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pro vyhledávání: '"CHENG, JIA"'
We investigate quantum-enhanced metrology in a triple point criticality and discover that quantum criticality can not always enhance measuring precision. We have developed suitable adiabatic evolution protocols approaching a final point around the tr
Externí odkaz:
http://arxiv.org/abs/2409.14048
Autor:
Liu, Qi, Tang, Xingyuan, Huang, Jianqiang, Yu, Xiangqian, Jin, Haoran, Chen, Jin, Pu, Yuanhao, Lian, Defu, Qu, Tan, Wang, Zhe, Cheng, Jia, Lei, Jun
Natural content and advertisement coexist in industrial recommendation systems but differ in data distribution. Concretely, traffic related to the advertisement is considerably sparser compared to that of natural content, which motivates the developm
Externí odkaz:
http://arxiv.org/abs/2408.16238
Zero-shot dialogue state tracking (DST) transfers knowledge to unseen domains, reducing the cost of annotating new datasets. Previous zero-shot DST models mainly suffer from domain transferring and partial prediction problems. To address these challe
Externí odkaz:
http://arxiv.org/abs/2404.08559
In real-life conversations, the content is diverse, and there exists the one-to-many problem that requires diverse generation. Previous studies attempted to introduce discrete or Gaussian-based continuous latent variables to address the one-to-many p
Externí odkaz:
http://arxiv.org/abs/2404.06760
Publikováno v:
Robotic Intelligence and Automation, 2024, Vol. 44, Issue 6, pp. 922-934.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/RIA-12-2023-0181
Click-through rate (CTR) prediction is a vital task in industrial recommendation systems. Most existing methods focus on the network architecture design of the CTR model for better accuracy and suffer from the data sparsity problem. Especially in ind
Externí odkaz:
http://arxiv.org/abs/2312.06683
Autor:
Liu, Qi, Hou, Xuyang, Jin, Haoran, Chen, Xiaolong, Chen, Jin, Lian, Defu, Wang, Zhe, Cheng, Jia, Lei, Jun
Extracting users' interests from their lifelong behavior sequence is crucial for predicting Click-Through Rate (CTR). Most current methods employ a two-stage process for efficiency: they first select historical behaviors related to the candidate item
Externí odkaz:
http://arxiv.org/abs/2311.10764
Safety is a primary concern when applying reinforcement learning to real-world control tasks, especially in the presence of external disturbances. However, existing safe reinforcement learning algorithms rarely account for external disturbances, limi
Externí odkaz:
http://arxiv.org/abs/2310.07207
Publikováno v:
Energy Science & Engineering, Vol 12, Iss 10, Pp 4236-4259 (2024)
Abstract In this study, nonaxisymmetric endwall contouring technology is employed as a passive control strategy to enhance the stable operating range of a centrifugal compressor with an asymmetric volute. The endwall contouring method is applied to t
Externí odkaz:
https://doaj.org/article/b3f1af79db9c4860ad2c20c878030db3
In Location-Based Services, Point-Of-Interest(POI) recommendation plays a crucial role in both user experience and business opportunities. Graph neural networks have been proven effective in providing personalized POI recommendation services. However
Externí odkaz:
http://arxiv.org/abs/2309.02251