Zobrazeno 1 - 10
of 145 647
pro vyhledávání: '"cs.LG"'
In the hydrology field, time series forecasting is crucial for efficient water resource management, improving flood and drought control and increasing the safety and quality of life for the general population. However, predicting long-term streamflow
Externí odkaz:
http://arxiv.org/abs/2312.08763
Autor:
Lukasik, Michal, Nagarajan, Vaishnavh, Rawat, Ankit Singh, Menon, Aditya Krishna, Kumar, Sanjiv
The success of modern neural networks has prompted study of the connection between memorisation and generalisation: overparameterised models generalise well, despite being able to perfectly fit (memorise) completely random labels. To carefully study
Externí odkaz:
http://arxiv.org/abs/2310.05337
Autor:
Akansha, Singh
Graph Neural Networks (GNNs) revolutionize machine learning for graph-structured data, effectively capturing complex relationships. They disseminate information through interconnected nodes, but long-range interactions face challenges known as "over-
Externí odkaz:
http://arxiv.org/abs/2308.15568
Autor:
Shehab, Muhammad, Almohamad, Abdullateef, Elsayed, Mohamed, Badawy, Ahmed, Khattab, Tamer, Zorba, Nizar, Hasna, Mazen, Trinchero, Daniele
We investigate THz communication uplink multiple access using cascaded intelligent reflecting surfaces (IRSs) assuming correlated channels. Two independent objectives to be achieved via adjusting the phases of the cascaded IRSs: 1) maximizing the rec
Externí odkaz:
http://arxiv.org/abs/2303.09476
Autor:
Ariane Pinche, Peter Stokes
Publikováno v:
Journal of Data Mining and Digital Humanities, Vol Historical Documents and... (2024)
With this special issue of the Journal of Data Mining and Digital Humanities (JDMDH), we bringtogether in one single volume several experiments, projects and reflections related to automatic textrecognition applied to historical documents. More and m
Externí odkaz:
https://doaj.org/article/0aa874c87b904ad2a6b793699d0b0b80
Deep learning models have become increasingly useful in many different industries. On the domain of image classification, convolutional neural networks proved the ability to learn robust features for the closed set problem, as shown in many different
Externí odkaz:
http://arxiv.org/abs/2102.03243
Skew-Gaussian processes (SkewGPs) extend the multivariate Unified Skew-Normal distributions over finite dimensional vectors to distribution over functions. SkewGPs are more general and flexible than Gaussian processes, as SkewGPs may also represent a
Externí odkaz:
http://arxiv.org/abs/2012.06846
Autor:
Bian, Weijie, Wu, Kailun, Ren, Lejian, Pi, Qi, Zhang, Yujing, Xiao, Can, Sheng, Xiang-Rong, Zhu, Yong-Nan, Chan, Zhangming, Mou, Na, Luo, Xinchen, Xiang, Shiming, Zhou, Guorui, Zhu, Xiaoqiang, Deng, Hongbo
Feature interaction has been recognized as an important problem in machine learning, which is also very essential for click-through rate (CTR) prediction tasks. In recent years, Deep Neural Networks (DNNs) can automatically learn implicit nonlinear i
Externí odkaz:
http://arxiv.org/abs/2011.05625
Autor:
Gmeiner, Peter
Inferring the causal direction and causal effect between two discrete random variables X and Y from a finite sample is often a crucial problem and a challenging task. However, if we have access to observational and interventional data, it is possible
Externí odkaz:
http://arxiv.org/abs/2007.15047
Autor:
Yazici, Yusuf
Publikováno v:
pp. 235-244, 2020. CS & IT - CSCP 2020
Credit card fraud is an ongoing problem for almost all industries in the world, and it raises millions of dollars to the global economy each year. Therefore, there is a number of research either completed or proceeding in order to detect these kinds
Externí odkaz:
http://arxiv.org/abs/2007.14622