Zobrazeno 1 - 10
of 214
pro vyhledávání: '"Ju, Yue"'
Parameter-Efficient Fine-Tuning (PEFT) has risen as an innovative training strategy that updates only a select few model parameters, significantly lowering both computational and memory demands. PEFT also helps to decrease data transfer in federated
Externí odkaz:
http://arxiv.org/abs/2409.02346
The emergence of 5G technology marks a significant milestone in developing telecommunication networks, enabling exciting new applications such as augmented reality and self-driving vehicles. However, these improvements bring an increased management c
Externí odkaz:
http://arxiv.org/abs/2406.15638
We propose a secure inference protocol for a distributed setting involving a single server node and multiple client nodes. We assume that the observed data vector is partitioned across multiple client nodes while the deep learning model is located at
Externí odkaz:
http://arxiv.org/abs/2405.03775
The rise of 5G deployments has created the environment for many emerging technologies to flourish. Self-driving vehicles, Augmented and Virtual Reality, and remote operations are examples of applications that leverage 5G networks' support for extreme
Externí odkaz:
http://arxiv.org/abs/2404.10643
Spatial-temporal Gaussian process regression is a popular method for spatial-temporal data modeling. Its state-of-art implementation is based on the state-space model realization of the spatial-temporal Gaussian process and its corresponding Kalman f
Externí odkaz:
http://arxiv.org/abs/2209.12565
Regularized system identification is the major advance in system identification in the last decade. Although many promising results have been achieved, it is far from complete and there are still many key problems to be solved. One of them is the asy
Externí odkaz:
http://arxiv.org/abs/2209.12231
Publikováno v:
In Colloids and Surfaces A: Physicochemical and Engineering Aspects 20 January 2025 705 Part 2
The analysis of long sequence data remains challenging in many real-world applications. We propose a novel architecture, ChunkFormer, that improves the existing Transformer framework to handle the challenges while dealing with long time series. Origi
Externí odkaz:
http://arxiv.org/abs/2112.15087
In this paper, we give a tutorial on asymptotic properties of the Least Square (LS) and Regularized Least Squares (RLS) estimators for the finite impulse response model with filtered white noise inputs. We provide three perspectives: the almost sure
Externí odkaz:
http://arxiv.org/abs/2112.10319
Publikováno v:
In Journal of Environmental Chemical Engineering June 2024 12(3)