Zobrazeno 1 - 10
of 5 246
pro vyhledávání: '"Nguyen, Minh P."'
Autor:
Nguyen, Minh, Shareghi, Ehsan
Language agents have shown promising adaptability in dynamic environments to perform complex tasks. However, despite the versatile knowledge embedded in large language models, these agents still fall short when it comes to tasks that require planning
Externí odkaz:
http://arxiv.org/abs/2411.08432
The accurate alignment of 3D woodblock geometrical models with 2D orthographic projection images presents a significant challenge in the digital preservation of Vietnamese cultural heritage. This paper proposes a unified image processing algorithm to
Externí odkaz:
http://arxiv.org/abs/2411.05524
Singing is one of the most cherished forms of human entertainment. However, creating a beautiful song requires an accompaniment that complements the vocals and aligns well with the song instruments and genre. With advancements in deep learning, previ
Externí odkaz:
http://arxiv.org/abs/2411.01661
Autor:
Quy, Vu Khanh, Quy, Nguyen Minh, Hoai, Tran Thi, Shaon, Shaba, Uddin, Md Raihan, Nguyen, Tien, Nguyen, Dinh C., Kaushik, Aryan, Chatzimisios, Periklis
6G wireless networks are expected to provide seamless and data-based connections that cover space-air-ground and underwater networks. As a core partition of future 6G networks, Space-Air-Ground Integrated Networks (SAGIN) have been envisioned to prov
Externí odkaz:
http://arxiv.org/abs/2411.01312
Consensus is arguably the most studied problem in distributed computing as a whole, and particularly in the distributed message-passing setting. In this latter framework, research on consensus has considered various hypotheses regarding the failure t
Externí odkaz:
http://arxiv.org/abs/2410.21538
Material segmentation is a complex task, particularly when dealing with aerial data in poor lighting and atmospheric conditions. To address this, hyperspectral data from specialized cameras can be very useful in addition to RGB images. However, due t
Externí odkaz:
http://arxiv.org/abs/2410.15208
Autor:
Dong, Kris Shengjun, Nikiforov, Dima, Soedarmadji, Widyadewi, Nguyen, Minh, Fletcher, Christopher, Shao, Yakun Sophia
Empowering resource-limited robots to execute computationally intensive tasks such as locomotion and manipulation is challenging. This project provides a comprehensive design space exploration to determine optimal hardware computation architectures s
Externí odkaz:
http://arxiv.org/abs/2410.12142
This paper introduces a novel lossless compression method for compressing geometric attributes of point cloud data with bits-back coding. Our method specializes in using a deep learning-based probabilistic model to estimate the Shannon's entropy of t
Externí odkaz:
http://arxiv.org/abs/2410.18115
Autor:
Nguyen, Minh Hieu, Nguyen, Huu Tien, Nguyen, Trung Thanh, Nguyen, Manh Duong, Hoang, Trong Nghia, Nguyen, Truong Thao, Nguyen, Phi Le
Federated Learning (FL) has emerged as a powerful paradigm for training machine learning models in a decentralized manner, preserving data privacy by keeping local data on clients. However, evaluating the robustness of these models against data pertu
Externí odkaz:
http://arxiv.org/abs/2410.03067
Autor:
Nguyen, Minh Duong, Le, Khanh, Do, Khoi, Tran, Nguyen H., Nguyen, Duc, Trinh, Chien, Yang, Zhaohui
In personalized Federated Learning (pFL), high data heterogeneity can cause significant gradient divergence across devices, adversely affecting the learning process. This divergence, especially when gradients from different users form an obtuse angle
Externí odkaz:
http://arxiv.org/abs/2410.02845