Publications related to Linear model

Training Techniques for Presence-Only Habitat Suitability Mapping with Deep Learning

Devis Tuia, Benjamin Alexander Kellenberger

The goal of habitat suitability mapping is to predict the lo-cations in which a given species could be present. This is typically accomplished by statistical models which use envi-ronmental variables to predict species observation data. The relationship be ...

IEEE2022

Positive and Negative Critiquing for VAE-based Recommenders

Boi Faltings, Diego Matteo Antognini

Providing explanations for recommended items allows users to refine the recommendations by critiquing parts of the explanations. As a result of revisiting critiquing from the perspective of multimodal generative models, recent work has proposed M&Ms-VAE, w ...

2022

Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation

Maryam Kamgarpour, Andreas Krause

We consider model-based multi-agent reinforcement learning, where the environment transition model is unknown and can only be learned via expensive interactions with the environment. We propose H-MARL (Hallucinated Multi-Agent Reinforcement Learning), a no ...

JMLR-JOURNAL MACHINE LEARNING RESEARCH2022

Running Speed Estimation Using Shoe-Worn Inertial Sensors: Direct Integration, Linear, and Personalized Model

Kamiar Aminian, Mathieu Pascal Falbriard, Abolfazl Soltani

The overground speed is a key component of running analysis. Today, most speed estimation wearable systems are based on GNSS technology. However, these devices can suffer from sparse communication with the satellites and have a high-power consumption. In t ...

2021

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models

Giovanni De Micheli, Sandro Carrara, Mandresy Ivan Ny Hanitra, Francesca Criscuolo

One paramount challenge in multi-ion-sensing arises from ion interference that degrades the accuracy of sensor calibration. Machine learning models are here proposed to optimize such multivariate calibration. However, the acquisition of big experimental da ...

2021

Swimming Phase-Based Performance Evaluation Using a Single IMU in Main Swimming Techniques

Kamiar Aminian, Farzin Dadashi, Fabien Massé, Mahdi Hamidi Rad, Vincent Gremeaux

Comprehensive monitoring of performance is essential for swimmers and swimming coaches to optimize the training. Regardless of the swimming technique, the swimmer passes various swimming phases from wall to wall, including a dive into the water or wall pus ...

FRONTIERS MEDIA SA2021

Compound Admittance Matrix Estimation of Three-phase Untransposed Power Distribution Grids using Synchrophasor Measurements

Jean-Yves Le Boudec, Mario Paolone, Fabrizio Sossan, Rahul Kumar Gupta

The paper considers the problem of estimating the parameters of the compound admittance matrix of three-phase untransposed low-and medium-voltage electrical distribution networks using synchrophasor measurements from phasor measurement units (PMUs). The wo ...

2021

A machine-learning algorithm correctly classifies cortical evoked potentials from both visual stimulation and electrical stimulation of the optic nerve

Diego Ghezzi, Eleonora Borda, Vivien Gaillet, Elodie Geneviève Zollinger

Objective. Optic nerve's intraneural stimulation is an emerging neuroprosthetic approach to provide artificial vision to totally blind patients. An open question is the possibility to evoke individual non-overlapping phosphenes via selective intraneural op ...

IOP PUBLISHING LTD2021

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Linear model

Training Techniques for Presence-Only Habitat Suitability Mapping with Deep Learning

Positive and Negative Critiquing for VAE-based Recommenders

Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation

Discrete-Choice Mining of Social Processes

Running Speed Estimation Using Shoe-Worn Inertial Sensors: Direct Integration, Linear, and Personalized Model

Compact atomic descriptors enable accurate predictions via linear models

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models

Swimming Phase-Based Performance Evaluation Using a Single IMU in Main Swimming Techniques

Compound Admittance Matrix Estimation of Three-phase Untransposed Power Distribution Grids using Synchrophasor Measurements

A machine-learning algorithm correctly classifies cortical evoked potentials from both visual stimulation and electrical stimulation of the optic nerve

Graph Chatbot

Chat with Graph Search

Positive and Negative Critiquing for VAE-based Recommenders

Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation

Compact atomic descriptors enable accurate predictions via linear models

Swimming Phase-Based Performance Evaluation Using a Single IMU in Main Swimming Techniques

Discrete-Choice Mining of Social Processes

Running Speed Estimation Using Shoe-Worn Inertial Sensors: Direct Integration, Linear, and Personalized Model

Multi-ion-sensing emulator and multivariate calibration optimization by machine learning models

Training Techniques for Presence-Only Habitat Suitability Mapping with Deep Learning

A machine-learning algorithm correctly classifies cortical evoked potentials from both visual stimulation and electrical stimulation of the optic nerve

Compound Admittance Matrix Estimation of Three-phase Untransposed Power Distribution Grids using Synchrophasor Measurements