no code implementations • 21 Mar 2024 • Jiawen Liu, Yuanyuan Yao, Pengcheng An, Qi Wang
In children's collaborative learning, effective peer conversations can significantly enhance the quality of children's collaborative interactions.
no code implementations • 5 Sep 2023 • Jiawen Liu, Kan Li
To enhance sampling diversity and improve the model's adaptability, we propose a smooth function that maps the combined result of sentence-level and word-level information to an appropriate range, and employ probabilistic sampling based on the mapped values instead of threshold truncation.
no code implementations • 3 Mar 2020 • Jie Liu, Jiawen Liu, Zhen Xie, Dong Li
How to accurately and efficiently label data on a mobile device is critical for the success of training machine learning models on mobile devices.
no code implementations • 10 Jun 2019 • Jie Liu, Jiawen Liu, Wan Du, Dong Li
In this paper, we perform a variety of experiments on a representative mobile device (the NVIDIA TX2) to study the performance of training deep learning models.
no code implementations • 21 Oct 2018 • Jiawen Liu, Dong Li, Gokcen Kestor, Jeffrey Vetter
These frameworks employ a dataflow model where the NN training is modeled as a directed graph composed of a set of nodes.