no code implementations • 2 Nov 2023 • Mingjie Zhou
In multimodal machine learning tasks, it is due to the complexity of the assignments that the network structure, in most cases, is assembled in a sophisticated way.
1 code implementation • 22 May 2023 • Yuan Sui, Mengyu Zhou, Mingjie Zhou, Shi Han, Dongmei Zhang
Although tables can be used as input to LLMs with serialization, there is a lack of comprehensive studies that examine whether LLMs can truly comprehend such data.
no code implementations • MM '22: Proceedings of the 30th ACM International Conference on Multimedia 2022 • Huafeng Liu, Liping Jing, Dahai Yu, Mingjie Zhou, Michael Ng
In this paper, we propose an intention neural process model (INP) for user cold-start recommendation (i. e., user with very few historical interactions), a novel extension of the neural stochastic process family using a general meta learning strategy with intrinsic and extrinsic intention learning for robust user preference learning.
no code implementations • 2 Sep 2022 • Xinyi He, Mengyu Zhou, Mingjie Zhou, Jialiang Xu, Xiao Lv, Tianle Li, Yijia Shao, Shi Han, Zejian yuan, Dongmei Zhang
Tabular data analysis is performed every day across various domains.
no code implementations • 23 May 2022 • Yihang Gao, Huafeng Liu, Michael K. Ng, Mingjie Zhou
Wide applications of differentiable two-player sequential games (e. g., image generation by GANs) have raised much interest and attention of researchers to study efficient and fast algorithms.
no code implementations • 18 Mar 2021 • Yihang Gao, Michael K. Ng, Mingjie Zhou
Studied here are Wasserstein generative adversarial networks (WGANs) with GroupSort neural networks as their discriminators.