no code implementations • ACL (ECNLP) 2021 • Ying Lin, Han Wang, Jiangning Chen, Tong Wang, Yue Liu, Heng Ji, Yang Liu, Premkumar Natarajan
We first build a cross-source heterogeneous knowledge graph from customer purchase history and product knowledge graph to jointly learn customer and product embeddings.
no code implementations • 11 May 2022 • Yue Liu, Xihong Yang, Sihang Zhou, Xinwang Liu
To solve this problem, we propose a Simple Contrastive Graph Clustering (SCGC) algorithm to improve the existing methods from the perspectives of network architecture, data augmentation, and objective function.
no code implementations • 4 Apr 2022 • Shengyuan Hu, Jack Goetz, Kshitiz Malik, Hongyuan Zhan, Zhe Liu, Yue Liu
Model compression is important in federated learning (FL) with large models to reduce communication cost.
no code implementations • 25 Feb 2022 • Yue Liu, Sihang Zhou, Xinwang Liu, Wenxuan Tu, Xihong Yang
Deep graph clustering, which aims to reveal the underlying graph structure and divide the nodes into different clusters without human annotations, is a fundamental yet challenging task.
2 code implementations • 29 Dec 2021 • Yue Liu, Wenxuan Tu, Sihang Zhou, Xinwang Liu, Linxuan Song, Xihong Yang, En Zhu
To address this issue, we propose a novel self-supervised deep graph clustering method termed Dual Correlation Reduction Network (DCRN) by reducing information correlation in a dual manner.
no code implementations • 24 Dec 2021 • Hong-Li Zeng, Yue Liu, Vito Dichio, Erik Aurell
We use Direct Coupling Analysis to determine epistatic interactions between loci of variability of the SARS-CoV-2 virus, segmenting genomes by month of sampling.
no code implementations • 9 Dec 2021 • Wenxuan Tu, Sihang Zhou, Yue Liu, Xinwang Liu
First, we entangle the attribute embedding and structure embedding by introducing a siamese network structure to share the parameters learned by both processes, which allows the network training to benefit from more abundant and diverse information.
2 code implementations • 2 Dec 2021 • Moein Sorkhei, Yue Liu, Hossein Azizpour, Edward Azavedo, Karin Dembrower, Dimitra Ntoula, Athanasios Zouzos, Fredrik Strand, Kevin Smith
Interval and large invasive breast cancers, which are associated with worse prognosis than other cancers, are usually detected at a late stage due to false negative assessments of screening mammograms.
1 code implementation • 15 Oct 2021 • Yue Liu, Philip K. Maini, Ruth E. Baker
In certain biological contexts, such as the plumage patterns of birds and stripes on certain species of fishes, pattern formation takes place behind a so-called "wave of competency".
no code implementations • 12 Oct 2021 • Pooja Sethi, Denis Savenkov, Forough Arabshahi, Jack Goetz, Micaela Tolliver, Nicolas Scheffer, Ilknur Kabul, Yue Liu, Ahmed Aly
Improving the quality of Natural Language Understanding (NLU) models, and more specifically, task-oriented semantic parsing models, in production is a cumbersome task.
no code implementations • 1 Oct 2021 • Yue Liu, Ethan X. Fang, Junwei Lu
Our proposed method aims to infer general ranking properties of the BTL model.
no code implementations • 7 Sep 2021 • Hong-Li Zeng, Yue Liu, Vito Dichio, Kaisa Thorell, Rickard Nordén, Erik Aurell
We compute the allele frequencies of the alpha (B. 1. 1. 7), beta (B. 1. 351) and delta (B. 167. 2) variants of SARS-CoV-2 from almost two million genome sequences on the GISAID repository.
no code implementations • 16 Aug 2021 • Sin Kit Lo, Yue Liu, Qinghua Lu, Chen Wang, Xiwei Xu, Hye-Young Paik, Liming Zhu
To enhance the accountability and fairness of federated learning systems, we present a blockchain-based trustworthy federated learning architecture.
no code implementations • NAACL 2021 • Mingyue Shang, Tong Wang, Mihail Eric, Jiangning Chen, Jiyang Wang, Matthew Welch, Tiantong Deng, Akshay Grewal, Han Wang, Yue Liu, Yang Liu, Dilek Hakkani-Tur
In recent years, incorporating external knowledge for response generation in open-domain conversation systems has attracted great interest.
no code implementations • NAACL 2021 • Tong Wang, Jiangning Chen, Mohsen Malmir, Shuyan Dong, Xin He, Han Wang, Chengwei Su, Yue Liu, Yang Liu
In dialog systems, the Natural Language Understanding (NLU) component typically makes the interpretation decision (including domain, intent and slots) for an utterance before the mentioned entities are resolved.
