no code implementations • 31 Dec 2022 • Wei Cao, Liguo Zhou, Yuhong Huang, Alois Knoll
There are many artificial intelligence algorithms for autonomous driving, but directly installing these algorithms on vehicles is unrealistic and expensive.
1 code implementation • 22 Nov 2022 • Tianping Zhang, Zheyu Zhang, Zhiyuan Fan, Haoyan Luo, Fengyuan Liu, Wei Cao, Jian Li
The major challenge in automated feature generation is to efficiently and accurately identify useful features from a vast pool of candidate features.
no code implementations • 4 Jul 2022 • Tianping Zhang, Yizhuo Zhang, Wei Cao, Jiang Bian, Xiaohan Yi, Shun Zheng, Jian Li
It uses less than 5% FLOPS compared with previous SOTA methods on the largest benchmark dataset.
no code implementations • 29 Apr 2022 • Andrey A. Kistanov, Stepan A. Shcherbinin, Romain Botella, Artur Davletshin, Wei Cao
A large number of novel two-dimensional (2D) materials are constantly discovered and deposed into the databases.
1 code implementation • ICLR 2022 • Wei Fan, Shun Zheng, Xiaohan Yi, Wei Cao, Yanjie Fu, Jiang Bian, Tie-Yan Liu
However, the complicated dependencies of the PTS signal on its inherent periodicity as well as the sophisticated composition of various periods hinder the performance of PTS forecasting.
1 code implementation • 24 Nov 2021 • Zhining Liu, Pengfei Wei, Zhepei Wei, Boyang Yu, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang
Class-imbalance is a common problem in machine learning practice.
no code implementations • 9 Apr 2021 • Disheng Tang, Wei Cao, Jiang Bian, Tie-Yan Liu, Zhifeng Gao, Shun Zheng, Jue Liu
We used a stochastic metapopulation model with a hierarchical structure and fitted the model to the positive cases in the US from the start of outbreak to the end of 2020.
no code implementations • 1 Apr 2021 • Jiansong Li, Xiao Dong, Guangli Li, Peng Zhao, Xueying Wang, Xiaobing Chen, Xianzhi Yu, Yongxin Yang, Zihan Jiang, Wei Cao, Lei Liu, Xiaobing Feng
The training of deep neural networks (DNNs) is usually memory-hungry due to the limited device memory capacity of DNN accelerators.
no code implementations • 1 Jan 2021 • Yihan He, Wei Cao, Shun Zheng, Zhifeng Gao, Jiang Bian
In recent years, research communities have been developing stochastic sampling methods to handle large graphs when it is unreal to put the whole graph into a single batch.
1 code implementation • 1 Jan 2021 • Yihan He, Wei Cao, Shun Zheng, Zhifeng Gao, Jiang Bian
In this work, we present a new method named Fourier Temporal State Embedding (FTSE) to address the temporal information in dynamic graph representation learning.
no code implementations • 3 Dec 2020 • Yanfei Kang, Wei Cao, Fotios Petropoulos, Feng Li
In this work, we suggest a change of focus from the historical data to the produced forecasts to extract features.
2 code implementations • NeurIPS 2020 • Zhining Liu, Pengfei Wei, Jing Jiang, Wei Cao, Jiang Bian, Yi Chang
This makes MESA generally applicable to most of the existing learning models and the meta-sampler can be efficiently applied to new tasks.
no code implementations • 7 May 2020 • Wei Cao, Alex Dytso, Michael Fauß, H. Vincent Poor, Gang Feng
First, an estimator proposed by Bhattacharya is revisited and improved convergence rates are derived.
no code implementations • ICLR 2020 • Fan Yang, Ling Chen, Fan Zhou, Yusong Gao, Wei Cao
Real-world dynamical systems often consist of multiple stochastic subsystems that interact with each other.
1 code implementation • 27 Nov 2019 • Weiqi Chen, Ling Chen, Yu Xie, Wei Cao, Yusong Gao, Xiaojie Feng
Traffic forecasting is of great importance to transportation management and public safety, and very challenging due to the complicated spatial-temporal dependency and essential uncertainty brought about by the road network and traffic conditions.
1 code implementation • 8 Sep 2019 • Zhining Liu, Wei Cao, Zhifeng Gao, Jiang Bian, Hechang Chen, Yi Chang, Tie-Yan Liu
To tackle this problem, we conduct deep investigations into the nature of class imbalance, which reveals that not only the disproportion between classes, but also other difficulties embedded in the nature of data, especially, noises and class overlapping, prevent us from learning effective classifiers.
no code implementations • 24 Jun 2019 • Dong Wang, Yitong Li, Wei Cao, Liqun Chen, Qi Wei, Lawrence Carin
We propose a Leaked Motion Video Predictor (LMVP) to predict future frames by capturing the spatial and temporal dependencies from given inputs.
2 code implementations • IJCNLP 2019 • Shun Zheng, Wei Cao, Wei Xu, Jiang Bian
Most existing event extraction (EE) methods merely extract event arguments within the sentence scope.
Ranked #4 on Document-level Event Extraction on ChFinAnn
4 code implementations • NeurIPS 2018 • Wei Cao, Dong Wang, Jian Li, Hao Zhou, Lei LI, Yitan Li
It is ubiquitous that time series contains many missing values.
General Classification Multivariate Time Series Forecasting +4
no code implementations • NeurIPS 2015 • Wei Cao, Jian Li, Yufei Tao, Zhize Li
This paper discusses how to efficiently choose from $n$ unknowndistributions the $k$ ones whose means are the greatest by a certainmetric, up to a small relative error.
no code implementations • 24 May 2013 • Yin Song, Longbing Cao, Xuhui Fan, Wei Cao, Jian Zhang
These sequence-level latent parameters for each sequence are modeled as latent Dirichlet random variables and parameterized by a set of deterministic database-level hyper-parameters.