1 code implementation • 2 Nov 2023 • Gongjin Lan, and Qiangqiang Lai, Bing Bai, Zirui Zhao, Qi Hao
A free-to-use executable file (Microsoft Windows) and open-source code are available at https://github. com/LadissonLai/SUSTech_VREngine for facilitating the development of VR systems in the automotive industry.
1 code implementation • 3 Aug 2023 • Yao Liu, Hang Shao, Bing Bai
This paper introduces a new Convolutional Neural Network (ConvNet) architecture inspired by a class of partial differential equations (PDEs) called quasi-linear hyperbolic systems.
no code implementations • ICCV 2023 • Fangfei Lin, Bing Bai, Yiwen Guo, Hao Chen, Yazhou Ren, Zenglin Xu
Multi-view hierarchical clustering (MCHC) plays a pivotal role in comprehending the structures within multi-view data, which hinges on the skillful interaction between hierarchical feature learning and comprehensive representation learning across multiple views.
1 code implementation • CVPR 2023 • Baowei Jiang, Bing Bai, Haozhe Lin, Yu Wang, Yuchen Guo, Lu Fang
Facial information is particularly sensitive in this regard.
no code implementations • ICCV 2023 • Haozhe Lin, Zequn Chen, Jinzhi Zhang, Bing Bai, Yu Wang, Ruqi Huang, Lu Fang
The CGG task capitalizes on the calibrated multiview videos of a dynamic scene, and targets at recovering semantic information (coordination, trajectories and relationships) of the presented objects in the form of spatio-temporal context graph in 4D space.
no code implementations • 12 Jul 2022 • Yingsong Huang, Bing Bai, Shengwei Zhao, Kun Bai, Fei Wang
The second issue refers to that models may output misleading predictions due to epistemic uncertainty and aleatoric uncertainty, thus existing methods that rely solely on the output probabilities may fail to distinguish confident samples.
no code implementations • 5 May 2022 • Fangfei Lin, Bing Bai, Kun Bai, Yazhou Ren, Peng Zhao, Zenglin Xu
Then, we embed the representations into a hyperbolic space and optimize the hyperbolic embeddings via a continuous relaxation of hierarchical clustering loss.
no code implementations • 11 Aug 2021 • Liuhui Ding, Dachuan Li, Bowen Liu, Wenxing Lan, Bing Bai, Qi Hao, Weipeng Cao, Ke Pei
Uncertainties in Deep Neural Network (DNN)-based perception and vehicle's motion pose challenges to the development of safe autonomous driving vehicles.
1 code implementation • The CVPR 2021 Workshop on Autonomous Driving (WAD) 2021 • Yueming Zhang, Xiaolin Song, Bing Bai, Tengfei Xing, Chao Liu, Xin Gao, Zhihui Wang, Yawei Wen, Haojin Liao, Guoshan Zhang, Pengfei Xu
In an autonomous driving system, it is essential to recognize vehicles, pedestrians and cyclists from images.
1 code implementation • 16 Jun 2021 • Yueming Zhang, Xiaolin Song, Bing Bai, Tengfei Xing, Chao Liu, Xin Gao, Zhihui Wang, Yawei Wen, Haojin Liao, Guoshan Zhang, Pengfei Xu
In an autonomous driving system, it is essential to recognize vehicles, pedestrians and cyclists from images.
Ranked #1 on Object Detection on Waymo Open Dataset
no code implementations • 15 Oct 2020 • Guanhua Zhang, Bing Bai, Jian Liang, Kun Bai, Conghui Zhu, Tiejun Zhao
Recent studies show that crowd-sourced Natural Language Inference (NLI) datasets may suffer from significant biases like annotation artifacts.
no code implementations • 11 Oct 2020 • Jian Liang, Yuren Cao, Shuang Li, Bing Bai, Hao Li, Fei Wang, Kun Bai
We further extend our method to a meta-learning framework to pursue more thorough domain-difference elimination.
no code implementations • 6 Sep 2020 • Chang Wang, Jian Liang, Mingkai Huang, Bing Bai, Kun Bai, Hao Li
We present HDP-VFL, the first hybrid differentially private (DP) framework for vertical federated learning (VFL) to demonstrate that it is possible to jointly learn a generalized linear model (GLM) from vertically partitioned data with only a negligible cost, w. r. t.
no code implementations • 25 Aug 2020 • Mingkai Huang, Hao Li, Bing Bai, Chang Wang, Kun Bai, Fei Wang
Federated Learning(FL) is a newly developed privacy-preserving machine learning paradigm to bridge data repositories without compromising data security and privacy.
no code implementations • 10 Jun 2020 • Bing Bai, Jian Liang, Guanhua Zhang, Hao Li, Kun Bai, Fei Wang
In this paper, we demonstrate that one root cause of this phenomenon is the combinatorial shortcuts, which means that, in addition to the highlighted parts, the attention weights themselves may carry extra information that could be utilized by downstream models after attention layers.
1 code implementation • 9 Jun 2020 • Jian Liang, Bing Bai, Yuren Cao, Kun Bai, Fei Wang
A popular way of performing model interpretation is Instance-wise Feature Selection (IFS), which provides an importance score of each feature representing the data samples to explain how the model generates the specific output.
1 code implementation • 27 May 2020 • Junqi Zhang, Bing Bai, Ye Lin, Jian Liang, Kun Bai, Fei Wang
In this paper, we report our recent practice at Tencent for user modeling based on mobile app usage.
1 code implementation • ACL 2020 • Guanhua Zhang, Bing Bai, Junqi Zhang, Kun Bai, Conghui Zhu, Tiejun Zhao
In this paper, we formalize the unintended biases in text classification datasets as a kind of selection bias from the non-discrimination distribution to the discrimination distribution.
no code implementations • 7 Apr 2020 • Bing Bai, Guanhua Zhang, Ye Lin, Hao Li, Kun Bai, Bo Luo
Recurrent Neural Network (RNN)-based sequential recommendation is a popular approach that utilizes users' recent browsing history to predict future items.
no code implementations • 27 Feb 2020 • Christopher Malon, Bing Bai
As a first instantiation of this framework, we train a pointer-generator network to predict followup questions based on the question and partial information.
no code implementations • 10 Sep 2019 • Guanhua Zhang, Bing Bai, Junqi Zhang, Kun Bai, Conghui Zhu, Tiejun Zhao
This irregularity makes the evaluation results over-estimated and affects models' generalization ability.
2 code implementations • ACL 2019 • Guanhua Zhang, Bing Bai, Jian Liang, Kun Bai, Shiyu Chang, Mo Yu, Conghui Zhu, Tiejun Zhao
Natural Language Sentence Matching (NLSM) has gained substantial attention from both academics and the industry, and rich public datasets contribute a lot to this process.
no code implementations • NeurIPS 2012 • Siddharth Gopal, Yiming Yang, Bing Bai, Alexandru Niculescu-Mizil
A challenging problem in hierarchical classification is to leverage the hierarchical relations among classes for improving classification performance.
no code implementations • NeurIPS 2009 • Bing Bai, Jason Weston, David Grangier, Ronan Collobert, Kunihiko Sadamasa, Yanjun Qi, Corinna Cortes, Mehryar Mohri
We present a class of nonlinear (polynomial) models that are discriminatively trained to directly map from the word content in a query-document or document-document pair to a ranking score.