In recommendation systems (RS), user behavior data is observational rath...
A shared space area is a low-speed urban area in which pedestrians, cycl...
Understanding pedestrian route choice behavior in complex buildings is
i...
Graph Neural Networks (GNNs) have emerged as the de facto standard for
r...
This paper proposes a comprehensive approach for modeling pedestrian
way...
In this paper, we study the Robust optimization for
sequence Networked s...
Machine learning models are frequently employed to perform either purely...
Although diffusion model has shown great potential for generating higher...
Federated learning (FL) is a technique that trains machine learning mode...
Knowledge graph embedding (KGE) has been intensively investigated for li...
Knowledge distillation aims to compress a powerful yet cumbersome teache...
Knowledge distillation has recently become a popular technique to improv...
Spectral unmixing (SU) expresses the mixed pixels existed in hyperspectr...
Knowledge distillation is a generalized logits matching technique for mo...
Although route and exit choice in complex buildings are important aspect...
Sampling strategies have been widely applied in many recommendation syst...
Recommendation from implicit feedback is a highly challenging task due t...
This work studied the score-based black-box adversarial attack problem, ...
Adversarial examples have been shown to be the severe threat to deep neu...
Recommendation from implicit feedback is a highly challenging task due t...
Federated learning, as an emerging distributed training model of neural
...
Distillation is an effective knowledge-transfer technique that uses pred...