no code implementations • 29 May 2024 • Dingkang Yang, Jinjie Wei, Dongling Xiao, Shunli Wang, Tong Wu, Gang Li, Mingcheng Li, Shuaibing Wang, Jiawei Chen, Yue Jiang, Qingyao Xu, Ke Li, Peng Zhai, Lihua Zhang
In the parameter-efficient secondary SFT phase, a mixture of universal-specific experts strategy is presented to resolve the competency conflict between medical generalist and pediatric expertise mastery.
no code implementations • 22 May 2024 • Ying Ma, Owen Burns, Mingqiu Wang, Gang Li, Nan Du, Laurent El Shafey, Liqiang Wang, Izhak Shafran, Hagen Soltau
To alleviate the distributional mismatch issue in general self-supervised RL (SSRL), in our supervised learning (SL) stage, the agent selects actions based on the policy network and learns from generated labels; this self-generation of labels is the intuition behind the name self-supervised.
1 code implementation • 14 May 2024 • Dasith de Silva Edirimuni, Xuequan Lu, Gang Li, Lei Wei, Antonio Robles-Kelly, Hongdong Li
Point cloud filtering is a fundamental 3D vision task, which aims to remove noise while recovering the underlying clean surfaces.
no code implementations • 3 May 2024 • Chengyang Zhang, Weiming Li, Gang Li, Huina Song, Zhaohui Song, Xueqian Wang, Antonio Plaza
Detection of changes in heterogeneous remote sensing images is vital, especially in response to emergencies like earthquakes and floods.
no code implementations • 1 May 2024 • Shiva Raj Pokhrel, Naman Yash, Jonathan Kua, Gang Li, Lei Pan
Quantum Federated Learning (QFL) is an emerging concept that aims to unfold federated learning (FL) over quantum networks, enabling collaborative quantum model training along with local data privacy.
no code implementations • 3 Apr 2024 • Jiatong Li, Gang Li, Nan Su Su Win, Ling Lin
The results illustrate the method's efficacy in detecting and identifying various heterogeneous body types, depths, and thicknesses.
no code implementations • 29 Mar 2024 • Guanhua Ding, Zexi Ye, Zhen Zhong, Gang Li, David Shao
In our experiments, the SMART pruner consistently demonstrated its superiority over existing pruning methods across a wide range of tasks and models on block and output channel pruning.
1 code implementation • 28 Feb 2024 • Ziying Pan, Kun Wang, Gang Li, Feihong He, Xiwang Li, Yongxuan Lai
The class-conditional image generation based on diffusion models is renowned for generating high-quality and diverse images.
no code implementations • 28 Jan 2024 • Feihong He, Gang Li, Mengyuan Zhang, Leilei Yan, Lingyu Si, Fanzhang Li
In the decoder, we further modulate features from the dual streams based on a given content image and the corresponding style text prompt for precise style transfer.
no code implementations • 11 Jan 2024 • Seung Hyun Lee, Yinxiao Li, Junjie Ke, Innfarn Yoo, Han Zhang, Jiahui Yu, Qifei Wang, Fei Deng, Glenn Entis, Junfeng He, Gang Li, Sangpil Kim, Irfan Essa, Feng Yang
Additionally, Parrot employs a joint optimization approach for the T2I model and the prompt expansion network, facilitating the generation of quality-aware text prompts, thus further enhancing the final image quality.
1 code implementation • 1 Jan 2024 • Michalis Pistos, Gang Li, Weili Lin, Dinggang Shen, Islem Rekik
The three key innovations of FedGmTE-Net++ are: (i) presenting the first federated learning framework specifically designed for brain multi-trajectory evolution prediction in a data-scarce environment, (ii) incorporating an auxiliary regularizer in the local objective function to exploit all the longitudinal brain connectivity within the evolution trajectory and maximize data utilization, (iii) introducing a two-step imputation process, comprising a preliminary KNN-based precompletion followed by an imputation refinement step that employs regressors to improve similarity scores and refine imputations.
no code implementations • 15 Dec 2023 • Peizhao Li, Junfeng He, Gang Li, Rachit Bhargava, Shaolei Shen, Nachiappan Valliappan, Youwei Liang, Hongxiang Gu, Venky Ramachandran, Golnaz Farhadi, Yang Li, Kai J Kohlhoff, Vidhya Navalpakkam
Such a model would enable predicting subjective feedback such as overall satisfaction or aesthetic quality ratings, along with the underlying human attention or interaction heatmaps and viewing order, enabling designers and content-creation models to optimize their creation for human-centric improvements.
