Search Results for author: Yu Chen

Found 96 papers, 33 papers with code

Influence of the Binomial Crossover on Performance of Randomized Search Heuristics

no code implementations29 Sep 2021 Cong Wang, Yu Chen, Jun He, Xiufen Zou

Unlike other metaheuristics, differential Evolution (DE) employs a crossover operation filtering variables to be mutated, which contributes to its successful applications in a variety of complicated optimization problems.

Graph-MVP: Multi-View Prototypical Contrastive Learning for Multiplex Graphs

no code implementations8 Sep 2021 Baoyu Jing, Yuejia Xiang, Xi Chen, Yu Chen, Hanghang Tong

To address these challenges, we propose a novel Graph Multi-View Prototypical (Graph-MVP) framework to extract node embeddings on multiplex graphs.

Contrastive Learning Graph Representation Learning +1

Photonic-enabled radio-frequency self-interference cancellation incorporated in an in-band full-duplex radio-over-fiber system

no code implementations1 Sep 2021 Taixia Shi, Yu Chen, Yang Chen

A photonic approach for radio-frequency (RF) self-interference cancellation (SIC) incorporated in an in-band full-duplex radio-over-fiber system is proposed.

Model-based Decision Making with Imagination for Autonomous Parking

1 code implementation25 Aug 2021 Ziyue Feng, Yu Chen, Shitao Chen, Nanning Zheng

The proposed algorithm consists of three parts: an imaginative model for anticipating results before parking, an improved rapid-exploring random tree (RRT) for planning a feasible trajectory from a given start point to a parking lot, and a path smoothing module for optimizing the efficiency of parking tasks.

Autonomous Driving Decision Making

A Cuckoo Quantum Evolutionary Algorithm for the Graph Coloring Problem

no code implementations19 Aug 2021 Yongjian Xu, Yu Chen

Based on the framework of the quantum-inspired evolutionary algorithm, a cuckoo quantum evolutionary algorithm (CQEA) is proposed for solving the graph coloring problem (GCP).

Method Towards CVPR 2021 Image Matching Challenge

no code implementations10 Aug 2021 Xiaopeng Bi, Yu Chen, Xinyang Liu, Dehao Zhang, Ran Yan, Zheng Chai, Haotian Zhang, Xiao Liu

This report describes Megvii-3D team's approach towards CVPR 2021 Image Matching Workshop.

Energy-based Unknown Intent Detection with Data Manipulation

1 code implementation27 Jul 2021 Yawen Ouyang, Jiasheng Ye, Yu Chen, Xinyu Dai, ShuJian Huang, Jiajun Chen

Unknown intent detection aims to identify the out-of-distribution (OOD) utterance whose intent has never appeared in the training set.

Intent Detection

CLIP2Video: Mastering Video-Text Retrieval via Image CLIP

1 code implementation21 Jun 2021 Han Fang, Pengfei Xiong, Luhui Xu, Yu Chen

We present CLIP2Video network to transfer the image-language pre-training model to video-text retrieval in an end-to-end manner.

Language Modelling Video-Text Retrieval

Deep Learning in Latent Space for Video Prediction and Compression

no code implementations CVPR 2021 Bowen Liu, Yu Chen, Shiyu Liu, Hun-Seok Kim

The proposed method first learns the efficient lower-dimensional latent space representation of each video frame and then performs inter-frame prediction in that latent domain.

Anomaly Detection Event Detection +2

Graph Neural Networks for Natural Language Processing: A Survey

1 code implementation10 Jun 2021 Lingfei Wu, Yu Chen, Kai Shen, Xiaojie Guo, Hanning Gao, Shucheng Li, Jian Pei, Bo Long

Deep learning has become the dominant approach in coping with various tasks in Natural LanguageProcessing (NLP).

graph construction Graph Representation Learning

Deep Learning on Graphs for Natural Language Processing

no code implementations NAACL 2021 Lingfei Wu, Yu Chen, Heng Ji, Yunyao Li

Due to its great power in modeling non-Euclidean data like graphs or manifolds, deep learning on graph techniques (i. e., Graph Neural Networks (GNNs)) have opened a new door to solving challenging graph-related NLP problems.

