Publications related to Linear predictor function

On the symmetries in the dynamics of wide two-layer neural networks

We consider the idealized setting of gradient flow on the population risk for infinitely wide two-layer ReLU neural networks (without bias), and study the effect of symmetries on the learned parameters and predictors. We first describe a general class of s ...

AMER INST MATHEMATICAL SCIENCES-AIMS2023

Application of UV absorbance and electron-donating capacity as surrogates for micropollutant abatement during full-scale ozonation of secondary-treated wastewater

Urs von Gunten

Ozonation of secondary-treated wastewater for the abatement of micropollutants requires a reliable control of ozone doses. Changes in the UV absorbance of dissolved organic matter (DOM) during ozonation allow to estimate micropollutant abatement on-line an ...

PERGAMON-ELSEVIER SCIENCE LTD2022

Last iterate convergence of SGD for Least-Squares in the Interpolation regime

Nicolas Henri Bernard Flammarion, Aditya Vardhan Varre, Loucas Pillaud-Vivien

Motivated by the recent successes of neural networks that have the ability to fit the data perfectly \emph{and} generalize well, we study the noiseless model in the fundamental least-squares setup. We assume that an optimum predictor fits perfectly inputs ...

2021

Empirical observations of multi-modal network-level models: Insights from the pNEUMA experiment

Nikolaos Geroliminis, Emmanouil Barmpounakis

Multi-modal interactions at the network-level remain unexplored due to the lack of highresolution data for all transportation modes involved. The current work investigates the effect of multi-modal interactions at space-mean network speed for each mode usi ...

PERGAMON-ELSEVIER SCIENCE LTD2021

Travel Time Prediction for Congested Freeways With a Dynamic Linear Model

Nikolaos Geroliminis, Semin Kwak

Accurate prediction of travel time is an essential feature to support Intelligent Transportation Systems (ITS). The non-linearity of traffic states, however, makes this prediction a challenging task. Here we propose to use dynamic linear models (DLMs) to a ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Integrating the Finite Element Method with a Data-Driven Approach for Dam Displacement Prediction

Zhenzhu Meng, Yating Hu, Chenfei Shao

Both numerical simulations and data-driven methods have been applied in dam's displacement modeling. For monitored displacement data-driven methods, the physical mechanism and structural correlations were rarely discussed. In order to take the spatial and ...

2020

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

Reach-to-grasp motions: Towards a dynamic classification approach for upper-limp prosthesis

Aude Billard, Iason Batzianoulis

During reach-to-grasp motions,the Electromyographic (EMG) activity of the arm varies depending on motion stage. The variability of the EMG signals results in low classification accuracy during the reaching phase, delaying the activation of the prosthesis. ...

IEEE2019

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Linear predictor function

On the symmetries in the dynamics of wide two-layer neural networks

Kernel Density Estimation of Electromyographic Signals and Ensemble Learning for Highly Accurate Classification of a Large Set of Hand/Wrist Motions

Application of UV absorbance and electron-donating capacity as surrogates for micropollutant abatement during full-scale ozonation of secondary-treated wastewater

Last iterate convergence of SGD for Least-Squares in the Interpolation regime

Empirical observations of multi-modal network-level models: Insights from the pNEUMA experiment

Travel Time Prediction for Congested Freeways With a Dynamic Linear Model

Integrating the Finite Element Method with a Data-Driven Approach for Dam Displacement Prediction

Cognitive workload monitoring in virtual reality based rescue missions with drones

Reach-to-grasp motions: Towards a dynamic classification approach for upper-limp prosthesis

Improving the arm-hand coordination in neuroprosthetics control with prior information from muscle activity

Graph Chatbot

Chat with Graph Search

On the symmetries in the dynamics of wide two-layer neural networks

Kernel Density Estimation of Electromyographic Signals and Ensemble Learning for Highly Accurate Classification of a Large Set of Hand/Wrist Motions

Application of UV absorbance and electron-donating capacity as surrogates for micropollutant abatement during full-scale ozonation of secondary-treated wastewater

Last iterate convergence of SGD for Least-Squares in the Interpolation regime

Travel Time Prediction for Congested Freeways With a Dynamic Linear Model

Integrating the Finite Element Method with a Data-Driven Approach for Dam Displacement Prediction

Cognitive workload monitoring in virtual reality based rescue missions with drones

Improving the arm-hand coordination in neuroprosthetics control with prior information from muscle activity

Reach-to-grasp motions: Towards a dynamic classification approach for upper-limp prosthesis

Empirical observations of multi-modal network-level models: Insights from the pNEUMA experiment