1 code implementation • 15 Dec 2023 • Youwei Liang, Junfeng He, Gang Li, Peizhao Li, Arseniy Klimovskiy, Nicholas Carolan, Jiao Sun, Jordi Pont-Tuset, Sarah Young, Feng Yang, Junjie Ke, Krishnamurthy Dj Dvijotham, Katie Collins, Yiwen Luo, Yang Li, Kai J Kohlhoff, Deepak Ramachandran, Vidhya Navalpakkam
We show that the predicted rich human feedback can be leveraged to improve image generation, for example, by selecting high-quality training data to finetune and improve the generative models, or by creating masks with predicted heatmaps to inpaint the problematic regions.
no code implementations • 10 Nov 2023 • Zhengliang Liu, Hanqi Jiang, Tianyang Zhong, Zihao Wu, Chong Ma, Yiwei Li, Xiaowei Yu, Yutong Zhang, Yi Pan, Peng Shu, Yanjun Lyu, Lu Zhang, Junjie Yao, Peixin Dong, Chao Cao, Zhenxiang Xiao, Jiaqi Wang, Huan Zhao, Shaochen Xu, Yaonai Wei, Jingyuan Chen, Haixing Dai, Peilong Wang, Hao He, Zewei Wang, Xinyu Wang, Xu Zhang, Lin Zhao, Yiheng Liu, Kai Zhang, Liheng Yan, Lichao Sun, Jun Liu, Ning Qiang, Bao Ge, Xiaoyan Cai, Shijie Zhao, Xintao Hu, Yixuan Yuan, Gang Li, Shu Zhang, Xin Zhang, Xi Jiang, Tuo Zhang, Dinggang Shen, Quanzheng Li, Wei Liu, Xiang Li, Dajiang Zhu, Tianming Liu
GPT-4V represents a breakthrough in artificial general intelligence (AGI) for computer vision, with applications in the biomedical domain.
no code implementations • 18 Oct 2023 • Jianzhi Xv, Gang Li, Tianbao Yang
While deep AUC maximization (DAM) has shown remarkable success on imbalanced medical tasks, e. g., chest X-rays classification and skin lesions classification, it could suffer from severe overfitting when applied to small datasets due to its aggressive nature of pushing prediction scores of positive data away from that of negative data.
no code implementations • 16 Oct 2023 • Junpeng Tan, Xin Zhang, Yao Lv, Xiangmin Xu, Gang Li
Finally, the experimental results on real-world fetal brain MRI stacks demonstrate the state-of-the-art performance of our method.
no code implementations • 16 Oct 2023 • Lihui Xue, Zhihao Wang, Xueqian Wang, Gang Li
In addition, our method reduces more than 60% memory costs of the subsequent pixel-level CD processing stage.
no code implementations • 12 Oct 2023 • Tao Li, Gang Li, Zhiwei Deng, Bryan Wang, Yang Li
To perform a task, recent works often require a model to learn from trace examples of the task via either supervised learning or few/many-shot prompting.
1 code implementation • 10 Oct 2023 • Forrest Huang, Gang Li, Tao Li, Yang Li
Macros are building block tasks of our everyday smartphone activity (e. g., "login", or "booking a flight").
no code implementations • 5 Oct 2023 • Feihong He, Gang Li, Lingyu Si, Leilei Yan, Fanzhang Li, Fuchun Sun
In particular, our method achieves 97. 07% and 90. 88% on 5-way 5-shot and 5-way 1-shot tasks of miniImageNet, which surpasses the state-of-the-art results with accuracy of 7. 27% and 8. 72%, respectively.
no code implementations • 15 Sep 2023 • Feihong He, Gang Li, Lingyu Si, Leilei Yan, Shimeng Hou, Hongwei Dong, Fanzhang Li
Image cartoonization has attracted significant interest in the field of image generation.
