no code implementations • 10 Apr 2024 • Chenyang An, Zhibo Chen, Qihao Ye, Emily First, Letian Peng, Jiayun Zhang, Zihan Wang, Sorin Lerner, Jingbo Shang
Recent advances in Automated Theorem Proving have shown the effectiveness of leveraging a (large) language model that generates tactics (i. e. proof steps) to search through proof states.
no code implementations • 12 Nov 2023 • Xiyuan Zhang, Xiaohan Fu, Diyan Teng, chengyu dong, Keerthivasan Vijayakumar, Jiayun Zhang, Ranak Roy Chowdhury, Junsheng Han, Dezhi Hong, Rashmi Kulkarni, Jingbo Shang, Rajesh Gupta
By obviating the need for ground truth clean data, our method offers a practical denoising solution for real-world applications.
1 code implementation • 1 Jan 2023 • Jiayun Zhang, Xiyuan Zhang, Xinyang Zhang, Dezhi Hong, Rajesh K. Gupta, Jingbo Shang
Traditional federated classification methods, even those designed for non-IID clients, assume that each client annotates its local data with respect to the same universal class set.
no code implementations • 1 Jan 2023 • Xiyuan Zhang, Ranak Roy Chowdhury, Jiayun Zhang, Dezhi Hong, Rajesh K. Gupta, Jingbo Shang
In this paper, we propose SHARE, a HAR framework that takes into account shared structures of label names for different activities.
1 code implementation • 24 Jun 2020 • Huiying Li, Shawn Shan, Emily Wenger, Jiayun Zhang, Hai-Tao Zheng, Ben Y. Zhao
In particular, query-based black-box attacks do not require knowledge of the deep learning model, but can compute adversarial examples over the network by submitting queries and inspecting returns.
1 code implementation • 19 Feb 2020 • Shawn Shan, Emily Wenger, Jiayun Zhang, Huiying Li, Hai-Tao Zheng, Ben Y. Zhao
In this paper, we propose Fawkes, a system that helps individuals inoculate their images against unauthorized facial recognition models.
no code implementations • 24 Sep 2019 • Fanrong Li, Zitao Mo, Peisong Wang, Zejian Liu, Jiayun Zhang, Gang Li, Qinghao Hu, Xiangyu He, Cong Leng, Yang Zhang, Jian Cheng
As a case study, we evaluate our object detection system on a real-world surveillance video with input size of 512x512, and it turns out that the system can achieve an inference speed of 18 fps at the cost of 6. 9W (with display) with an mAP of 66. 4 verified on the PASCAL VOC 2012 dataset.