graph construction Graph Representation Learning +8

VeniBot: Towards Autonomous Venipuncture with Automatic Puncture Area and Angle Regression from NIR Images

no code implementations27 May 2021 Xu Cao, Zijie Chen, Bolin Lai, Yuxuan Wang, Yu Chen, Zhengqing Cao, Zhilin Yang, Nanyang Ye, Junbo Zhao, Xiao-Yun Zhou, Peng Qi

For the automation, we focus on the positioning part and propose a Dual-In-Dual-Out network based on two-step learning and two-task learning, which can achieve fully automatic regression of the suitable puncture area and angle from near-infrared(NIR) images.

Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning in Targeted Display Advertising

2 code implementations18 May 2021 Dongbo Xi, Zhen Chen, Peng Yan, Yinger Zhang, Yongchun Zhu, Fuzhen Zhuang, Yu Chen

While considerable multi-task efforts have been made in this direction, a long-standing challenge is how to explicitly model the long-path sequential dependence among audience multi-step conversions for improving the end-to-end conversion.

Multi-Task Learning

A Rigid Registration Method in TEVAR

no code implementations29 Apr 2021 Meng Li, Changyan Lin, Lixia Shu, Xin Pu, Yu Chen, Heng Wu, Jiasong Li, Hongshuai Cao

Since the mapping relationship between definitized intra-interventional 2D X-ray and undefined pre-interventional 3D Computed Tomography(CT) is uncertain, auxiliary positioning devices or body markers, such as medical implants, are commonly used to determine this relationship.

Computed Tomography (CT) Semantic Segmentation

Improve GAN-based Neural Vocoder using Pointwise Relativistic LeastSquare GAN

no code implementations26 Mar 2021 Congyi Wang, Yu Chen, Bin Wang, Yi Shi

GAN-based neural vocoders, such as Parallel WaveGAN and MelGAN have attracted great interest due to their lightweight and parallel structures, enabling them to generate high fidelity waveform in a real-time manner.

Generic Perceptual Loss for Modeling Structured Output Dependencies

no code implementations CVPR 2021 Yifan Liu, Hao Chen, Yu Chen, Wei Yin, Chunhua Shen

We hope that this simple, extended perceptual loss may serve as a generic structured-output loss that is applicable to most structured output learning tasks.

Depth Estimation Image Generation +4

Continual Density Ratio Estimation in an Online Setting

no code implementations9 Mar 2021 Yu Chen, Song Liu, Tom Diethe, Peter Flach

To the best of our knowledge, there is no existing method that can evaluate generative models in continual learning without storing samples from the original distribution.

Continual Learning Decision Making +1

An Optimized H.266/VVC Software Decoder On Mobile Platform

no code implementations5 Mar 2021 Yiming Li, Shan Liu, Yu Chen, Yushan Zheng, Sijia Chen, Bin Zhu, Jian Lou

As the successor of H. 265/HEVC, the new versatile video coding standard (H. 266/VVC) can provide up to 50% bitrate saving with the same subjective quality, at the cost of increased decoding complexity.

The LOB Recreation Model: Predicting the Limit Order Book from TAQ History Using an Ordinary Differential Equation Recurrent Neural Network

no code implementations2 Mar 2021 Zijian Shi, Yu Chen, John Cartlidge

In an order-driven financial market, the price of a financial asset is discovered through the interaction of orders - requests to buy or sell at a particular price - that are posted to the public limit order book (LOB).

Transfer Learning

Signal identification with Kalman Filter towards background-free neutrinoless double beta decay searches in gaseous detectors

no code implementations16 Feb 2021 Tao Li, Shaobo Wang, Yu Chen, Ke Han, Heng Lin, Kaixiang Ni, Wei Wang, Yiliu Xu, Anni Zou

Particle tracks and differential energy loss measured in high pressure gaseous detectors can be exploited for event identification in neutrinoless double beta decay~($0\nu \beta \beta$) searches.