no code implementations • 12 Jul 2023 • Zhuowen Yin, Xinyao Ding, Xin Zhang, Zhengwang Wu, Li Wang, Xiangmin Xu, Gang Li
Specifically, we propose a Siamese verification framework to extend the scarce data, and an unsupervised compressor to alleviate data imbalance by extracting key features.
no code implementations • 30 Jun 2023 • Shanika I Nanayakkara, Shiva Raj Pokhrel, Gang Li
By incorporating unbiased weights into the model, the proposed approach effectively addresses quality-aware aggregation under the heterogeneity of the participating clients and the FL environment.
no code implementations • 27 Jun 2023 • Dev Gurung, Shiva Raj Pokhrel, Gang Li
Quantum Federated Learning (QFL) has gained significant attention due to quantum computing and machine learning advancements.
1 code implementation • 20 Jun 2023 • Dev Gurung, Shiva Raj Pokhrel, Gang Li
To this end, we develop a decentralized and trustworthy quantum federated learning (QFL) framework.
no code implementations • 8 Jun 2023 • Xiang Li, Lu Zhang, Zihao Wu, Zhengliang Liu, Lin Zhao, Yixuan Yuan, Jun Liu, Gang Li, Dajiang Zhu, Pingkun Yan, Quanzheng Li, Wei Liu, Tianming Liu, Dinggang Shen
In this review, we explore the potential applications of Artificial General Intelligence (AGI) models in healthcare, focusing on foundational Large Language Models (LLMs), Large Vision Models, and Large Multimodal Models.
1 code implementation • 5 Jun 2023 • Zhuoning Yuan, Dixian Zhu, Zi-Hao Qiu, Gang Li, Xuanhui Wang, Tianbao Yang
This paper introduces the award-winning deep learning (DL) library called LibAUC for implementing state-of-the-art algorithms towards optimizing a family of risk functions named X-risks.
2 code implementations • 29 May 2023 • Xi Chen, Josip Djolonga, Piotr Padlewski, Basil Mustafa, Soravit Changpinyo, Jialin Wu, Carlos Riquelme Ruiz, Sebastian Goodman, Xiao Wang, Yi Tay, Siamak Shakeri, Mostafa Dehghani, Daniel Salz, Mario Lucic, Michael Tschannen, Arsha Nagrani, Hexiang Hu, Mandar Joshi, Bo Pang, Ceslee Montgomery, Paulina Pietrzyk, Marvin Ritter, AJ Piergiovanni, Matthias Minderer, Filip Pavetic, Austin Waters, Gang Li, Ibrahim Alabdulmohsin, Lucas Beyer, Julien Amelot, Kenton Lee, Andreas Peter Steiner, Yang Li, Daniel Keysers, Anurag Arnab, Yuanzhong Xu, Keran Rong, Alexander Kolesnikov, Mojtaba Seyedhosseini, Anelia Angelova, Xiaohua Zhai, Neil Houlsby, Radu Soricut
We present the training recipe and results of scaling up PaLI-X, a multilingual vision and language model, both in terms of size of the components and the breadth of its training task mixture.
Ranked #1 on Fine-Grained Image Recognition on OVEN
no code implementations • 23 May 2023 • Yuantong Zhang, Baoxin Teng, Daiqin Yang, Zhenzhong Chen, Haichuan Ma, Gang Li, Wenpeng Ding
Low-light image enhancement (LLIE) aims to improve the illuminance of images due to insufficient light exposure.
no code implementations • 20 May 2023 • Bing Liu, Wei Luo, Gang Li, Jing Huang, Bo Yang
As deep learning gains popularity in modelling dynamical systems, we expose an underappreciated misunderstanding relevant to modelling dynamics on networks.
1 code implementation • 26 Apr 2023 • Dev Gurung, Shiva Raj Pokhrel, Gang Li
We design a model of Post Quantum Cryptography (PQC) Quantum Federated Learning (QFL).
no code implementations • 18 Apr 2023 • Zihao Wu, Lu Zhang, Chao Cao, Xiaowei Yu, Haixing Dai, Chong Ma, Zhengliang Liu, Lin Zhao, Gang Li, Wei Liu, Quanzheng Li, Dinggang Shen, Xiang Li, Dajiang Zhu, Tianming Liu
To this end, in this study, we evaluate the performance of ChatGPT/GPT-4 on a radiology NLI task and compare it to other models fine-tuned specifically on task-related data samples.
