a controversial issue. Identifying its predictors and their interaction using traditional statistical methods is difficult, given the large number of variables involved. The purpose of this study was to use machine-lear ...

CAMBRIDGE UNIV PRESS2021

A Spectral Algorithm for 3-valued Function Equivalence Classification

Mathias Soeken

Spectral techniques for Boolean and multiple-valued functions have been well studied and found to be useful in logic design and testing for conventional circuits. Spectral techniques also have potential application for reversible and quantum circuits. This ...

OLD CITY PUBLISHING INC2020

Cognitive workload monitoring in virtual reality based rescue missions with drones

David Atienza Alonso, Adriana Arza Valdes, Fabio Isidoro Tiberio Dell'Agnola, Niloofar Momeni

The use of drones in search and rescue (SAR) missions can be very cognitively demanding. Since high levels of cognitive workload can negatively affect human performance, there is a risk of compromising the mission and leading to failure with catastrophic o ...

2020

ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification

Mahsa Shoaran, Bingzhao Zhu

Classifiers that can be implemented on chip with minimal computational and memory resources are essential for edge computing in emerging applications such as medical and IoT devices. This paper introduces a machine learning model based on oblique decision ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

Multi-armed Bandits in Action

Farnood Salehi

Making decisions is part and parcel of being human. Among a set of actions, we want to choose the one that has the highest reward. But the uncertainty of the outcome prevents us from always making the right decision. Making decisions under uncertainty can ...

EPFL2020

The Cost of Scaling a Reliable Interconnection Topology

Rachid Guerraoui, Alexandre David Olivier Maurer

In distributed computing, many papers try to evaluate the message complexity of a distributed system as a function of the number of nodes n. But what about the cost of building the distributed system itself? Assuming that we want to reliably connect n node ...

2020

Robust Adaptive Decision Making: Bayesian Optimization and Beyond

Ilija Bogunovic

The central task in many interactive machine learning systems can be formalized as the sequential optimization of a black-box function. Bayesian optimization (BO) is a powerful model-based framework for \emph{adaptive} experimentation, where the primary go ...

EPFL2019

Incorporating Deep Bagging Ensemble Method as a Surrogate Model for Simulating Hyper-Concentrated Sediment-Laden Flows

David Andrew Barry, Seyed Mahmood Hamze Ziabari

Macroscale and mesoscale simulations of hyper-concentrated sediment-laden flows rely on robust couplings of the Reynolds-Averaged Navier-Stokes equations in conjunction with the shear-stress transport k-ω turbulence model. Also other closure laws for model ...

2019

New insights on Drosophila antimicrobial peptide function in host defense and beyond

Bruno Lemaitre, Mark Austin Hanson

Since the first animal antimicrobial peptides (AMPs) were discovered in insects, Drosophila melanogaster has emerged as a powerful model for their characterization. Drosophila AMPs have been used extensively to monitor the activity of the Toll and Imd NF-κ ...

2019

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Fabio Nobile, Giovanni Migliorati

We analyze the accuracy of the discrete least-squares approximation of a function

u

in multivariate polynomial spaces

P_\Lambda:=span\{y\mapsto y^\nu \,: \, \nu\in \Lambda\}

with

\Lambda\subset N_0^d

over the domain

\Gamma:=[-1,1]^d

, based on the s ...

2017

When Is Amplification Necessary for Composition in Randomized Query Complexity?

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Predicting involuntary hospitalization in psychiatry: A machine learning investigation

A Spectral Algorithm for 3-valued Function Equivalence Classification

Cognitive workload monitoring in virtual reality based rescue missions with drones

ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification

Multi-armed Bandits in Action

The Cost of Scaling a Reliable Interconnection Topology

Robust Adaptive Decision Making: Bayesian Optimization and Beyond

Incorporating Deep Bagging Ensemble Method as a Surrogate Model for Simulating Hyper-Concentrated Sediment-Laden Flows

New insights on Drosophila antimicrobial peptide function in host defense and beyond

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Predicting involuntary hospitalization in psychiatry: A machine learning investigation

ResOT: Resource-Efficient Oblique Trees for Neural Signal Classification

Robust Adaptive Decision Making: Bayesian Optimization and Beyond

The Cost of Scaling a Reliable Interconnection Topology

Incorporating Deep Bagging Ensemble Method as a Surrogate Model for Simulating Hyper-Concentrated Sediment-Laden Flows

A Spectral Algorithm for 3-valued Function Equivalence Classification

New insights on Drosophila antimicrobial peptide function in host defense and beyond

Discrete least-squares approximations over optimized downward closed polynomial spaces in arbitrary dimension

Cognitive workload monitoring in virtual reality based rescue missions with drones

Multi-armed Bandits in Action