no code implementations • 2 Apr 2024 • Tianhao Zhao, Yongcan Chen, Yu Wu, Tianyang Liu, Bo Du, Peilun Xiao, Shi Qiu, Hongda Yang, Guozhen Li, Yi Yang, Yutian Lin
In the first stage, we train a BEV autoencoder to reconstruct the BEV segmentation maps given corrupted noisy latent representation, which urges the decoder to learn fundamental knowledge of typical BEV patterns.
no code implementations • 10 May 2018 • Ming Li, Peilun Xiao, Ju Zhang
In traditional ELM and its improved versions suffer from the problems of outliers or noises due to overfitting and imbalance due to distribution.
no code implementations • 10 May 2018 • Ming Li, Peilun Xiao, Ju Zhang
In this paper, we propose a novel approach based on cost-sensitive ensemble weighted extreme learning machine; we call this approach AE1-WELM.
no code implementations • 26 May 2017 • Ming Li, Peilun Xiao, Ju Zhang
In this paper, we explore SPPIM-based text classification method, and the experiment reveals that the SPPIM method is equal to or even superior than SGNS method in text classification task on three international and standard text datasets, namely 20newsgroups, Reuters52 and WebKB.