1 code implementation • CVPR 2023 • Dasith de Silva Edirimuni, Xuequan Lu, Zhiwen Shao, Gang Li, Antonio Robles-Kelly, Ying He
Consequently, a fundamental 3D vision task is the removal of noise, known as point cloud filtering or denoising.
no code implementations • 3 Apr 2023 • Chengxi Li, Gang Li, Zhuoyue Wang, Xueqian Wang, Pramod K. Varshney
For this problem, an unsupervised change detection method has been proposed recently based on the image translation technique of Cycle-Consistent Adversarial Networks (CycleGANs), where one image is translated from its original modality to the modality of the other image so that the difference map can be obtained by performing arithmetical subtraction.
no code implementations • 30 Mar 2023 • Weiming Li, Xueqian Wang, Gang Li
Change detection (CD) in heterogeneous remote sensing images is a practical and challenging issue for real-life emergencies.
no code implementations • 30 Mar 2023 • Minglei Lu, Ali Mohammadi, Zhaoxu Meng, Xuhui Meng, Gang Li, Zhen Li
After an offline training, the DNO model can act as surrogate of physics-based FEA to predict the transient mechanical response in terms of reaction force and stress distribution of the IPCs to various strain loads in one second at an accuracy of 98%.
1 code implementation • 13 Mar 2023 • Xuesheng Bian, Cheng Wang, Shuting Chen, Weiquan Liu, Sen Xu, Jinxin Zhu, Rugang Wang, Zexin Chen, Min Huang, Gang Li
Performing ATP bioluminescence causes cell lysis of organoids, so it is impossible to observe organoids' long-term viability changes after medication continually.
1 code implementation • 26 Feb 2023 • Rongxin Xu, Shiva Raj Pokhrel, Qiujun Lan, Gang Li
We aim to employ Federated Learning (FL) and prominent features of blockchain into MEC architecture such as connected autonomous vehicles to enable complete decentralization, immutability, and rewarding mechanisms simultaneously.
1 code implementation • 1 Feb 2023 • Zeyu Zhu, Fanrong Li, Zitao Mo, Qinghao Hu, Gang Li, Zejian Liu, Xiaoyao Liang, Jian Cheng
Through an in-depth analysis of the topology of GNNs, we observe that the topology of the graph leads to significant differences between nodes, and most of the nodes in a graph appear to have a small aggregation value.
no code implementations • 27 Jan 2023 • Chin-Yi Cheng, Forrest Huang, Gang Li, Yang Li
Layout design is an important task in various design fields, including user interface, document, and graphic design.
2 code implementations • 30 Dec 2022 • Yang Cao, Ye Zhu, Kai Ming Ting, Flora D. Salim, Hong Xian Li, Luxing Yang, Gang Li
Detecting abrupt changes in data distribution is one of the most significant tasks in streaming data analysis.
no code implementations • 25 Nov 2022 • Gang Li, Heliang Zheng, Chaoyue Wang, Chang Li, Changwen Zheng, DaCheng Tao
Text-guided diffusion models have shown superior performance in image/video generation and editing.
no code implementations • 14 Oct 2022 • Weiming Li, Lihui Xue, Xueqian Wang, Gang Li
For the task of change detection (CD) in remote sensing images, deep convolution neural networks (CNNs)-based methods have recently aggregated transformer modules to improve the capability of global feature extraction.
no code implementations • 29 Sep 2022 • Tao Li, Gang Li, Jingjie Zheng, Purple Wang, Yang Li
To investigate the problem, we create a new dataset that consists of 77, 820 sequences of human user-agent interaction on mobile interfaces in which 20% involves multiple rounds of interactions.
no code implementations • 29 Sep 2022 • Gang Li, Yang Li
Specifically, we enhance a vision-language model that only takes the screenshot of the UI and a region of interest on the screen -- the focus -- as the input.
1 code implementation • 18 Sep 2022 • Bryan Wang, Gang Li, Yang Li
This paper investigates the feasibility of enabling versatile conversational interactions with mobile UIs using a single LLM.
