Zobrazeno 1 - 10
of 579
pro vyhledávání: '"Matwin Stan"'
Autor:
Sadeghi Zahra, Matwin Stan
Publikováno v:
Journal of Intelligent Systems, Vol 32, Iss 1, Pp 1-26 (2023)
Anomaly detection is a fundamental problem in data science and is one of the highly studied topics in machine learning. This problem has been addressed in different contexts and domains. This article investigates anomalous data within time series dat
Externí odkaz:
https://doaj.org/article/09851cce627f47e2a14982d9713a0d5b
Autor:
Spadon, Gabriel, Kumar, Jay, Chen, Jinkun, Smith, Matthew, Hilliard, Casey, Vela, Sarah, Gehrmann, Romina, DiBacco, Claudio, Matwin, Stan, Pelot, Ronald
Efficiently handling Automatic Identification System (AIS) data is vital for enhancing maritime safety and navigation, yet is hindered by the system's high volume and error-prone datasets. This paper introduces the Automatic Identification System Dat
Externí odkaz:
http://arxiv.org/abs/2407.08082
A Review of Global Sensitivity Analysis Methods and a comparative case study on Digit Classification
Autor:
Sadeghi, Zahra, Matwin, Stan
Global sensitivity analysis (GSA) aims to detect influential input factors that lead a model to arrive at a certain decision and is a significant approach for mitigating the computational burden of processing high dimensional data. In this paper, we
Externí odkaz:
http://arxiv.org/abs/2406.16975
Aquatic non-indigenous species (NIS) pose significant threats to biodiversity, disrupting ecosystems and inflicting substantial economic damages across agriculture, forestry, and fisheries. Due to the fast growth of global trade and transportation ne
Externí odkaz:
http://arxiv.org/abs/2401.13098
In this paper, we propose leveraging causal generative learning as an interpretable tool for explaining image classifiers. Specifically, we present a generative counterfactual inference approach to study the influence of visual features (i.e., pixels
Externí odkaz:
http://arxiv.org/abs/2401.11394
Autor:
Zare, Nader, Amini, Omid, Sayareh, Aref, Sarvmaili, Mahtab, Firouzkouhi, Arad, Matwin, Stan, Soares, Amilcar
The RoboCup competition was started in 1997, and is known as the oldest RoboCup league. The RoboCup 2D Soccer Simulation League is a stochastic, partially observable soccer environment in which 24 autonomous agents play on two opposing teams. In this
Externí odkaz:
http://arxiv.org/abs/2401.03406
Autor:
Spadon, Gabriel, Kumar, Jay, Eden, Derek, van Berkel, Josh, Foster, Tom, Soares, Amilcar, Fablet, Ronan, Matwin, Stan, Pelot, Ronald
This paper addresses the challenge of boosting the precision of multi-path long-term vessel trajectory forecasting on engineered sequences of Automatic Identification System (AIS) data using feature fusion for problem shifting. We have developed a de
Externí odkaz:
http://arxiv.org/abs/2310.18948
Autor:
Zare, Nader, Sayareh, Aref, Amini, Omid, Sarvmaili, Mahtab, Firouzkouhi, Arad, Matwin, Stan, Soares, Amilcar
Soccer, also known as football in some parts of the world, involves two teams of eleven players whose objective is to score more goals than the opposing team. To simulate this game and attract scientists from all over the world to conduct research an
Externí odkaz:
http://arxiv.org/abs/2307.16875
The RoboCup competitions hold various leagues, and the Soccer Simulation 2D League is a major one among them. Soccer Simulation 2D (SS2D) match involves two teams, including 11 players and a coach, competing against each other. The players can only c
Externí odkaz:
http://arxiv.org/abs/2305.19283