Instrumentation and Detectors High Energy Physics - Experiment

Exponential suppression of bit or phase flip errors with repetitive error correction

no code implementations11 Feb 2021 Zijun Chen, Kevin J. Satzinger, Juan Atalaya, Alexander N. Korotkov, Andrew Dunsworth, Daniel Sank, Chris Quintana, Matt McEwen, Rami Barends, Paul V. Klimov, Sabrina Hong, Cody Jones, Andre Petukhov, Dvir Kafri, Sean Demura, Brian Burkett, Craig Gidney, Austin G. Fowler, Harald Putterman, Igor Aleiner, Frank Arute, Kunal Arya, Ryan Babbush, Joseph C. Bardin, Andreas Bengtsson, Alexandre Bourassa, Michael Broughton, Bob B. Buckley, David A. Buell, Nicholas Bushnell, Benjamin Chiaro, Roberto Collins, William Courtney, Alan R. Derk, Daniel Eppens, Catherine Erickson, Edward Farhi, Brooks Foxen, Marissa Giustina, Jonathan A. Gross, Matthew P. Harrigan, Sean D. Harrington, Jeremy Hilton, Alan Ho, Trent Huang, William J. Huggins, L. B. Ioffe, Sergei V. Isakov, Evan Jeffrey, Zhang Jiang, Kostyantyn Kechedzhi, Seon Kim, Fedor Kostritsa, David Landhuis, Pavel Laptev, Erik Lucero, Orion Martin, Jarrod R. McClean, Trevor McCourt, Xiao Mi, Kevin C. Miao, Masoud Mohseni, Wojciech Mruczkiewicz, Josh Mutus, Ofer Naaman, Matthew Neeley, Charles Neill, Michael Newman, Murphy Yuezhen Niu, Thomas E. O'Brien, Alex Opremcak, Eric Ostby, Bálint Pató, Nicholas Redd, Pedram Roushan, Nicholas C. Rubin, Vladimir Shvarts, Doug Strain, Marco Szalay, Matthew D. Trevithick, Benjamin Villalonga, Theodore White, Z. Jamie Yao, Ping Yeh, Adam Zalcman, Hartmut Neven, Sergio Boixo, Vadim Smelyanskiy, Yu Chen, Anthony Megrant, Julian Kelly

QEC also requires that the errors are local and that performance is maintained over many rounds of error correction, two major outstanding experimental challenges.

Quantum Physics

Polyphone Disambiguition in Mandarin Chinese with Semi-Supervised Learning

no code implementations1 Feb 2021 Yi Shi, Congyi Wang, Yu Chen, Bin Wang

In this paper, we propose a novel semi-supervised learning (SSL) framework for Mandarin Chinese polyphone disambiguation that can potentially leverage unlimited unlabeled text data.

Polyphone disambiguation

Hybrid Rotation Averaging: A Fast and Robust Rotation Averaging Approach

no code implementations CVPR 2021 Yu Chen, Ji Zhao, Laurent Kneip

We push the envelope of rotation averaging by leveraging the advantages of a global RA method and a local RA method.

3D Reconstruction Structure from Motion

Slow Control System for PandaX-III experiment

no code implementations24 Dec 2020 Xiyu Yan, Xun Chen, Yu Chen, Bo Dai, Heng Lin, Tao Li, Ke Han, Kaixiang Ni, Fusang Wang, Shaobo Wang, Qibin Zheng, Xinning Zeng

The PandaX-III experiment uses high pressure gaseous time projection chamber to search for the neutrinoless double beta decay of $^{136}$Xe.

Anomaly Detection High Energy Physics - Experiment Instrumentation and Detectors

On Extending NLP Techniques from the Categorical to the Latent Space: KL Divergence, Zipf's Law, and Similarity Search

1 code implementation2 Dec 2020 Adam Hare, Yu Chen, Yinan Liu, Zhenming Liu, Christopher G. Brinton

Despite the recent successes of deep learning in natural language processing (NLP), there remains widespread usage of and demand for techniques that do not rely on machine learning.

Word Embeddings

Entropy Linear Response Theory with Non-Markovian Bath

no code implementations1 Dec 2020 Yu Chen

A non-monotonic behavior of Renyi entropy for fermionic systems is found to be quite general when the environment's temperature is lower.