1 code implementation • 14 Aug 2022 • Dasith de Silva Edirimuni, Xuequan Lu, Gang Li, Antonio Robles-Kelly
Existing methods usually perform normal estimation and filtering separately and often show sensitivity to noise and/or inability to preserve sharp geometric features such as corners and edges.
no code implementations • 9 Aug 2022 • Yunzhi Huang, Sahar Ahmad, Luyi Han, Shuai Wang, Zhengwang Wu, Weili Lin, Gang Li, Li Wang, Pew-Thian Yap
In this paper, we propose a deep learning framework to predict missing scans from acquired scans, catering to longitudinal infant studies.
1 code implementation • 3 Aug 2022 • Qinghao Hu, Gang Li, Qiman Wu, Jian Cheng
In this paper, we propose the PArallel Low-precision Quantization (PalQuant) method that approximates high-precision computations via learning parallel low-precision representations from scratch.
no code implementations • 18 Jul 2022 • Wei Jiang, Gang Li, Yibo Wang, Lijun Zhang, Tianbao Yang
The key issue is to track and estimate a sequence of $\mathbf g(\mathbf{w})=(g_1(\mathbf{w}), \ldots, g_m(\mathbf{w}))$ across iterations, where $\mathbf g(\mathbf{w})$ has $m$ blocks and it is only allowed to probe $\mathcal{O}(1)$ blocks to attain their stochastic values and Jacobians.
1 code implementation • 12 Jul 2022 • Gang Li, Xiang Li, Yujie Wang, Yichao Wu, Ding Liang, Shanshan Zhang
Specifically, we propose the Inverse NMS Clustering (INC) and Rank Matching (RM) to instantiate the dense supervision, without the widely used, conventional sparse pseudo labels.
no code implementations • 26 Jun 2022 • Rongxin Xu, Shiva Raj Pokhrel, Qiujun Lan, Gang Li
These impending challenges in the design philosophy of FL call for blockchain-based federated learning (BFL) due to the benefits of coupling FL and blockchain (e. g., democracy, incentive, and immutability).
Ranked #1 on Malicious Detection on MNIST
1 code implementation • 21 Jun 2022 • Gang Li, Heliang Zheng, Daqing Liu, Chaoyue Wang, Bing Su, Changwen Zheng
In this paper, we explore a potential visual analogue of words, i. e., semantic parts, and we integrate semantic information into the training process of MAE by proposing a Semantic-Guided Masking strategy.
no code implementations • 26 May 2022 • Lu Zhang, Xiaowei Yu, Yanjun Lyu, Zhengwang Wu, Haixing Dai, Lin Zhao, Li Wang, Gang Li, Tianming Liu, Dajiang Zhu
Our experimental results show that: 1) the learned embedding vectors can quantitatively encode the commonality and individuality of cortical folding patterns; 2) with the embeddings we can robustly infer the complicated many-to-many anatomical correspondences among different brains and 3) our model can be successfully transferred to new populations with very limited training samples.
1 code implementation • 5 Apr 2022 • Eldon Schoop, Xin Zhou, Gang Li, Zhourong Chen, Björn Hartmann, Yang Li
We use a deep learning based approach to predict whether a selected element in a mobile UI screenshot will be perceived by users as tappable, based on pixels only instead of view hierarchies required by previous work.
1 code implementation • 30 Mar 2022 • Gang Li, Xiang Li, Yujie Wang, Yichao Wu, Ding Liang, Shanshan Zhang
Specifically, for pseudo labeling, existing works only focus on the classification score yet fail to guarantee the localization precision of pseudo boxes; For consistency training, the widely adopted random-resize training only considers the label-level consistency but misses the feature-level one, which also plays an important role in ensuring the scale invariance.
no code implementations • 29 Mar 2022 • Guangwei Yu, Gang Li, Xingtong Si, Zhuoyuan Song
Ball mixing is a ball bearing production quality problem that is difficult to identify using traditional frequency domain analysis methods since it requires high frequency resolutions of the measurement signals and results in a long analyzing time.
no code implementations • 1 Mar 2022 • Dixian Zhu, Gang Li, Bokun Wang, Xiaodong Wu, Tianbao Yang
In this paper, we propose systematic and efficient gradient-based methods for both one-way and two-way partial AUC (pAUC) maximization that are applicable to deep learning.
1 code implementation • 28 Jan 2022 • Jie Zhang, Lei Zhang, Gang Li, Chao Wu
Adversarial examples are inputs for machine learning models that have been designed by attackers to cause the model to make mistakes.
