no code implementations • EMNLP 2021 • Ying Zhang, Hidetaka Kamigaito, Manabu Okumura
Discourse segmentation and sentence-level discourse parsing play important roles for various NLP tasks to consider textual coherence.
no code implementations • RANLP 2021 • Ying Zhang, Hidetaka Kamigaito, Tatsuya Aoki, Hiroya Takamura, Manabu Okumura
Encoder-decoder models have been commonly used for many tasks such as machine translation and response generation.
no code implementations • 1 May 2022 • Naifan Li, Fan Song, Ying Zhang, Pengpeng Liang, Erkang Cheng
In this work, we propose a systematic study on simple Copy-Paste data augmentation for rare object detection in autonomous driving.
no code implementations • 28 Apr 2022 • Recep Yusuf Bekci, Yacine Mahdid, Jinling Xing, Nikita Letov, Ying Zhang, Zahid Pasha
In this study, we utilize Gaussian processes, probabilistic neural network, natural gradient boosting, and quantile regression augmented gradient boosting to model lead times of laser manufacturing processes.
no code implementations • 2 Apr 2022 • Yichen Zhang, Yifang Yin, Ying Zhang, Roger Zimmermann
Contrastive self-supervised learning has attracted significant research attention recently.
1 code implementation • 23 Mar 2022 • Ying Zhang, Thomas G. Fai
The endothelial lining of blood vessels presents a large surface area for exchanging materials between blood and tissues.
no code implementations • 2 Feb 2022 • Xi Yang, Nima PourNejatian, Hoo Chang Shin, Kaleb E Smith, Christopher Parisien, Colin Compas, Cheryl Martin, Mona G Flores, Ying Zhang, Tanja Magoc, Christopher A Harle, Gloria Lipori, Duane A Mitchell, William R Hogan, Elizabeth A Shenkman, Jiang Bian, Yonghui Wu
We developed GatorTron models from scratch using the BERT architecture of different sizes including 345 million, 3. 9 billion, and 8. 9 billion parameters, compared GatorTron with three existing transformer models in the clinical and biomedical domain on 5 different clinical NLP tasks including clinical concept extraction, relation extraction, semantic textual similarity, natural language inference, and medical question answering, to examine how large transformer models could help clinical NLP at different linguistic levels.
no code implementations • 25 Jan 2022 • Hanchen Wang, Ying Zhang, Lu Qin, Wei Wang, Wenjie Zhang, Xuemin Lin
In recent years, many advanced techniques for query vertex ordering (i. e., matching order generation) have been proposed to reduce the unpromising intermediate results according to the preset heuristic rules.
no code implementations • 11 Jan 2022 • Ying Zhang, Samuel A. Isaacson
In bounded domains with no-flux boundary conditions, when choosing unbinding kernels consistent with several commonly used binding kernels, we show that preserving detailed balance of spatial reaction-fluxes at all points requires spatially varying unbinding rate functions near the domain boundary.
no code implementations • 26 Nov 2021 • Xiangyu Meng, Xudong Zhang, Gan Wang, Ying Zhang, Xin Shi, Huanhuan Dai, Zixuan Wang, Xun Wang
Segmentation and labeling of liver tumors and blood vessels in CT images can provide convenience for doctors in liver tumor diagnosis and surgical intervention.
no code implementations • 9 Nov 2021 • Ying Zhang, Matthew A. Gitzendanner, Dan S. Maxwell, Justin W. Richardson, Kaleb E. Smith, Eric A. Stubbs, Brian J. Stucky, Jingchao Zhang, Erik Deumens
Artificial Intelligence has been transforming industries and academic research across the globe, and research software development is no exception.
no code implementations • 8 Nov 2021 • Ying Zhang, Yanbo Chen, Jianhui Wang, Yue Meng, Tianqiao Zhao
Current transmission and distribution system states are mostly unobservable to each other, and state estimation is separately conducted in the two systems owing to the differences in network structures and analytical models.
no code implementations • 27 Oct 2021 • Yaochen Li, Yuhui Hong, Yonghong Song, Chao Zhu, Ying Zhang, Ruihao Wang
The repeated cross-correlation and semi-FPN are designed based on this idea.
