Zobrazeno 1 - 10
of 902
pro vyhledávání: '"Sheng, Quan Z"'
Autor:
Ma, Congbo, Wang, Hu, Qiu, Zitai, Xue, Shan, Wu, Jia, Yang, Jian, Nakov, Preslav, Sheng, Quan Z.
Social media data is inherently rich, as it includes not only text content, but also users, geolocation, entities, temporal information, and their relationships. This data richness can be effectively modeled using heterogeneous information networks (
Externí odkaz:
http://arxiv.org/abs/2411.12588
Autor:
Li, Zihao, Yang, Chao, Chen, Yakun, Wang, Xianzhi, Chen, Hongxu, Xu, Guandong, Yao, Lina, Sheng, Quan Z.
Recent years have witnessed the remarkable success of recommendation systems (RSs) in alleviating the information overload problem. As a new paradigm of RSs, session-based recommendation (SR) specializes in users' short-term preference capture and ai
Externí odkaz:
http://arxiv.org/abs/2408.14851
Online video streaming has evolved into an integral component of the contemporary Internet landscape. Yet, the disclosure of user requests presents formidable privacy challenges. As users stream their preferred online videos, their requests are autom
Externí odkaz:
http://arxiv.org/abs/2408.14735
Pre-training exploits public datasets to pre-train an advanced machine learning model, so that the model can be easily tuned to adapt to various downstream tasks. Pre-training has been extensively explored to mitigate computation and communication re
Externí odkaz:
http://arxiv.org/abs/2408.09478
To preserve the data privacy, the federated learning (FL) paradigm emerges in which clients only expose model gradients rather than original data for conducting model training. To enhance the protection of model gradients in FL, differentially privat
Externí odkaz:
http://arxiv.org/abs/2408.08642
Autor:
Luo, Xuexiong, Wu, Jia, Yang, Jian, Xue, Shan, Beheshti, Amin, Sheng, Quan Z., McAlpine, David, Sowman, Paul, Giral, Alexis, Yu, Philip S.
Exploring the complex structure of the human brain is crucial for understanding its functionality and diagnosing brain disorders. Thanks to advancements in neuroimaging technology, a novel approach has emerged that involves modeling the human brain a
Externí odkaz:
http://arxiv.org/abs/2406.02594
Pedestrian trajectory prediction plays a pivotal role in the realms of autonomous driving and smart cities. Despite extensive prior research employing sequence and generative models, the unpredictable nature of pedestrians, influenced by their social
Externí odkaz:
http://arxiv.org/abs/2405.07164
Despite the significant progress of fully-supervised video captioning, zero-shot methods remain much less explored. In this paper, we propose to take advantage of existing pre-trained large-scale vision and language models to directly generate captio
Externí odkaz:
http://arxiv.org/abs/2405.07046
The exploration of high-speed movement by robots or road traffic agents is crucial for autonomous driving and navigation. Trajectory prediction at high speeds requires considering historical features and interactions with surrounding entities, a comp
Externí odkaz:
http://arxiv.org/abs/2405.07041
Caching content at the network edge is a popular and effective technique widely deployed to alleviate the burden of network backhaul, shorten service delay and improve service quality. However, there has been some controversy over privacy violations
Externí odkaz:
http://arxiv.org/abs/2405.01844