1 code implementation • 11 Jan 2022 • Gang Li, Gilles Baechler, Manuel Tragut, Yang Li
The layout of a mobile screen is a critical data source for UI design research and semantic understanding of the screen.
2 code implementations • 24 Dec 2021 • Gang Li, Di Xu, Xing Cheng, Lingyu Si, Changwen Zheng
Although vision Transformers have achieved excellent performance as backbone models in many vision tasks, most of them intend to capture global relations of all tokens in an image or a window, which disrupts the inherent spatial and local correlations between patches in 2D structure.
no code implementations • 10 Dec 2021 • Yang Li, Gang Li, Xin Zhou, Mostafa Dehghani, Alexey Gritsenko
Our model consists of a multimodal Transformer encoder that jointly encodes UI images and structures, and performs UI object detection when the UI structures are absent in the input.
no code implementations • 9 Dec 2021 • Gang Li, Xiang Li, Yujie Wang, Shanshan Zhang, Yichao Wu, Ding Liang
Based on the two observations, we propose Rank Mimicking (RM) and Prediction-guided Feature Imitation (PFI) for distilling one-stage detectors, respectively.
no code implementations • 14 Oct 2021 • Forrest Huang, Gang Li, Xin Zhou, John F. Canny, Yang Li
The design process of user interfaces (UIs) often begins with articulating high-level design goals.
1 code implementation • 6 Oct 2021 • Alaa Bessadok, Ahmed Nebli, Mohamed Ali Mahjoub, Gang Li, Weili Lin, Dinggang Shen, Islem Rekik
To the best of our knowledge, this is the first teacher-student architecture tailored for brain graph multi-trajectory growth prediction that is based on few-shot learning and generalized to graph neural networks (GNNs).
no code implementations • 29 Sep 2021 • Yang Li, Gang Li, Xin Zhou, Mostafa Dehghani, Alexey A. Gritsenko
Our model consists of a multimodal Transformer encoder that jointly encodes UI images and structures, and performs UI object detection when the UI structures are absent in the input.
2 code implementations • 7 Aug 2021 • Bryan Wang, Gang Li, Xin Zhou, Zhourong Chen, Tovi Grossman, Yang Li
Mobile User Interface Summarization generates succinct language descriptions of mobile screens for conveying important contents and functionalities of the screen, which can be useful for many language-based application scenarios.
no code implementations • 7 Aug 2021 • Mingyuan Zhong, Gang Li, Peggy Chi, Yang Li
We present HelpViz, a tool for generating contextual visual mobile tutorials from text-based instructions that are abundant on the web.
no code implementations • CVPR 2021 • Qian Li, Zhichao Wang, Gang Li, Jun Pang, Guandong Xu
Sinkhorn divergence has become a very popular metric to compare probability distributions in optimal transport.
1 code implementation • NeurIPS 2021 • Yang Li, Si Si, Gang Li, Cho-Jui Hsieh, Samy Bengio
Attentional mechanisms are order-invariant.
no code implementations • 12 Mar 2021 • Erin Sheridan, Gang Li, Mamun Sarker, Shan Hao, Ki-Tae Eom, Chang-Beom Eom, Alexander Sinitskii, Patrick Irvin, Jeremy Levy
We investigate the optical response of graphene nanoribbons (GNRs) using the broadband nonlinear generation and detection capabilities of nanoscale junctions created at the LaAlO$_3$/SrTiO$_3$ interface.
Mesoscale and Nanoscale Physics Optics
no code implementations • 4 Mar 2021 • Zejian Liu, Gang Li, Jian Cheng
BERT is the most recent Transformer-based model that achieves state-of-the-art performance in various NLP tasks.
no code implementations • 17 Feb 2021 • Cuiying Pei, Suhua Jin, Peihao Huang, Anna Vymazalova, Lingling Gao, Yi Zhao, Weizheng Cao, Changhua Li, Peter Nemes-Incze, Yulin Chen, Hanyu Liu, Gang Li, Yanpeng Qi
Recently monolayer jacutingaite (Pt2HgSe3), a naturally occurring exfoliable mineral, discovered in Brazil in 2008, has been theoretically predicted as a candidate quantum spin Hall system with a 0. 5 eV band gap, while the bulk form is one of only a few known dual-topological insulators which may host different surface states protected by symmetries.
