no code implementations • 25 Apr 2023 • Peiqi Wang, Yingcheng Liu, Ching-Yun Ko, William M. Wells, Seth Berkowitz, Steven Horng, Polina Golland
Self-supervised representation learning on image-text data facilitates crucial medical applications, such as image classification, visual grounding, and cross-modal retrieval.
no code implementations • 6 Oct 2022 • Ching-Yun Ko, Pin-Yu Chen, Jeet Mohapatra, Payel Das, Luca Daniel
Given a pretrained model, the representations of data synthesized from the Gaussian mixture are used to compare with our reference to infer the quality.
1 code implementation • 30 Jun 2022 • Yanwei Wang, Ching-Yun Ko, Pulkit Agrawal
One powerful paradigm in visual navigation is to predict actions from observations directly.
no code implementations • 8 Dec 2021 • Ching-Yun Ko, Jeet Mohapatra, Sijia Liu, Pin-Yu Chen, Luca Daniel, Lily Weng
With the integrated framework, we achieve up to 6\% improvement on the standard accuracy and 17\% improvement on the robust accuracy.
no code implementations • NeurIPS 2020 • Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei Weng, Pin-Yu Chen, Sijia Liu, Luca Daniel
We also provide a framework that generalizes the calculation for certification using higher-order information.
no code implementations • 2 Mar 2020 • Jeet Mohapatra, Ching-Yun Ko, Tsui-Wei, Weng, Sijia Liu, Pin-Yu Chen, Luca Daniel
The fragility of modern machine learning models has drawn a considerable amount of attention from both academia and the public.
no code implementations • 28 Feb 2020 • Rui Lin, Ching-Yun Ko, Zhuolun He, Cong Chen, Yuan Cheng, Hao Yu, Graziano Chesi, Ngai Wong
The emerging edge computing has promoted immense interests in compacting a neural network without sacrificing much accuracy.
1 code implementation • 2 Dec 2019 • Zhaoyang Lyu, Ching-Yun Ko, Zhifeng Kong, Ngai Wong, Dahua Lin, Luca Daniel
We draw inspiration from such work and further demonstrate the optimality of deterministic CROWN (Zhang et al. 2018) solutions in a given linear programming problem under mild constraints.
2 code implementations • 17 May 2019 • Ching-Yun Ko, Zhaoyang Lyu, Tsui-Wei Weng, Luca Daniel, Ngai Wong, Dahua Lin
The vulnerability to adversarial attacks has been a critical issue for deep neural networks.
no code implementations • 17 May 2019 • Ching-Yun Ko, Rui Lin, Shu Li, Ngai Wong
Popular crowdsourcing techniques mostly focus on evaluating workers' labeling quality before adjusting their weights during label aggregation.
no code implementations • 12 Nov 2018 • Cong Chen, Kim Batselier, Ching-Yun Ko, Ngai Wong
This work presents the matrix product operator RBM (MPORBM) that utilizes a tensor network generalization of Mv/TvRBM, preserves input formats in both the visible and hidden layers, and results in higher expressive power.
no code implementations • 9 Nov 2018 • Ching-Yun Ko, Cong Chen, Yuke Zhang, Kim Batselier, Ngai Wong
Sum-product networks (SPNs) represent an emerging class of neural networks with clear probabilistic semantics and superior inference speed over graphical models.
1 code implementation • 17 Apr 2018 • Ching-Yun Ko, Kim Batselier, Wenjian Yu, Ngai Wong
We propose a new tensor completion method based on tensor trains.
no code implementations • 17 Apr 2018 • Cong Chen, Kim Batselier, Ching-Yun Ko, Ngai Wong
There has been growing interest in extending traditional vector-based machine learning techniques to their tensor forms.