High Energy Physics - Theory Quantum Gases Strongly Correlated Electrons

Deep reinforcement learning for RAN optimization and control

no code implementations9 Nov 2020 Yu Chen, Jie Chen, Ganesh Krishnamurthi, Huijing Yang, Huahui Wang, Wenjie Zhao

Due to the high variability of the traffic in the radio access network (RAN), fixed network configurations are not flexible enough to achieve optimal performance.

Observation of separated dynamics of charge and spin in the Fermi-Hubbard model

no code implementations15 Oct 2020 Frank Arute, Kunal Arya, Ryan Babbush, Dave Bacon, Joseph C. Bardin, Rami Barends, Andreas Bengtsson, Sergio Boixo, Michael Broughton, Bob B. Buckley, David A. Buell, Brian Burkett, Nicholas Bushnell, Yu Chen, Zijun Chen, Yu-An Chen, Ben Chiaro, Roberto Collins, Stephen J. Cotton, William Courtney, Sean Demura, Alan Derk, Andrew Dunsworth, Daniel Eppens, Thomas Eckl, Catherine Erickson, Edward Farhi, Austin Fowler, Brooks Foxen, Craig Gidney, Marissa Giustina, Rob Graff, Jonathan A. Gross, Steve Habegger, Matthew P. Harrigan, Alan Ho, Sabrina Hong, Trent Huang, William Huggins, Lev B. Ioffe, Sergei V. Isakov, Evan Jeffrey, Zhang Jiang, Cody Jones, Dvir Kafri, Kostyantyn Kechedzhi, Julian Kelly, Seon Kim, Paul V. Klimov, Alexander N. Korotkov, Fedor Kostritsa, David Landhuis, Pavel Laptev, Mike Lindmark, Erik Lucero, Michael Marthaler, Orion Martin, John M. Martinis, Anika Marusczyk, Sam McArdle, Jarrod R. McClean, Trevor McCourt, Matt McEwen, Anthony Megrant, Carlos Mejuto-Zaera, Xiao Mi, Masoud Mohseni, Wojciech Mruczkiewicz, Josh Mutus, Ofer Naaman, Matthew Neeley, Charles Neill, Hartmut Neven, Michael Newman, Murphy Yuezhen Niu, Thomas E. O'Brien, Eric Ostby, Bálint Pató, Andre Petukhov, Harald Putterman, Chris Quintana, Jan-Michael Reiner, Pedram Roushan, Nicholas C. Rubin, Daniel Sank, Kevin J. Satzinger, Vadim Smelyanskiy, Doug Strain, Kevin J. Sung, Peter Schmitteckert, Marco Szalay, Norm M. Tubman, Amit Vainsencher, Theodore White, Nicolas Vogt, Z. Jamie Yao, Ping Yeh, Adam Zalcman, Sebastian Zanker

Strongly correlated quantum systems give rise to many exotic physical phenomena, including high-temperature superconductivity.

Quantum Physics

Simple Neighborhood Representative Pre-processing Boosts Outlier Detectors

no code implementations11 Oct 2020 Jiawei Yang, Yu Chen

The neighborhood representative first selects a subset of representative objects from data, then employs outlier detectors to score the representatives.

On Efficient Constructions of Checkpoints

no code implementations ICML 2020 Yu Chen, Zhenming Liu, Bin Ren, Xin Jin

Efficient construction of checkpoints/snapshots is a critical tool for training and diagnosing deep learning models.


CVPR 2020 Continual Learning in Computer Vision Competition: Approaches, Results, Current Challenges and Future Directions

1 code implementation14 Sep 2020 Vincenzo Lomonaco, Lorenzo Pellegrini, Pau Rodriguez, Massimo Caccia, Qi She, Yu Chen, Quentin Jodelet, Ruiping Wang, Zheda Mai, David Vazquez, German I. Parisi, Nikhil Churamani, Marc Pickett, Issam Laradji, Davide Maltoni

In the last few years, we have witnessed a renewed and fast-growing interest in continual learning with deep neural networks with the shared objective of making current AI systems more adaptive, efficient and autonomous.