Band Gap Superconductivity Materials Science
no code implementations • 17 Feb 2021 • Mingyuan Zhong, Gang Li, Yang Li
Based on our experiments, Spacewalker allows designers to effectively search a large design space of a UI, using the language they are familiar with, and improve their design rapidly at a minimal cost.
1 code implementation • ICCV 2021 • Fanrong Li, Gang Li, Xiangyu He, Jian Cheng
In particular, dynamic dual gating can provide 59. 7% saving in computing of ResNet50 with 76. 41% top-1 accuracy on ImageNet, which has advanced the state-of-the-art.
no code implementations • 24 Dec 2020 • Chengxi Li, Gang Li, Pramod K. Varshney
In this paper, we investigate the problem of decentralized federated learning (DFL) in Internet of things (IoT) systems, where a number of IoT clients train models collectively for a common task without sharing their private training data in the absence of a central server.
no code implementations • 12 Oct 2020 • Xin Han, Ye Zhu, Kai Ming Ting, Gang Li
In this paper, we identify the root cause of this issue and show that the use of a data-dependent kernel (instead of distance or existing kernel) provides an effective means to address it.
1 code implementation • EMNLP 2020 • Yang Li, Gang Li, Luheng He, Jingjie Zheng, Hong Li, Zhiwei Guan
We propose widget captioning, a novel task for automatically generating language descriptions for UI elements from multimodal input including both the image and the structural representations of user interfaces.
1 code implementation • 6 Sep 2020 • Peirong Liu, Zhengwang Wu, Gang Li, Pew-Thian Yap, Dinggang Shen
Charting cortical growth trajectories is of paramount importance for understanding brain development.
no code implementations • 8 Jul 2020 • Gang Li, Jan Hannig
Since the mid-2000s, there has been a resurrection of interest in modern modifications of fiducial inference.
no code implementations • 4 Jul 2020 • Yue Sun, Kun Gao, Zhengwang Wu, Zhihao Lei, Ying WEI, Jun Ma, Xiaoping Yang, Xue Feng, Li Zhao, Trung Le Phan, Jitae Shin, Tao Zhong, Yu Zhang, Lequan Yu, Caizi Li, Ramesh Basnet, M. Omair Ahmad, M. N. S. Swamy, Wenao Ma, Qi Dou, Toan Duc Bui, Camilo Bermudez Noguera, Bennett Landman, Ian H. Gotlib, Kathryn L. Humphreys, Sarah Shultz, Longchuan Li, Sijie Niu, Weili Lin, Valerie Jewells, Gang Li, Dinggang Shen, Li Wang
Deep learning-based methods have achieved state-of-the-art performance; however, one of major limitations is that the learning-based methods may suffer from the multi-site issue, that is, the models trained on a dataset from one site may not be applicable to the datasets acquired from other sites with different imaging protocols/scanners.
1 code implementation • 19 May 2020 • Dongming Wei, Sahar Ahmad, Yunzhi Huang, Lei Ma, Zhengwang Wu, Gang Li, Li Wang, Qian Wang, Pew-Thian Yap, Dinggang Shen
Deformable image registration is fundamental to longitudinal and population analysis.
no code implementations • 8 Apr 2020 • Xiao Jiang, Gang Li, Yu Liu, Xiao-Ping Zhang, You He
To solve this problem, this paper presents a new homogeneous transformation model termed deep homogeneous feature fusion (DHFF) based on image style transfer (IST).
no code implementations • LREC 2020 • Izhak Shafran, Nan Du, Linh Tran, Amanda Perry, Lauren Keyes, Mark Knichel, Ashley Domin, Lei Huang, Yu-Hui Chen, Gang Li, Mingqiu Wang, Laurent El Shafey, Hagen Soltau, Justin S. Paul
We used this annotation scheme to label a corpus of about 6k clinical encounters.
1 code implementation • 13 Jan 2020 • Xingyu Zhou, Shuxian Du, Gang Li, Chengping Shen
To help analysts obtain the physics process information from the truth information of the samples, we develop a physics process analysis program, TopoAna, with C++, ROOT, and LaTeX.