no code implementations • 1 Oct 2021 • Jian Yang, Gang Xiao, Yulong Shen, Wei Jiang, Xinyu Hu, Ying Zhang, Jinghui Peng
Pre-trained models learn contextualized word representations on large-scale text corpus through a self-supervised learning method, which has achieved promising performance after fine-tuning.
no code implementations • 16 Sep 2021 • Junfeng Hu, Yuxuan Liang, Zhencheng Fan, Yifang Yin, Ying Zhang, Roger Zimmermann
Sensors are the key to sensing the environment and imparting benefits to smart cities in many aspects, such as providing real-time air quality information throughout an urban area.
no code implementations • ICCV 2021 • Jing Li, Di Kang, Wenjie Pei, Xuefei Zhe, Ying Zhang, Zhenyu He, Linchao Bao
In order to overcome this problem, we propose a novel conditional variational autoencoder (VAE) that explicitly models one-to-many audio-to-motion mapping by splitting the cross-modal latent code into shared code and motion-specific code.
1 code implementation • ACL 2021 • Baohang Zhou, Xiangrui Cai, Ying Zhang, Xiaojie Yuan
Medical named entity recognition (NER) and normalization (NEN) are fundamental for constructing knowledge graphs and building QA systems.
1 code implementation • Findings (ACL) 2021 • Ying Zhang, Fandong Meng, Yufeng Chen, Jinan Xu, Jie zhou
In this paper, we tackle the problem by transferring knowledge from three aspects, i. e., domain, language and task, and strengthening connections among them.
1 code implementation • 19 Jul 2021 • Dong-Young Lim, Ariel Neufeld, Sotirios Sabanis, Ying Zhang
We consider non-convex stochastic optimization problems where the objective functions have super-linearly growing and discontinuous stochastic gradients.
1 code implementation • 25 Jun 2021 • Jianchuan Chen, Ying Zhang, Di Kang, Xuefei Zhe, Linchao Bao, Xu Jia, Huchuan Lu
We present animatable neural radiance fields (animatable NeRF) for detailed human avatar creation from monocular videos.
1 code implementation • CVPR 2021 • Yujin Chen, Zhigang Tu, Di Kang, Linchao Bao, Ying Zhang, Xuefei Zhe, Ruizhi Chen, Junsong Yuan
For the first time, we demonstrate the feasibility of training an accurate 3D hand reconstruction network without relying on manual annotations.
no code implementations • 9 Mar 2021 • Ying Zhang, Kan He
In the paper, we devote to defining an available measure to quantify the nonbilocal correlation in the entanglement-swapping experiment.
Quantum Physics
no code implementations • 25 Feb 2021 • Ying Zhang, Meng Yue, Jianhui Wang
Emergency control, typically such as under-voltage load shedding (UVLS), is broadly used to grapple with low voltage and voltage instability issues in practical power systems under contingencies.
1 code implementation • 5 Jan 2021 • Haiwen Diao, Ying Zhang, Lin Ma, Huchuan Lu
Image-text matching plays a critical role in bridging the vision and language, and great progress has been made by exploiting the global alignment between image and sentence, or local alignments between regions and words.
Ranked #2 on
Image Retrieval
on Flickr30K 1K test
no code implementations • 1 Jan 2021 • Ying Zhang, Zhiqiang Zhao, Zhuo Feng
For the first time, we prove the existence of linear-sized spectral sparsifiers for general directed graphs and introduce a practically-efficient and unified spectral graph sparsification approach that allows sparsifying real-world, large-scale directed and undirected graphs with guaranteed preservation of the original graph spectra.
no code implementations • 24 Dec 2020 • Baoquan Yuan, Ying Zhang
This paper studies the existence and uniqueness of local weak solutions to the d-dimensional tropical climate model without thermal diffusion.
Analysis of PDEs
1 code implementation • 9 Dec 2020 • Yunlong Liang, Fandong Meng, Ying Zhang, Jinan Xu, Yufeng Chen, Jie zhou
Firstly, we design a Heterogeneous Graph-Based Encoder to represent the conversation content (i. e., the dialogue history, its emotion flow, facial expressions, audio, and speakers' personalities) with a heterogeneous graph neural network, and then predict suitable emotions for feedback.
no code implementations • 17 Aug 2020 • Ying Zhang, Zhiqiang Zhao, Zhuo Feng
Recent spectral graph sparsification techniques have shown promising performance in accelerating many numerical and graph algorithms, such as iterative methods for solving large sparse matrices, spectral partitioning of undirected graphs, vectorless verification of power/thermal grids, representation learning of large graphs, etc.
