no code implementations • 28 Feb 2024 • Jian Liu, Sipeng Zhang, Chuixin Kong, Wenyuan Zhang, Yuhang Wu, Yikang Ding, Borun Xu, Ruibo Ming, Donglai Wei, Xianming Liu
This technical report presents our solution, "occTransformer" for the 3D occupancy prediction track in the autonomous driving challenge at CVPR 2023.
1 code implementation • 25 Feb 2024 • Ruibin Yuan, Hanfeng Lin, Yi Wang, Zeyue Tian, Shangda Wu, Tianhao Shen, Ge Zhang, Yuhang Wu, Cong Liu, Ziya Zhou, Ziyang Ma, Liumeng Xue, Ziyu Wang, Qin Liu, Tianyu Zheng, Yizhi Li, Yinghao Ma, Yiming Liang, Xiaowei Chi, Ruibo Liu, Zili Wang, Pengfei Li, Jingcheng Wu, Chenghua Lin, Qifeng Liu, Tao Jiang, Wenhao Huang, Wenhu Chen, Emmanouil Benetos, Jie Fu, Gus Xia, Roger Dannenberg, Wei Xue, Shiyin Kang, Yike Guo
It is based on continual pre-training and finetuning LLaMA2 on a text-compatible music representation, ABC notation, and the music is treated as a second language.
no code implementations • 29 Jan 2024 • Jiaqi Wang, Yuzhong Chen, Yuhang Wu, Mahashweta Das, Hao Yang, Fenglong Ma
Subsequently, we design a precise personalized model distribution strategy to allow clients to obtain the most suitable model from the server side.
1 code implementation • 20 Nov 2023 • Jiahao Yu, Yuhang Wu, Dong Shu, Mingyu Jin, Xinyu Xing
In the rapidly evolving landscape of artificial intelligence, ChatGPT has been widely used in various applications.
no code implementations • 3 Nov 2023 • Yuhang Wu, Jinghai He, Zeyu Zheng
Utilizing covariate information has been a powerful approach to improve the efficiency and accuracy for causal inference, which support massive amount of randomized experiments run on data-driven enterprises.
no code implementations • 8 Apr 2023 • Yuhang Wu, Zeyu Zheng, Tingyu Zhu
The BAICS problem aims at correctly identify, with high confidence, the arm with the largest expected reward from all arms that satisfy subpopulation constraints.
no code implementations • 2 Dec 2022 • Xiaoting Li, Yuhang Wu, Vineeth Rakesh, Yusan Lin, Hao Yang, Fei Wang
Graph neural networks have achieved significant success in representation learning.
no code implementations • 22 Oct 2022 • Henry Lam, Kaizheng Wang, Yuhang Wu, Yichen Zhang
We study the problem of multi-task non-smooth optimization that arises ubiquitously in statistical learning, decision-making and risk management.
no code implementations • 13 Jan 2022 • Lan Wang, Yusan Lin, Yuhang Wu, Huiyuan Chen, Fei Wang, Hao Yang
Today's cyber-world is vastly multivariate.
no code implementations • 22 Dec 2021 • Yuhang Wu, Tengteng Huang, Haotian Yao, Chi Zhang, Yuanjie Shao, Chuchu Han, Changxin Gao, Nong Sang
First, we present a Domain-Specific Contrastive Learning (DSCL) mechanism to fully explore intradomain information by comparing samples only from the same domain.
Contrastive Learning Domain Adaptive Person Re-Identification +2
no code implementations • 15 Aug 2021 • Yuhang Wu, Mengting Gu, Lan Wang, Yusan Lin, Fei Wang, Hao Yang
Modeling inter-dependencies between time-series is the key to achieve high performance in anomaly detection for multivariate time-series data.
no code implementations • ICCV 2021 • Ahmed Abusnaina, Yuhang Wu, Sunpreet Arora, Yizhen Wang, Fei Wang, Hao Yang, David Mohaisen
We present the first graph-based adversarial detection method that constructs a Latent Neighborhood Graph (LNG) around an input example to determine if the input example is adversarial.
no code implementations • 31 Dec 2020 • Yuhang Wu, Sunpreet S. Arora, Yanhong Wu, Hao Yang
Adversarial examples are input examples that are specifically crafted to deceive machine learning classifiers.
no code implementations • SEMEVAL 2020 • Junyi Li, Yuhang Wu, Bin Wang, Haiyan Ding
Our methods achieved a F1 score of 0. 85 in subtask A.
no code implementations • SEMEVAL 2020 • Yuhang Wu, Hao Wu
This paper describes our system in subtask A of SemEval 2020 Shared Task 4.
1 code implementation • 5 Jun 2020 • Aravind Sankar, Yanhong Wu, Yuhang Wu, Wei zhang, Hao Yang, Hari Sundaram
We study the problem of making item recommendations to ephemeral groups, which comprise users with limited or no historical activities together.
no code implementations • 24 Mar 2020 • Dinh-Luan Nguyen, Sunpreet S. Arora, Yuhang Wu, Hao Yang
While feasible, digital attacks have limited applicability in attacking deployed systems, including face recognition systems, where an adversary typically has access to the input and not the transmission channel.
no code implementations • WS 2019 • Junyi Li, Xiaobing Zhou, Yuhang Wu, Bin Wang
We participated in the BioNLP 2019 Open Shared Tasks: binary relation extraction of SeeDev task.
no code implementations • 12 Mar 2019 • Yuhang Wu, Ioannis A. Kakadiaris
The compact face representation is not sensitive to the number of patches that are used to construct the facial template and is more suitable for incorporating the information from different view angles for image-set based face recognition.
no code implementations • 17 Mar 2018 • Yuhang Wu, Le Anh Vu Ha, Xiang Xu, Ioannis A. Kakadiaris
The method relies on Convolutional Point-set Representation (CPR), a carefully designed matrix representation to summarize different layers of information encoded in the set of detected points in the annotated image.
no code implementations • 2 Sep 2017 • Yuhang Wu, Ioannis A. Kakadiaris
The visual clues extracted from the fiducial points, non-fiducial points, and facial contour are jointly employed to verify the hypotheses.
no code implementations • 7 Apr 2017 • Yuhang Wu, Shishir K. Shah, Ioannis A. Kakadiaris
Facial landmark localization is a fundamental module for pose-invariant face recognition.