no code implementations • 5 Jun 2018 • Jianzhong Sheng, Chuanbo Chen, Chenchen Fu, Chun Jason Xue
Convolution operations dominate the overall execution time of Convolutional Neural Networks (CNNs).
no code implementations • 25 Sep 2019 • Yufei Cui, Wuguannan Yao, Qiao Li, Antoni Chan, Chun Jason Xue
In this work, assuming that the exact posterior or a decent approximation is obtained, we propose a generic framework to approximate the output probability distribution induced by model posterior with a parameterized model and in an amortized fashion.
no code implementations • 18 Feb 2023 • Jingzong Li, Yik Hong Cai, Libin Liu, Yu Mao, Chun Jason Xue, Hong Xu
3D object detection plays a pivotal role in many applications, most notably autonomous driving and robotics.
no code implementations • 4 Jan 2024 • Shangyu Wu, Ying Xiong, Yufei Cui, Xue Liu, Buzhou Tang, Tei-Wei Kuo, Chun Jason Xue
Retrieval-based augmentations that aim to incorporate knowledge from an external database into language models have achieved great success in various knowledge-intensive (KI) tasks, such as question-answering and text generation.
Natural Language Understanding Neural Architecture Search +5
no code implementations • 3 Mar 2024 • Yu Mao, Weilan Wang, Hongchao Du, Nan Guan, Chun Jason Xue
Deploying Large Language Models (LLMs) on edge or mobile devices offers significant benefits, such as enhanced data privacy and real-time processing capabilities.
no code implementations • 17 Apr 2024 • Jun Wang, Yufei Cui, Yu Mao, Nan Guan, Chun Jason Xue
Our study analyzes the impact of pre-processing parameters on inference and training across single- and multiple-domain datasets.
1 code implementation • 29 May 2019 • Yufei Cui, Wuguannan Yao, Qiao Li, Antoni B. Chan, Chun Jason Xue
In this work, assuming that the exact posterior or a decent approximation is obtained, we propose a generic framework to approximate the output probability distribution induced by model posterior with a parameterized model and in an amortized fashion.
1 code implementation • CVPR 2021 • Yufei Cui, Yu Mao, Ziquan Liu, Qiao Li, Antoni B. Chan, Xue Liu, Tei-Wei Kuo, Chun Jason Xue
Nested dropout is a variant of dropout operation that is able to order network parameters or features based on the pre-defined importance during training.
1 code implementation • 24 May 2022 • Shangyu Wu, Yufei Cui, Jinghuan Yu, Xuan Sun, Tei-Wei Kuo, Chun Jason Xue
Based on the characteristics of the transformed keys, we propose a robust After-Flow Learned Index (AFLI).
1 code implementation • 30 Mar 2022 • Yu Mao, Yufei Cui, Tei-Wei Kuo, Chun Jason Xue
To ease this problem, this paper targets on cutting down the execution time of deep-learning-based compressors.