1 code implementation • ECCV 2020 • Haoran Wang, Ying Zhang, Zhong Ji, Yanwei Pang, Lin Ma
In this paper, we propose a Consensus-aware Visual-Semantic Embedding (CVSE) model to incorporate the consensus information, namely the commonsense knowledge shared between both modalities, into image-text matching.
no code implementations • 2 Jul 2020 • Sotirios Sabanis, Ying Zhang
We are thus able to provide theoretical guarantees for the algorithm's convergence in (standard) Wasserstein distances for both convex and non-convex objective functions.
1 code implementation • 12 May 2020 • Hanchen Wang, Defu Lian, Ying Zhang, Lu Qin, Xuemin Lin
We observe that existing works on structured entity interaction prediction cannot properly exploit the unique graph of graphs model.
no code implementations • 19 Apr 2020 • Hanchen Wang, Defu Lian, Ying Zhang, Lu Qin, Xiangjian He, Yiguang Lin, Xuemin Lin
Our proposed method can be seamlessly integrated into the existing GNN-based embedding approaches to binarize the model parameters and learn the compact embedding.
no code implementations • 31 Jan 2020 • Kevin McCloskey, Eric A. Sigel, Steven Kearnes, Ling Xue, Xia Tian, Dennis Moccia, Diana Gikunju, Sana Bazzaz, Betty Chan, Matthew A. Clark, John W. Cuozzo, Marie-Aude Guié, John P. Guilinger, Christelle Huguet, Christopher D. Hupp, Anthony D. Keefe, Christopher J. Mulhern, Ying Zhang, Patrick Riley
We demonstrate a new approach applying machine learning to DEL selection data by identifying active molecules from a large commercial collection and a virtual library of easily synthesizable compounds.
no code implementations • 4 Oct 2019 • Ying Zhang, Ömer Deniz Akyildiz, Theodoros Damoulas, Sotirios Sabanis
Within the context of empirical risk minimization, see Raginsky, Rakhlin, and Telgarsky (2017), we are concerned with a non-asymptotic analysis of sampling algorithms used in optimization.
1 code implementation • 25 Sep 2019 • Chiheb Trabelsi, Olexa Bilaniuk, Ousmane Dia, Ying Zhang, Mirco Ravanelli, Jonathan Binas, Negar Rostamzadeh, Christopher J Pal
Using the Wall Street Journal Dataset, we compare our phase-aware loss to several others that operate both in the time and frequency domains and demonstrate the effectiveness of our proposed signal extraction method and proposed loss.
no code implementations • IJCNLP 2019 • Zehao Lin, Xinjing Huang, Feng Ji, Haiqing Chen, Ying Zhang
How to incorporate external knowledge into a neural dialogue model is critically important for dialogue systems to behave like real humans.
no code implementations • NeurIPS Workshop Deep_Invers 2019 • Chiheb Trabelsi, Olexa Bilaniuk, Ousmane Dia, Ying Zhang, Mirco Ravanelli, Jonathan Binas, Negar Rostamzadeh, Christopher J Pal
Building on recent advances, we propose a new deep complex-valued method for signal retrieval and extraction in the frequency domain.
no code implementations • 21 Aug 2019 • Yike Wu, Shiwan Zhao, Jia Chen, Ying Zhang, Xiaojie Yuan, Zhong Su
Improving the captioning performance on low-resource languages by leveraging English caption datasets has received increasing research interest in recent years.
no code implementations • Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence (IJCAI-19) 2019 • Yonghong Luo, Ying Zhang, Xiangrui Cai, Xiaojie Yuan
The missing values, appear in most of multivariate time series, prevent advanced analysis of multivariate time series data.
1 code implementation • 27 Jun 2019 • Longbin Lai, Zhu Qing, Zhengyi Yang, Xin Jin, Zhengmin Lai, Ran Wang, Kongzhang Hao, Xuemin Lin, Lu Qin, Wenjie Zhang, Ying Zhang, Zhengping Qian, Jingren Zhou
We conduct extensive experiments for both unlabelled matching and labelled matching to analyze the performance of distributed subgraph matching under various settings, which is finally summarized as a practical guide.