Continual Learning

Iterative Deep Graph Learning for Graph Neural Networks: Better and Robust Node Embeddings

1 code implementation NeurIPS 2020 Yu Chen, Lingfei Wu, Mohammed J. Zaki

In this paper, we propose an end-to-end graph learning framework, namely Iterative Deep Graph Learning (IDGL), for jointly and iteratively learning graph structure and graph embedding.

Graph Embedding Graph Learning +1

Discriminative Representation Loss (DRL): Connecting Deep Metric Learning to Continual Learning

no code implementations19 Jun 2020 Yu Chen, Tom Diethe, Peter Flach

The use of episodic memories in continual learning has been shown to be effective in terms of alleviating catastrophic forgetting.

Continual Learning Metric Learning

Retrieval-Augmented Generation for Code Summarization via Hybrid GNN

1 code implementation ICLR 2021 Shangqing Liu, Yu Chen, Xiaofei Xie, JingKai Siow, Yang Liu

However, automatic code summarization is challenging due to the complexity of the source code and the language gap between the source code and natural language summaries.

Code Summarization Source Code Summarization

Minor Privacy Protection Through Real-time Video Processing at the Edge

no code implementations3 May 2020 Meng Yuan, Seyed Yahya Nikouei, Alem Fitwi, Yu Chen, Yunxi Dong

The collection of a lot of personal information about individuals, including the minor members of a family, by closed-circuit television (CCTV) cameras creates a lot of privacy concerns.

Face Recognition General Classification

Toward Subgraph Guided Knowledge Graph Question Generation with Graph Neural Networks

1 code implementation13 Apr 2020 Yu Chen, Lingfei Wu, Mohammed J. Zaki

In this work, we focus on a more realistic setting where we aim to generate questions from a KG subgraph and target answers.

Data Augmentation KG-to-Text Generation +2

Quantum Approximate Optimization of Non-Planar Graph Problems on a Planar Superconducting Processor

1 code implementation8 Apr 2020 Frank Arute, Kunal Arya, Ryan Babbush, Dave Bacon, Joseph C. Bardin, Rami Barends, Sergio Boixo, Michael Broughton, Bob B. Buckley, David A. Buell, Brian Burkett, Nicholas Bushnell, Yu Chen, Zijun Chen, Ben Chiaro, Roberto Collins, William Courtney, Sean Demura, Andrew Dunsworth, Daniel Eppens, Edward Farhi, Austin Fowler, Brooks Foxen, Craig Gidney, Marissa Giustina, Rob Graff, Steve Habegger, Matthew P. Harrigan, Alan Ho, Sabrina Hong, Trent Huang, L. B. Ioffe, Sergei V. Isakov, Evan Jeffrey, Zhang Jiang, Cody Jones, Dvir Kafri, Kostyantyn Kechedzhi, Julian Kelly, Seon Kim, Paul V. Klimov, Alexander N. Korotkov, Fedor Kostritsa, David Landhuis, Pavel Laptev, Mike Lindmark, Martin Leib, Erik Lucero, Orion Martin, John M. Martinis, Jarrod R. McClean, Matt McEwen, Anthony Megrant, Xiao Mi, Masoud Mohseni, Wojciech Mruczkiewicz, Josh Mutus, Ofer Naaman, Matthew Neeley, Charles Neill, Florian Neukart, Hartmut Neven, Murphy Yuezhen Niu, Thomas E. O'Brien, Bryan O'Gorman, Eric Ostby, Andre Petukhov, Harald Putterman, Chris Quintana, Pedram Roushan, Nicholas C. Rubin, Daniel Sank, Kevin J. Satzinger, Andrea Skolik, Vadim Smelyanskiy, Doug Strain, Michael Streif, Kevin J. Sung, Marco Szalay, Amit Vainsencher, Theodore White, Z. Jamie Yao, Ping Yeh, Adam Zalcman, Leo Zhou

For problems defined on our hardware graph we obtain an approximation ratio that is independent of problem size and observe, for the first time, that performance increases with circuit depth.

Quantum Physics

Automatic, Dynamic, and Nearly Optimal Learning Rate Specification by Local Quadratic Approximation

1 code implementation7 Apr 2020 Yingqiu Zhu, Yu Chen, Danyang Huang, Bo Zhang, Hansheng Wang

In each update step, given the gradient direction, we locally approximate the loss function by a standard quadratic function of the learning rate.

