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pro vyhledávání: '"Luo, Da"'
The rise of online multi-modal sharing platforms like TikTok and YouTube has enabled personalized recommender systems to incorporate multiple modalities (such as visual, textual, and acoustic) into user representations. However, addressing the challe
Externí odkaz:
http://arxiv.org/abs/2406.11781
We investigated the optimal control of a continuous variable system, focusing on entanglement generation in an optomechanical system without utilizing Fock basis cutoffs. Using the Krotov algorithm to optimize the dynamics of the covariance matrix, w
Externí odkaz:
http://arxiv.org/abs/2404.16227
Autor:
Luo, Da-Wei, Yu, Ting
Publikováno v:
Journal of the Optical Society of America B Vol. 41, Issue 8, pp. C112-C119 (2024)
We consider the Jaynes-Cummings (JC) model embedded in a structured environment, where the atom inside an optical cavity will be affected by a hierarchical environment consisting of the cavity and its environment. We propose several effective strateg
Externí odkaz:
http://arxiv.org/abs/2404.13762
Autor:
Luo, Da-Wei, Yu, Ting
We propose a protocol to overcome the shot noise limit and reach the Heisenberg scaling limit for parameter estimation by using quantum optimal control and a time-reversal strategy. Exemplified through the phase estimation, which can play an importan
Externí odkaz:
http://arxiv.org/abs/2312.14443
Autor:
Luo, Da-Wei, Yu, Ting
Non-Markovian effects of an open system dynamics are typically characterized by non-monotonic information flows from the system to its environment or information backflows from the environment to the system. By using a two-level system (TLS) coupled
Externí odkaz:
http://arxiv.org/abs/2312.13421
Few-shot Relation Extraction (FSRE) aims to extract relational facts from a sparse set of labeled corpora. Recent studies have shown promising results in FSRE by employing Pre-trained Language Models (PLMs) within the framework of supervised contrast
Externí odkaz:
http://arxiv.org/abs/2312.12021
GNN-based recommenders have excelled in modeling intricate user-item interactions through multi-hop message passing. However, existing methods often overlook the dynamic nature of evolving user-item interactions, which impedes the adaption to changin
Externí odkaz:
http://arxiv.org/abs/2311.16716
Aspect-based sentiment classification is a crucial problem in fine-grained sentiment analysis, which aims to predict the sentiment polarity of the given aspect according to its context. Previous works have made remarkable progress in leveraging atten
Externí odkaz:
http://arxiv.org/abs/2308.11447
Current sequential recommender systems are proposed to tackle the dynamic user preference learning with various neural techniques, such as Transformer and Graph Neural Networks (GNNs). However, inference from the highly sparse user behavior data may
Externí odkaz:
http://arxiv.org/abs/2303.11780
Publikováno v:
Phys. Rev. A 109, 012611 (2024)
We study the remote entanglement generation between macroscopic microwave magnon modes in a coupled cavity system. The cavities are connected via an optical fiber, which necessitates the use of a frequency conversion inside the cavity. The converter
Externí odkaz:
http://arxiv.org/abs/2211.09315