Databases
no code implementations • 30 May 2019 • Ngoc Huy Chau, Éric Moulines, Miklos Rásonyi, Sotirios Sabanis, Ying Zhang
We consider the problem of sampling from a target distribution, which is \emph {not necessarily logconcave}, in the context of empirical risk minimization and stochastic optimization as presented in Raginsky et al. (2017).
1 code implementation • 35th IEEE International Conference on Data Engineering (ICDE) 2019 • Ines Arous, Mourad Khayati, Philippe Cudré-Mauroux, Ying Zhang, Martin Kersten, Svetlin Stalinlov
In this paper, we also compare the efficiency and accuracy of RECOVDB against state-of-the-art recovery systems.
no code implementations • 17 Dec 2018 • Zhijing Xu, Juan Wang, Ying Zhang, Xiangjian He
In this paper, a method based on Deep Neural Network (DNN) recognition and classification combined with Mini-Batch Gradient Descent (MBGD) is proposed to distinguish PD patients from healthy people using voiceprint features.
no code implementations • NeurIPS 2018 • Yonghong Luo, Xiangrui Cai, Ying Zhang, Jun Xu, Yuan Xiaojie
Multivariate time series usually contain a large number of missing values, which hinders the application of advanced analysis methods on multivariate time series data.
1 code implementation • ECCV 2018 • Ying Zhang, Huchuan Lu
The key point of image-text matching is how to accurately measure the similarity between visual and textual inputs.
Ranked #10 on
Text based Person Retrieval
on CUHK-PEDES
2 code implementations • 21 Jun 2018 • Negar Rostamzadeh, Seyedarian Hosseini, Thomas Boquet, Wojciech Stokowiec, Ying Zhang, Christian Jauvin, Chris Pal
We introduce a new dataset of 293, 008 high definition (1360 x 1360 pixels) fashion images paired with item descriptions provided by professional stylists.
1 code implementation • 20 Jun 2018 • Titouan Parcollet, Ying Zhang, Mohamed Morchid, Chiheb Trabelsi, Georges Linarès, Renato De Mori, Yoshua Bengio
Quaternion numbers and quaternion neural networks have shown their efficiency to process multidimensional inputs as entities, to encode internal dependencies, and to solve many tasks with less learning parameters than real-valued models.
Ranked #19 on
Speech Recognition
on TIMIT
1 code implementation • 6 Jun 2018 • Xiangrui Cai, Jinyang Gao, Kee Yuan Ngiam, Beng Chin Ooi, Ying Zhang, Xiaojie Yuan
Embeddings of medical concepts such as medication, procedure and diagnosis codes in Electronic Medical Records (EMRs) are central to healthcare analytics.
no code implementations • 13 Mar 2018 • Torsten Kilias, Alexander Löser, Felix A. Gers, Richard Koopmanschap, Ying Zhang, Martin Kersten
We present a novel architecture, In-Database Entity Linking (IDEL), in which we integrate the analytics-optimized RDBMS MonetDB with neural text mining abilities.
no code implementations • 29 Nov 2017 • Donna Xu, Ivor W. Tsang, Ying Zhang
The experiments demonstrate that our online PQ model is both time-efficient and effective for ANN search in dynamic large scale databases compared with baseline methods and the idea of partial PQ codebook update further reduces the update cost.
no code implementations • 26 Oct 2017 • Alessandro Checco, Gianluca Demartini, Alexander Loeser, Ines Arous, Mourad Khayati, Matthias Dantone, Richard Koopmanschap, Svetlin Stalinov, Martin Kersten, Ying Zhang
A core business in the fashion industry is the understanding and prediction of customer needs and trends.
1 code implementation • 7 Oct 2017 • Lei Deng, Yinghui He, Ying Zhang, Minghua Chen, Zongpeng Li, Jack Y. B. Lee, Ying Jun Zhang, Lingyang Song
The idea is to shift traffic from a congested cell to its adjacent under-utilized cells by leveraging inter-cell D2D communication, so that the traffic can be served without using extra spectrum, effectively improving the spectrum temporal efficiency.