1 code implementation • 17 May 2021 • Jiawei Jiang, Shaoduo Gan, Yue Liu, Fanlin Wang, Gustavo Alonso, Ana Klimovic, Ankit Singla, Wentao Wu, Ce Zhang
The appeal of serverless (FaaS) has triggered a growing interest on how to use it in data-intensive applications such as ETL, query processing, or machine learning (ML).
no code implementations • 10 Apr 2021 • Yue Liu, Lixin Tian, Zhuyun Xie, Zaili Zhen, Huaping Sun
Considering the impact of price fluctuations of carbon emission right allowance, we investigate the operation of Chinese thermal power plant by modeling the decision-making with optimal stopping problem, which is established on the stochastic environment with carbon emission allowance price process simulated by geometric Brownian motion.
no code implementations • 6 Apr 2021 • Ying Lin, Han Wang, Jiangning Chen, Tong Wang, Yue Liu, Heng Ji, Yang Liu, Premkumar Natarajan
For example, with "add milk to my cart", a customer may refer to a certain organic product, while some customers may want to re-order products they regularly purchase.
no code implementations • 24 Mar 2021 • Wei Wei, Li Guan, Yue Liu, Hao Kang, Haoxiang Li, Ying Wu, Gang Hua
By the proposed physical regularization, our method can generate HDRs which are not only visually appealing but also physically plausible.
1 code implementation • 9 Mar 2021 • Yue Liu, Chakkrit Tantithamthavorn, Li Li, Yepang Liu
In this paper, we conducted a systematic literature review to search and analyze how deep learning approaches have been applied in the context of malware defenses in the Android environment.
no code implementations • 25 Feb 2021 • Zhuangyan Fang, Yue Liu, Zhi Geng, Shengyu Zhu, Yangbo He
We propose a local approach to identify whether a variable is a cause of a given target under the framework of causal graphical models of directed acyclic graphs (DAGs).
no code implementations • 7 Feb 2021 • Yue Liu, Ihor Korolov, Torben Hemke, Lena Bischoff, Gerrit Hübner, Julian Schulze, Thomas Mussenbrock
A two-dimensional fluid model is used to investigate the electron heating dynamics and the production of neutral species in a capacitively coupled radio-frequency micro atmospheric pressure helium plasma jet -- specifically the COST jet -- with a small oxygen admixture.
Plasma Physics
no code implementations • 21 Jan 2021 • Haotian Ye, Chuanlong Xie, Yue Liu, Zhenguo Li
One of the definitions of OOD accuracy is worst-domain accuracy.
no code implementations • 1 Jan 2021 • Zhuangyan Fang, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, Yangbo He
Despite several important advances in recent years, learning causal structures represented by directed acyclic graphs (DAGs) remains a challenging task in high dimensional settings when the graphs to be learned are not sparse.
no code implementations • 4 Dec 2020 • Panpan Zhou, Liyang Chen, Yue Liu, Ilya Sochnikov, Anthony T. Bollinger, Myung-Geun Han, Yimei Zhu, Xi He, Ivan Bozovic, Douglas Natelson
In the quest to understand high-temperature superconductivity in copper oxides, a vigorous debate has been focused on the pseudogap - a partial gap that opens over portions of the Fermi surface in the 'normal' state above the bulk critical temperature ($T_{c}$).
Superconductivity Mesoscale and Nanoscale Physics Strongly Correlated Electrons
no code implementations • 29 Nov 2020 • Yan He, Jifang Qiu, Chang Liu, Yue Liu, Jian Wu
The latest theoretical advances in the field of unlimited sampling framework (USF) show the potential to avoid clipping problems of analog-to-digital converters (ADC).
no code implementations • 14 Sep 2020 • Yue Liu, Alex Colburn, Mehlika Inanici
The proposed DNN model can faithfully predict high-quality annual panoramic luminance maps from one of the three options within 30 minutes training time: a) point-in-time luminance imagery spanning 5% of the year, when evenly distributed during daylight hours, b) one-month hourly imagery generated or collected continuously during daylight hours around the equinoxes (8% of the year); or c) 9 days of hourly data collected around the spring equinox, summer and winter solstices (2. 5% of the year) all suffice to predict the luminance maps for the rest of the year.
no code implementations • 6 Sep 2020 • Weishan Zhang, Qinghua Lu, Qiuyu Yu, Zhaotong Li, Yue Liu, Sin Kit Lo, Shiping Chen, Xiwei Xu, Liming Zhu
Therefore, in this paper, we present a platform architecture of blockchain-based federated learning systems for failure detection in IIoT.
no code implementations • 4 Sep 2020 • Xinli Yu, Mohsen Malmir, Cynthia He, Yue Liu, Rex Wu
However, the inference time will not be a problem for our model since our model has a simple architecture which enables efficient training and inference.
2 code implementations • ICML 2020 • Christos Matsoukas, Albert Bou I Hernandez, Yue Liu, Karin Dembrower, Gisele Miranda, Emir Konuk, Johan Fredin Haslum, Athanasios Zouzos, Peter Lindholm, Fredrik Strand, Kevin Smith
Evidence suggests that networks trained on large datasets generalize well not solely because of the numerous training examples, but also class diversity which encourages learning of enriched features.
