no code implementations • LREC 2022 • Zheng Chen, Hongyu Lin
Cross-lingual summarization, which produces the summary in one language from a given source document in another language, could be extremely helpful for humans to obtain information across the world.
Abstractive Text Summarization Cross-Lingual Abstractive Summarization
no code implementations • NAACL 2022 • Dingcheng Li, Zheng Chen, Eunah Cho, Jie Hao, Xiaohu Liu, Fan Xing, Chenlei Guo, Yang Liu
Seq2seq language generation models that are trained offline with multiple domains in a sequential fashion often suffer from catastrophic forgetting.
no code implementations • EMNLP (NLP4ConvAI) 2021 • Eunah Cho, Ziyan Jiang, Jie Hao, Zheng Chen, Saurabh Gupta, Xing Fan, Chenlei Guo
Query rewrite (QR) is an emerging component in conversational AI systems, reducing user defect.
no code implementations • 11 Mar 2023 • Zheng Chen, Yulun Zhang, Jinjin Gu, Linghe Kong, Xiaokang Yang
In this work, we propose the Recursive Generalization Transformer (RGT) for image SR, which can capture global spatial information and is suitable for high-resolution images.
no code implementations • 5 Mar 2023 • Zheng Chen, Zhengming Ding, Jason M. Gregory, Lantao Liu
To improve the UDA-SS performance, we propose an Informed Domain Adaptation (IDA) model, a self-training framework that mixes the data based on class-level segmentation performance, which aims to emphasize small-region semantics during mixup.
no code implementations • 5 Mar 2023 • Zheng Chen, Deepak Duggirala, David Crandall, Lei Jiang, Lantao Liu
Prediction beyond partial observations is crucial for robots to navigate in unknown environments because it can provide extra information regarding the surroundings beyond the current sensing range or resolution.
no code implementations • 22 Feb 2023 • Honglin Shu, Pei Gao, Lingwei Zhu, Zheng Chen
In this paper, we propose a novel framework for rapid clinical intervention by viewing health records as graphs whose nodes are mapped from medical events and edges as correspondence between events in given a time window.
no code implementations • 21 Feb 2023 • Jinglun Cai, Mingda Li, Ziyan Jiang, Eunah Cho, Zheng Chen, Yang Liu, Xing Fan, Chenlei Guo
Query Rewriting (QR) plays a critical role in large-scale dialogue systems for reducing frictions.
no code implementations • 27 Jan 2023 • Lingwei Zhu, Zheng Chen, Takamitsu Matsubara, Martha White
Many policy optimization approaches in reinforcement learning incorporate a Kullback-Leilbler (KL) divergence to the previous policy, to prevent the policy from changing too quickly.
no code implementations • 14 Dec 2022 • Chung-Hsuan Hu, Zheng Chen, Erik G. Larsson
Federated Learning (FL) is a collaborative machine learning (ML) framework that combines on-device training and server-based aggregation to train a common ML model among distributed agents.
1 code implementation • 24 Nov 2022 • Zheng Chen, Yulun Zhang, Jinjin Gu, Yongbing Zhang, Linghe Kong, Xin Yuan
The core of our CAT is the Rectangle-Window Self-Attention (Rwin-SA), which utilizes horizontal and vertical rectangle window attention in different heads parallelly to expand the attention area and aggregate the features cross different windows.
no code implementations • 5 Oct 2022 • Jialing Liao, Zheng Chen, Erik G. Larsson
In this work, we aim at minimizing privacy leakage to the adversary and the degradation of model accuracy at the edge server at the same time.
no code implementations • 12 Sep 2022 • Zheng Chen, Chen Wang, Yuan-Chen Guo, Song-Hai Zhang
Neural Radiance Fields (NeRF) achieve photo-realistic view synthesis with densely captured input images.
no code implementations • 20 Jul 2022 • Zheng Chen, Ziwei Yang, Lingwei Zhu, Guang Shi, Kun Yue, Takashi Matsubara, Shigehiko Kanaya, MD Altaf-Ul-Amin
As such, existing methods often impose unrealistic assumptions to extract useful features from the data while avoiding overfitting to spurious correlations.