Networking and Internet Architecture
8 code implementations • CVPR 2018 • Ying Zhang, Tao Xiang, Timothy M. Hospedales, Huchuan Lu
Model distillation is an effective and widely used technique to transfer knowledge from a teacher to a student network.
8 code implementations • ICLR 2018 • Chiheb Trabelsi, Olexa Bilaniuk, Ying Zhang, Dmitriy Serdyuk, Sandeep Subramanian, João Felipe Santos, Soroush Mehri, Negar Rostamzadeh, Yoshua Bengio, Christopher J. Pal
Despite their attractive properties and potential for opening up entirely new neural architectures, complex-valued deep neural networks have been marginalized due to the absence of the building blocks required to design such models.
Ranked #3 on
Music Transcription
on MusicNet
no code implementations • 13 Apr 2017 • Ying Zhang
This paper considers a general data-fitting problem over a networked system, in which many computing nodes are connected by an undirected graph.
1 code implementation • 10 Jan 2017 • Ying Zhang, Mohammad Pezeshki, Philemon Brakel, Saizheng Zhang, Cesar Laurent Yoshua Bengio, Aaron Courville
Meanwhile, Connectionist Temporal Classification (CTC) with Recurrent Neural Networks (RNNs), which is proposed for labeling unsegmented sequences, makes it feasible to train an end-to-end speech recognition system instead of hybrid settings.
no code implementations • 27 Dec 2016 • Lilei Zheng, Ying Zhang, Stefan Duffner, Khalid Idrissi, Christophe Garcia, Atilla Baskurt
This paper presents a deep nonlinear metric learning framework for data visualization on an image dataset.
1 code implementation • 21 Nov 2016 • Joachim Ott, Zhouhan Lin, Ying Zhang, Shih-Chii Liu, Yoshua Bengio
Recurrent Neural Networks (RNNs) produce state-of-art performance on many machine learning tasks but their demand on resources in terms of memory and computational power are often high.
1 code implementation • NeurIPS 2016 • Alex Lamb, Anirudh Goyal, Ying Zhang, Saizheng Zhang, Aaron Courville, Yoshua Bengio
We introduce the Professor Forcing algorithm, which uses adversarial domain adaptation to encourage the dynamics of the recurrent network to be the same when training the network and when sampling from the network over multiple time steps.
3 code implementations • 8 Oct 2016 • Wen Li, Ying Zhang, Yifang Sun, Wei Wang, Wenjie Zhang, Xuemin Lin
Approximate Nearest neighbor search (ANNS) is fundamental and essential operation in applications from many domains, such as databases, machine learning, multimedia, and computer vision.
Databases
1 code implementation • 24 Aug 2016 • Joachim Ott, Zhouhan Lin, Ying Zhang, Shih-Chii Liu, Yoshua Bengio
We present results from the use of different stochastic and deterministic reduced precision training methods applied to three major RNN types which are then tested on several datasets.
no code implementations • NeurIPS 2016 • Yuhuai Wu, Saizheng Zhang, Ying Zhang, Yoshua Bengio, Ruslan Salakhutdinov
We introduce a general and simple structural design called Multiplicative Integration (MI) to improve recurrent neural networks (RNNs).
no code implementations • CVPR 2016 • Ying Zhang, Baohua Li, Huchuan Lu, Atshushi Irie, Xiang Ruan
Person re-identification addresses the problem of matching people across disjoint camera views and extensive efforts have been made to seek either the robust feature representation or the discriminative matching metrics.
1 code implementation • 9 May 2016 • The Theano Development Team, Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermueller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre-Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Mélanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian Goodfellow, Matt Graham, Caglar Gulcehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrancois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert T. McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang
Since its introduction, it has been one of the most used CPU and GPU mathematical compilers - especially in the machine learning community - and has shown steady performance improvements.
no code implementations • 5 Oct 2015 • César Laurent, Gabriel Pereyra, Philémon Brakel, Ying Zhang, Yoshua Bengio
Recurrent Neural Networks (RNNs) are powerful models for sequential data that have the potential to learn long-term dependencies.
no code implementations • CVPR 2015 • Baohua Li, Ying Zhang, Zhouchen Lin, Huchuan Lu
Therefore, we propose Mixture of Gaussian Regression (MoG Regression) for subspace clustering by modeling noise as a Mixture of Gaussians (MoG).