10 papers · ranked by Valyu relevance
Ming Xiao, Mikael Skoglund, H. Vincent Poor, Onur Günlü + 2 more
'Rafael F. Schaefer' 'Holger Boche'] This article aims to give a comprehensive and rigorous review of the principles and recent development of coding for large-scale distributed machine learning (DML). With increasing data volumes and the pervasive deployment of sensors and computing machines, machine learning has…
Ari S. Benjamin, Ling-Qi Zhang, Cheng Qiu, Alan A. Stocker + 1 more
'Konrad P. Kording'] Human sensory systems are more sensitive to common features in the environment than uncommon features. For example, small deviations from the more frequently encountered horizontal orientations can be more easily detected than small deviations from the less frequent diagonal ones. Here we find that…
Robert Rosenbaum, Gennady S. Cymbalyuk
Artificial neural networks are often interpreted as abstract models of biological neuronal networks, but they are typically trained using the biologically unrealistic backpropagation algorithm and its variants. Predictive coding has been proposed as a potentially more biologically realistic alternative to…
Vicente Mora, Juan Geraldo, Ildefonso Roldán, Ester Galiana + 8 more
Rotational mechanics is a fundamental determinant of left ventricular ejection fraction (LVEF). The coding system currently employed in clinical practice does not distinguish between rotational patterns. We propose an alternative coding system that makes possible to identify the rotational pattern of the LV and relate…
Jiamin Sun, Zhongjie Zhu, Renwei Tu, Zhibo Xie + 1 more
In Versatile Video Coding (VVC), the partition patterns for coding units (CUs) have significant impact on the encoding efficiency. Determining the optimal CU partition is particularly time-consuming due to the calculation and comparison of rate-distortion costs for all possible partition patterns, especially during the…
Kungjui Hou, Kunlun Wu, Yongcheng Zhou
Background Spiking Neural Networks (SNNs) have emerged as a promising paradigm in artificial intelligence due to their energy efficiency. However, training SNNs remains a formidable challenge because the nondifferentiable nature of spike activation functions prevents the direct application of conventional…
Sorinel A. Oprisan, Ana Oprisan, Xiangjie Kong
This study presents a novel analytical framework for understanding the relationship between the image gradients and the symmetries of the Gray Level Co-occurrence Matrix (GLCM). Analytical expression for four key features-sum average (SA), sum variance (SV), difference variance (DV), and entropy-were derived to capture…
Yaqiang Wang, Xu Han, Xuechao Hao, Tao Zhu + 2 more
'Joaquim Carreras'] The International Classification of Diseases (ICD) has an important role in building applications for clinical medicine. Extremely large ICD coding label sets and imbalanced label distribution bring the problem of inconsistency between the local batch data distribution and the global training data…
Tenzin Chan, De Wen Soh, Christopher Hillar, Kichun Lee + 1 more
'Boris Ryabko'] Oftentimes in a complex system it is observed that as a control parameter is varied, there are certain intervals during which the system undergoes dramatic change. In biology especially, these signatures of criticality are thought to be connected with efficient computation and information processing.…
Jesús E. Garca, Verónica A. González-López, Gustavo H. Tasca, Karina Y. Yaginuma + 1 more
In the framework of coding theory, under the assumption of a Markov process $(X_{t})$ on a finite alphabet $A,$ the compressed representation of the data will be composed of a description of the model used to code the data and the encoded data. Given the model, the Huffman’s algorithm is optimal for the number of bits…