1 code implementation • 22 Jun 2022 • Zheng Chen, Lingwei Zhu, Ziwei Yang, Takashi Matsubara
Cancer subtyping is crucial for understanding the nature of tumors and providing suitable therapy.
no code implementations • 16 May 2022 • Lingwei Zhu, Zheng Chen, Eiji Uchibe, Takamitsu Matsubara
Maximum Tsallis entropy (MTE) framework in reinforcement learning has gained popularity recently by virtue of its flexible modeling choices including the widely used Shannon entropy and sparse entropy.
no code implementations • 16 May 2022 • Lingwei Zhu, Zheng Chen, Eiji Uchibe, Takamitsu Matsubara
The recently successful Munchausen Reinforcement Learning (M-RL) features implicit Kullback-Leibler (KL) regularization by augmenting the reward function with logarithm of the current stochastic policy.
no code implementations • 7 May 2022 • Zheng Chen, Jian Zhao, Mingyu Yang, Wengang Zhou, Houqiang Li
In this work, we are dedicated to multi-target active object tracking (AOT), where there are multiple targets as well as multiple cameras in the environment.
no code implementations • 21 Apr 2022 • Zheng Chen, Lingwei Zhu, Ziwei Yang, Renyuan Zhang
A spiking neural network (SNN) based tier is designed to distill the principle information in terms of spike-streams from the rare features, which maintains the temporal implication in the nature of EEGs.
no code implementations • 7 Apr 2022 • Zheng Chen, Ziwei Yang, Lingwei Zhu, Wei Chen, Toshiyo Tamura, Naoaki Ono, MD Altaf-Ul-Amin, Shigehiko Kanaya, Ming Huang
This paper proposes a novel framework for automatically capturing the time-frequency nature of electroencephalogram (EEG) signals of human sleep based on the authoritative sleep medicine guidance.
no code implementations • 2 Apr 2022 • Lingwei Zhu, Koki Odani, Ziwei Yang, Guang Shi, Yirong Kan, Zheng Chen, Renyuan Zhang
Recently there has seen promising results on automatic stage scoring by extracting spatio-temporal features from electroencephalogram (EEG).
no code implementations • 2 Apr 2022 • Ziwei Yang, Lingwei Zhu, Zheng Chen, Ming Huang, Naoaki Ono, MD Altaf-Ul-Amin, Shigehiko Kanaya
In this paper, we propose to investigate automatic subtyping from an unsupervised learning perspective by directly constructing the underlying data distribution itself, hence sufficient data can be generated to alleviate the issue of overfitting.
no code implementations • 28 Jan 2022 • Mohammad Hatami, Markus Leinonen, Zheng Chen, Nikolaos Pappas, Marian Codreanu
We consider a resource-constrained IoT network, where multiple users make on-demand requests to a cache-enabled edge node to send status updates about various random processes, each monitored by an energy harvesting sensor.
no code implementations • 29 Oct 2021 • Zheng Chen, Zhengming Ding, David Crandall, Lantao Liu
Detecting navigable space is a fundamental capability for mobile robots navigating in unknown or unmapped environments.
no code implementations • 23 Jul 2021 • Chung-Hsuan Hu, Zheng Chen, Erik G. Larsson
Federated Learning (FL) is a newly emerged decentralized machine learning (ML) framework that combines on-device local training with server-based model synchronization to train a centralized ML model over distributed nodes.
no code implementations • 19 Apr 2021 • Zheng Chen, Håkan Johansson
Efficient and low-complexity beamforming design is an important element of satellite communication systems with mobile receivers equipped with phased arrays.
no code implementations • 16 Feb 2021 • Dehai Yu, Zheng Chen
It is found that as the heating power grows, the memory effect becomes increasingly important and it can greatly reduce the minimum ignition energy.
no code implementations • ICCV 2021 • Zheng Chen, Sihan Wang, Yi Sun, Xiaohong Ma
Traditional methods for RGB hand mesh recovery usually need to train a separate model for each dataset with the corresponding ground truth and are hardly adapted to new scenarios without the ground truth for supervision.
no code implementations • 29 Dec 2020 • Zheng Chen, Erik G. Larsson
Average consensus algorithms have wide applications in distributed computing systems where all the nodes agree on the average value of their initial states by only exchanging information with their local neighbors.
Distributed Computing Distributed, Parallel, and Cluster Computing Social and Information Networks Signal Processing
no code implementations • 22 Dec 2020 • Yuan Zheng, Xueming Shao, Zheng Chen, Wenjie Zhao
When the target's velocity is constant, by employing the geometric properties, those 4 candidates are transformed to a class of sufficiently smooth real-valued functions.
Optimization and Control
no code implementations • COLING 2020 • Zheng Chen, Kangjian Wu
First, ForceReader proposes a novel solution called the Attention Separation Representation to respond to attention deconcentration.
