Zobrazeno 1 - 10
of 123
pro vyhledávání: '"Srivastava, Ajitesh"'
Autor:
Srivastava, Ajitesh, Teng, Shang-Hua
Given a network with an ongoing epidemic, the network immunization problem seeks to identify a fixed number of nodes to immunize in order to maximize the number of infections prevented. One of the fundamental computational challenges in network immun
Externí odkaz:
http://arxiv.org/abs/2410.19205
Neural networks are trained by choosing an architecture and training the parameters. The choice of architecture is often by trial and error or with Neural Architecture Search (NAS) methods. While NAS provides some automation, it often relies on discr
Externí odkaz:
http://arxiv.org/abs/2410.08339
In the realm of medical imaging, leveraging large-scale datasets from various institutions is crucial for developing precise deep learning models, yet privacy concerns frequently impede data sharing. federated learning (FL) emerges as a prominent sol
Externí odkaz:
http://arxiv.org/abs/2406.17235
During the COVID-19 pandemic, a major driver of new surges has been the emergence of new variants. When a new variant emerges in one or more countries, other nations monitor its spread in preparation for its potential arrival. The impact of the new v
Externí odkaz:
http://arxiv.org/abs/2401.03390
Spectral-domain CNNs have been shown to be more efficient than traditional spatial CNNs in terms of reducing computation complexity. However they come with a `kernel explosion' problem that, even after compression (pruning), imposes a high memory bur
Externí odkaz:
http://arxiv.org/abs/2310.10902
Autor:
Srivastava, Ajitesh
Measuring distance or similarity between time-series data is a fundamental aspect of many applications including classification and clustering. Existing measures may fail to capture similarities due to local trends (shapes) and may even produce misle
Externí odkaz:
http://arxiv.org/abs/2309.03579
Acoustic-to-articulatory inversion (AAI) involves mapping from the acoustic to the articulatory space. Signal-processing features like the MFCCs, have been widely used for the AAI task. For subjects with dysarthric speech, AAI is challenging because
Externí odkaz:
http://arxiv.org/abs/2309.01108
Autor:
Srivastava, Ajitesh, Ramírez, Juan Marcos, Díaz-Aranda, Sergio, Aguilar, Jose, Ortega, Antonio, Anta, Antonio Fernández, Lillo, Rosa Elvira
Indirect surveys, in which respondents provide information about other people they know, have been proposed for estimating (nowcasting) the size of a \emph{hidden population} where privacy is important or the hidden population is hard to reach. Examp
Externí odkaz:
http://arxiv.org/abs/2307.06643
The traditional methods for detecting autism spectrum disorder (ASD) are expensive, subjective, and time-consuming, often taking years for a diagnosis, with many children growing well into adolescence and even adulthood before finally confirming the
Externí odkaz:
http://arxiv.org/abs/2211.07360
Infectious disease forecasting for ongoing epidemics has been traditionally performed, communicated, and evaluated as numerical targets - 1, 2, 3, and 4 week ahead cases, deaths, and hospitalizations. While there is great value in predicting these nu
Externí odkaz:
http://arxiv.org/abs/2209.04035