Authors: Weidong Liu, Xi Luo
arXiv
This paper proposes a new method for estimating sparse precision matrices in the high dimensional setting. It has been popular to study fast computation and adaptive procedures for this problem. We pr...
Authors: Gillian M Raab
arXiv
This paper introduces two methods of creating differentially private (DP) synthetic data that are now incorporated into the \textit{synthpop} package for \textbf{R}. Both are suitable for synthesising...
Authors: Xiaoxu Chen, Zhanhong Cheng, Jian Gang Jin, Martin Trepanier, Lijun Sun
arXiv
Accurate forecasting of bus travel time and its uncertainty is critical to service quality and operation of transit systems; for example, it can help passengers make better decisions on departure time...
Authors: Alessandro Gallo, Manh Duong Phung
arXiv
A trained T1 class Convolutional Neural Network (CNN) model will be used to examine its ability to successfully identify motor imagery when fed pre-processed electroencephalography (EEG) data. In theo...
Authors: Giulia Cereda, Richard D. Gill, Franco Taroni
arXiv
The rare type match problem is an evaluative challenging situation in which the analysis of a DNA profile reveals the presence of (at least) one allele which is not contained in the reference database...
Authors: Argyro Lafatzi, Athanasios Rakitzis
arXiv
In this work, we study the performance of two-sided EWMA charts for monitoring double bounded processes using individual observations. Specifically, the term double bounded refers to observations in t...
Authors: Pau Clusella, Elif Köksal-Ersöz, Jordi Garcia-Ojalvo, Giulio Ruffini
arXiv
Neural mass models (NMMs) are designed to reproduce the collective dynamics of neuronal populations. A common framework for NMMs assumes heuristically that the output firing rate of a neural populatio...
Authors: Francisco Rowe, Michael Mahony, Sui Tao
arXiv
Given an increasingly volatile climate, the relationship between weather and transit ridership has drawn increasing interest. However, challenges stemming from spatio-temporal dependency and non-stati...
Authors: Elina Thibeau-Sutre, Sasha Collin, Ninon Burgos, Olivier Colliot
arXiv
Deep learning methods have become very popular for the processing of natural images, and were then successfully adapted to the neuroimaging field. As these methods are non-transparent, interpretabilit...
Authors: Jason Maddox, Ryan Sides, Jane Harvill
arXiv
Two new Bayesian methods for estimating and predicting in-game home team win probabilities are proposed. The first method has a prior that adjusts as a function of lead differential and time elapsed....
Authors: Gongbo Zhang, Yijie Peng, Yilong Xu
arXiv
We consider the popular tree-based search strategy within the framework of reinforcement learning, the Monte Carlo Tree Search (MCTS), in the context of finite-horizon Markov decision process. We prop...
Authors: Christopher Boyer, Sangeeta Chatterji, Jasper Cooper, Lori Heise
arXiv
Over the last decade, the number of randomized trials of programs to reduce intimate partner violence (IPV) has grown precipitously. However, most trials continue to measure and code violence using st...
Authors: Tom Birkoben, Hermann Kohlstedt
arXiv
As a result of a hundred million years of evolution, living animals have adapted extremely well to their ecological niche. Such adaptation implies species-specific interactions with their immediate en...
Authors: Terrence Chan, Carla Arus Gomez, Anish Kothikar, Pedro Baiz
arXiv
Land Carbon verification has long been a challenge in the carbon credit market. Carbon verification methods currently available are expensive, and may generate low-quality credit. Scalable and accurat...
Authors: Jean-Nicolas Jérémie, Laurent U Perrinet
arXiv
Humans are able to categorize images very efficiently, in particular to detect the presence of an animal very quickly. Recently, deep learning algorithms based on convolutional neural networks (CNNs)...