High Energy Physics - Experiment
2 code implementations • 17 Dec 2019 • Gang Li, Jan Zrimec, Boyang Ji, Jun Geng, Johan Larsbrink, Aleksej Zelezniak, Jens Nielsen, Martin KM Engqvist
A challenge in developing machine learning regression models is that it is difficult to know whether maximal performance has been reached on a particular dataset, or whether further model improvement is possible.
no code implementations • 31 Oct 2019 • Ruibin Ma, Po-Hsuan Cameron Chen, Gang Li, Wei-Hung Weng, Angela Lin, Krishna Gadepalli, Yuannan Cai
However, manual classification for a huge number of reports on multiple tasks is labor-intensive.
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.
no code implementations • IJCNLP 2019 • Nan Du, Mingqiu Wang, Linh Tran, Gang Li, Izhak Shafran
Recently we proposed the Span Attribute Tagging (SAT) Model (Du et al., 2019) to infer clinical entities (e. g., symptoms) and their properties (e. g., duration).
no code implementations • NAACL 2019 • Ido Cohn, Itay Laish, Genady Beryozkin, Gang Li, Izhak Shafran, Idan Szpektor, Tzvika Hartman, Avinatan Hassidim, Yossi Matias
To this end, we define the task of audio de-ID, in which audio spans with entity mentions should be detected.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +5
no code implementations • 9 May 2019 • Di Zhao, Jiqiang Liu, Jialin Wang, Wenjia Niu, Endong Tong, Tong Chen, Gang Li
"Feint Attack" is simulated by the real attack inserted in the normal causal attack chain, and the addition of the real attack destroys the causal relationship of the original attack chain.
no code implementations • 11 Apr 2019 • Qian Zhang, Li Wang, Xiaopeng Zong, Weili Lin, Gang Li, Dinggang Shen
Skull stripping for brain MR images is a basic segmentation task.
no code implementations • 1 Apr 2019 • Fenqiang Zhao, Shunren Xia, Zhengwang Wu, Dingna Duan, Li Wang, Weili Lin, John H Gilmore, Dinggang Shen, Gang Li
In this paper, by leveraging the regular and consistent geometric structure of the resampled cortical surface mapped onto the spherical space, we propose a novel convolution filter analogous to the standard convolution on the image grid.
no code implementations • 17 Mar 2019 • Ido Cohn, Itay Laish, Genady Beryozkin, Gang Li, Izhak Shafran, Idan Szpektor, Tzvika Hartman, Avinatan Hassidim, Yossi Matias
To this end, we define the task of audio de-ID, in which audio spans with entity mentions should be detected.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +5
no code implementations • 6 Feb 2019 • Dongming Wei, Zhengwang Wu, Gang Li, Xiaohuan Cao, Dinggang Shen, Qian Wang
Thus, the two trajectories can act as a bridge to link the fixed and the moving images, and guide their registration.
no code implementations • ECCV 2018 • Qinghao Hu, Gang Li, Peisong Wang, Yifan Zhang, Jian Cheng
In this paper, we propose a novel semi-binary decomposition method which decomposes a matrix into two binary matrices and a diagonal matrix.
no code implementations • 18 Jul 2018 • Tong Chen, Wenjia Niu, Yingxiao Xiang, Xiaoxuan Bai, Jiqiang Liu, Zhen Han, Gang Li
In addition, we propose Gradient Band-based Adversarial Training, which trained with a single randomly choose dominant adversarial example without taking any modification, to realize the "1:N" attack immunity for generalized dominant adversarial examples.
no code implementations • 3 Feb 2018 • Jian Cheng, Peisong Wang, Gang Li, Qinghao Hu, Hanqing Lu
As for hardware implementation of deep neural networks, a batch of accelerators based on FPGA/ASIC have been proposed in recent years.
no code implementations • WS 2017 • Gang Li, Cathy Wu, K. Vijay-Shanker
Distant supervision has been applied to automatically generate labeled data for biomedical relation extraction.
1 code implementation • 15 Nov 2016 • Yuhang Lu, Youchuan Wan, Gang Li
Unsupervised evaluation of segmentation quality is a crucial step in image segmentation applications.
no code implementations • 28 Jul 2014 • Zhenqiu Liu, Gang Li
Therefore, it is natural to expect that L0 regularized regression performs better than LASSO.