3 code implementations • 19 Oct 2020 • Ming Zhou, Jun Luo, Julian Villella, Yaodong Yang, David Rusu, Jiayu Miao, Weinan Zhang, Montgomery Alban, Iman Fadakar, Zheng Chen, Aurora Chongxi Huang, Ying Wen, Kimia Hassanzadeh, Daniel Graves, Dong Chen, Zhengbang Zhu, Nhat Nguyen, Mohamed Elsayed, Kun Shao, Sanjeevan Ahilan, Baokuan Zhang, Jiannan Wu, Zhengang Fu, Kasra Rezaee, Peyman Yadmellat, Mohsen Rohani, Nicolas Perez Nieves, Yihan Ni, Seyedershad Banijamali, Alexander Cowen Rivers, Zheng Tian, Daniel Palenicek, Haitham Bou Ammar, Hongbo Zhang, Wulong Liu, Jianye Hao, Jun Wang
We open-source the SMARTS platform and the associated benchmark tasks and evaluation metrics to encourage and empower research on multi-agent learning for autonomous driving.
2 code implementations • 11 Aug 2020 • Qin Lyu, Kaushik Chakrabarti, Shobhit Hathi, Souvik Kundu, Jianwen Zhang, Zheng Chen
In this paper, we study how to leverage pre-trained language models in Text-to-SQL.
no code implementations • 16 May 2020 • Zheng Chen, Xinli Yu, Yuan Ling, Xiaohua Hu
Compared with SBM, our framework is flexible, naturally allows soft labels and digestion of complex node attributes.
no code implementations • 13 Feb 2020 • Zheng Chen, Sadid A. Hasan, Joey Liu, Vivek Datla, Md Shamsuzzaman, Hafiz Khan, Mohammad S. Sorower, Gabe Mankovich, Rob van Ommering, Nevenka Dimitrova
This paper presents an ontology-driven treatment article retrieval system developed and experimented using the data and ground truths provided by the TREC 2017 precision medicine track.
no code implementations • 13 Feb 2020 • Zheng Chen, Xing Fan, Yuan Ling, Lambert Mathias, Chenlei Guo
Then, inspired by the wide success of pre-trained contextual language embeddings, and also as a way to compensate for insufficient QR training data, we propose a language-modeling (LM) based approach to pre-train query embeddings on historical user conversation data with a voice assistant.
no code implementations • 10 Oct 2019 • Zheng Chen, Nikolaos Pappas, Emil Björnson, Erik G. Larsson
We formulate an optimization problem that aims at minimizing the average age of information (AoI) of the EH node subject to the queue stability condition of the grid-connected node.
Information Theory Networking and Internet Architecture Information Theory
1 code implementation • 4 Mar 2019 • Zheng Chen, Lantao Liu
We present a framework for creating navigable space from sparse and noisy map points generated by sparse visual SLAM methods.
no code implementations • 14 Jan 2019 • Xinli Yu, Zheng Chen, Wei-Shih Yang, Xiaohua Hu, Erjia Yan
This paper presents a non-trivial reconstruction of a previous joint topic-sentiment-preference review model TSPRA with stick-breaking representation under the framework of variational inference (VI) and stochastic variational inference (SVI).
no code implementations • 19 Dec 2018 • Zheng Chen, Xinli Yu, Chi Zhang, Jin Zhang, Cui Lin, Bo Song, Jianliang Gao, Xiaohua Hu, Wei-Shih Yang, Erjia Yan
Botnet, a group of coordinated bots, is becoming the main platform of malicious Internet activities like DDOS, click fraud, web scraping, spam/rumor distribution, etc.
1 code implementation • 19 Dec 2018 • Zheng Chen, Yong Zhang, Yue Shang, Xiaohua Hu
TSPRA combines topics (i. e. product aspects), word sentiment and user preference as regression factors, and is able to perform topic clustering, review rating prediction, sentiment analysis and what we invent as "critical aspect" analysis altogether in one framework.
no code implementations • 19 Dec 2018 • Zheng Chen, Xinli Yu, Yuan Ling, Bo Song, Wei Quan, Xiaohua Hu, Erjia Yan
Correlated anomaly detection (CAD) from streaming data is a type of group anomaly detection and an essential task in useful real-time data mining applications like botnet detection, financial event detection, industrial process monitor, etc.
1 code implementation • EMNLP 2017 • Dongyeop Kang, Varun Gangal, Ang Lu, Zheng Chen, Eduard Hovy
Our quantitative and human analysis show empirical evidence that our method successfully extracts meaningful causality relationships between time series with textual features and generates appropriate explanation between them.
1 code implementation • AAAI 2014 2014 • Zhen Wang, Jianwen Zhang, Jianlin Feng, Zheng Chen
Utilizing the one-to-many/many-to-one mapping property of a relation, we propose a simple trick to reduce the possibility of false negative labeling.