Zobrazeno 1 - 10
of 3 252
pro vyhledávání: '"Tran, Viet"'
Autor:
Nazirkar, Nimish, Tran, Viet, Bassene, Pascal, Ndiaye, Atoumane, Barringer, Julie, Jiang, Jie, Cha, Wonsuk, Harder, Ross, Shi, Jian, NGom, Moussa, Fohtung, Edwin
The dynamic control of novel states of matter beyond thermodynamic equilibrium is a fundamental pursuit in condensed matter physics. Intense terahertz fields have enabled metal-insulator transitions, superconductivity, quantum paraelectric ferroelect
Externí odkaz:
http://arxiv.org/abs/2410.20577
From the observation of a diffusion path $(X_t)_{t\in [0,T]}$ on a compact connected $d$-dimensional manifold $M$ without boundary, we consider the problem of estimating the stationary measure $\mu$ of the process. Wang and Zhu (2023) showed that for
Externí odkaz:
http://arxiv.org/abs/2410.11777
Autor:
Vo, Thieu N., Tran, Viet-Hoang, Huu, Tho Tran, The, An Nguyen, Tran, Thanh, Nguyen-Nhat, Minh-Khoi, Pham, Duy-Tung, Nguyen, Tan Minh
Neural Functional Networks (NFNs) have gained increasing interest due to their wide range of applications, including extracting information from implicit representations of data, editing network weights, and evaluating policies. A key design principl
Externí odkaz:
http://arxiv.org/abs/2410.04213
Autor:
Tran, Viet-Hoang, Vo, Thieu N., The, An Nguyen, Huu, Tho Tran, Nguyen-Nhat, Minh-Khoi, Tran, Thanh, Pham, Duy-Tung, Nguyen, Tan Minh
This paper systematically explores neural functional networks (NFN) for transformer architectures. NFN are specialized neural networks that treat the weights, gradients, or sparsity patterns of a deep neural network (DNN) as input data and have prove
Externí odkaz:
http://arxiv.org/abs/2410.04209
This paper presents a novel Collaborative Cyberattack Detection (CCD) system aimed at enhancing the security of blockchain-based data-sharing networks by addressing the complex challenges associated with noise addition in federated learning models. L
Externí odkaz:
http://arxiv.org/abs/2409.04972
Model Inversion (MI) is a type of privacy violation that focuses on reconstructing private training data through abusive exploitation of machine learning models. To defend against MI attacks, state-of-the-art (SOTA) MI defense methods rely on regular
Externí odkaz:
http://arxiv.org/abs/2409.01062
Music streaming services often leverage sequential recommender systems to predict the best music to showcase to users based on past sequences of listening sessions. Nonetheless, most sequential recommendation methods ignore or insufficiently account
Externí odkaz:
http://arxiv.org/abs/2408.16578
Autor:
Son, Do Hai, Manh, Bui Duc, Khoa, Tran Viet, Trung, Nguyen Linh, Hoang, Dinh Thai, Minh, Hoang Trong, Alem, Yibeltal, Minh, Le Quang
Blockchain-based supply chain (BSC) systems have tremendously been developed recently and can play an important role in our society in the future. In this study, we develop an anomaly detection model for BSC systems. Our proposed model can detect cyb
Externí odkaz:
http://arxiv.org/abs/2407.15603
Autor:
Khoa, Tran Viet, Son, Do Hai, Hoang, Dinh Thai, Trung, Nguyen Linh, Quynh, Tran Thi Thuy, Nguyen, Diep N., Ha, Nguyen Viet, Dutkiewicz, Eryk
With the ever-increasing popularity of blockchain applications, securing blockchain networks plays a critical role in these cyber systems. In this paper, we first study cyberattacks (e.g., flooding of transactions, brute pass) in blockchain networks
Externí odkaz:
http://arxiv.org/abs/2407.04011
Sliced Wasserstein (SW) distance in Optimal Transport (OT) is widely used in various applications thanks to its statistical effectiveness and computational efficiency. On the other hand, Tree Wassenstein (TW) and Tree-sliced Wassenstein (TSW) are ins
Externí odkaz:
http://arxiv.org/abs/2406.13725