1 code implementation • 11 Jul 2020 • Yue Liu, Hossein Azizpour, Fredrik Strand, Kevin Smith
With this in mind, we trained networks using three different criteria to select the positive training data (i. e. images from patients that will develop cancer): an inherent risk model trained on images with no visible signs of cancer, a cancer signs model trained on images containing cancer or early signs of cancer, and a conflated model trained on all images from patients with a cancer diagnosis.
no code implementations • 6 Jul 2020 • Yue Liu, Adam Ghandar, Georgios Theodoropoulos
In this paper, we describe application of Neuroevolution to a P2P lending problem in which a credit evaluation model is updated based on streaming data.
no code implementations • 13 Jun 2020 • Chuanlong Xie, Haotian Ye, Fei Chen, Yue Liu, Rui Sun, Zhenguo Li
The key of the out-of-distribution (OOD) generalization is to generalize invariance from training domains to target domains.
no code implementations • 10 Jun 2020 • Zhuangyan Fang, Shengyu Zhu, Jiji Zhang, Yue Liu, Zhitang Chen, Yangbo He
Despite several important advances in recent years, learning causal structures represented by directed acyclic graphs (DAGs) remains a challenging task in high dimensional settings when the graphs to be learned are not sparse.
no code implementations • 9 Jun 2020 • Kun Kuang, Bo Li, Peng Cui, Yue Liu, Jianrong Tao, Yueting Zhuang, Fei Wu
By assuming the relationships between causal variables and response variable are invariant across data, to address this problem, we propose a conditional independence test based algorithm to separate those causal variables with a seed variable as priori, and adopt them for stable prediction.
no code implementations • 5 Jun 2020 • Xin Cheng, Lei Zhang, Yin Tang, Yue Liu, Hao Wu, Jun He
For deep learning, improvements in performance have to heavily rely on increasing model size or capacity to scale to larger and larger datasets, which inevitably leads to the increase of operations.
1 code implementation • 5 Mar 2020 • Helena H. Lee, Ke Shu, Palakorn Achananuparp, Philips Kokoh Prasetyo, Yue Liu, Ee-Peng Lim, Lav R. Varshney
Interests in the automatic generation of cooking recipes have been growing steadily over the past few years thanks to a large amount of online cooking recipes.
no code implementations • 23 Sep 2019 • Yue Liu, Elisabeth G. Rens, Leah Edelstein-Keshet
The polarization and motility of eukaryotic cells depends on assembly and contraction of the actin cytoskeleton and its regulation by proteins called GTPases.
1 code implementation • 17 Sep 2019 • Helena Lee, Palakorn Achananuparp, Yue Liu, Ee-Peng Lim, Lav R. Varshney
Consumption of diets with low glycemic impact is highly recommended for diabetics and pre-diabetics as it helps maintain their blood glucose levels.
1 code implementation • 17 Sep 2019 • Yue Liu, Helena Lee, Palakorn Achananuparp, Ee-Peng Lim, Tzu-Ling Cheng, Shou-De Lin
Human beings are creatures of habit.
no code implementations • 2 Sep 2019 • Zhitang Chen, Shengyu Zhu, Yue Liu, Tim Tse
We show our algorithm can be reduced to an eigen-decomposition task on a kernel matrix measuring intrinsic deviance/invariance.
no code implementations • 28 Aug 2019 • Andreas Buttenschön, Yue Liu, Leah Edelstein-Keshet
We further consider the feedback between mechanical tension, GTPase activation, and cell deformation in both static, growing, shrinking, and moving cells.
no code implementations • 17 Feb 2019 • Guang-Yu Nie, Yun Liu, Cong Wang, Yue Liu, Yongtian Wang
Three-dimensional (3-D) scene reconstruction is one of the key techniques in Augmented Reality (AR), which is related to the integration of image processing and display systems of complex information.
3 code implementations • 4 Jul 2018 • Yue Liu, Tongtao Zhang, Zhicheng Liang, Heng Ji, Deborah L. McGuinness
Inspired by recent successes in neural machine translation, we treat the triples within a given knowledge graph as an independent graph language and propose an encoder-decoder framework with an attention mechanism that leverages knowledge graph embeddings.
no code implementations • 18 May 2018 • Silvia L. Pintea, Yue Liu, Jan C. van Gemert
Knowledge distillation compacts deep networks by letting a small student network learn from a large teacher network.
no code implementations • WS 2015 • Yue Liu, Tao Ge, Kusum S. Mathews, Heng Ji, Deborah L. McGuinness
In the medical domain, identifying and expanding abbreviations in clinical texts is a vital task for both better human and machine understanding.
no code implementations • ICCV 2015 • Weipeng Xu, Mathieu Salzmann, Yongtian Wang, Yue Liu
Capturing the 3D motion of dynamic, non-rigid objects has attracted significant attention in computer vision.