I-ViSE: Interactive Video Surveillance as an Edge Service using Unsupervised Feature Queries

no code implementations9 Mar 2020 Seyed Yahya Nikouei, Yu Chen, Alexander Aved, Erik Blasch

Adopting unsupervised methods that do not reveal any private information, the I-ViSE scheme utilizes general features of a human body and color of clothes.

Face Recognition Scene Recognition

Deform-GAN:An Unsupervised Learning Model for Deformable Registration

1 code implementation26 Feb 2020 Xiaoyue Zhang, Weijian Jian, Yu Chen, Shihting Yang

Deformable registration is one of the most challenging task in the field of medical image analysis, especially for the alignment between different sequences and modalities.

Simulation Pipeline for Traffic Evacuation in Urban Areas and Emergency Traffic Management Policy Improvements through Case Studies

1 code implementation14 Feb 2020 Yu Chen, S. Yusef Shafi, Yi-fan Chen

Traffic evacuation plays a critical role in saving lives in devastating disasters such as hurricanes, wildfires, floods, earthquakes, etc.

Exploitation and Exploration Analysis of Elitist Evolutionary Algorithms: A Case Study

no code implementations29 Jan 2020 Yu Chen, Jun He

Known as two cornerstones of problem solving by search, exploitation and exploration are extensively discussed for implementation and application of evolutionary algorithms (EAs).

Occlum: Secure and Efficient Multitasking Inside a Single Enclave of Intel SGX

7 code implementations21 Jan 2020 Youren Shen, Hongliang Tian, Yu Chen, Kang Chen, Runji Wang, Yi Xu, Yubin Xia

SFI is a software instrumentation technique for sandboxing untrusted modules (called domains).

Operating Systems Hardware Architecture Cryptography and Security

Graph-Based Parallel Large Scale Structure from Motion

1 code implementation23 Dec 2019 Yu Chen, Shuhan Shen, Yisong Chen, Guoping Wang

After local reconstructions, we construct a minimum spanning tree (MinST) to find accurate similarity transformations.

3D Reconstruction Structure from Motion

Microchain: a Light Hierarchical Consensus Protocol for IoT System

no code implementations21 Dec 2019 Ronghua Xu, Yu Chen

While the large-scale Internet of Things (IoT) makes many new applications feasible, like Smart Cities, IoT also brings new concerns on data reliability, security, and privacy.

Distributed, Parallel, and Cluster Computing

Predicting Heart Failure Readmission from Clinical Notes Using Deep Learning

no code implementations21 Dec 2019 Xiong Liu, Yu Chen, Jay Bae, Hu Li, Joseph Johnston, Todd Sanger

We then use the trained models to classify and predict potentially high-risk admissions/patients.

Readmission Prediction

Deep Iterative and Adaptive Learning for Graph Neural Networks

1 code implementation17 Dec 2019 Yu Chen, Lingfei Wu, Mohammed J. Zaki

In this paper, we propose an end-to-end graph learning framework, namely Deep Iterative and Adaptive Learning for Graph Neural Networks (DIAL-GNN), for jointly learning the graph structure and graph embeddings simultaneously.

Graph Learning Metric Learning

Bundle Adjustment Revisited

no code implementations9 Dec 2019 Yu Chen, Yisong Chen, Guoping Wang

3D reconstruction has been developing all these two decades, from moderate to medium size and to large scale.

3D Reconstruction Structure from Motion

Fast and Incremental Loop Closure Detection Using Proximity Graphs

1 code implementation25 Nov 2019 Shan An, Guangfu Che, Fangru Zhou, Xianglong Liu, Xin Ma, Yu Chen

Visual loop closure detection, which can be considered as an image retrieval task, is an important problem in SLAM (Simultaneous Localization and Mapping) systems.

Image Retrieval Loop Closure Detection +1

Identification of Interaction Clusters Using a Semi-supervised Hierarchical Clustering Method

no code implementations20 Oct 2019 Yu Chen, Yuanyuan Yang, Yaochu Jin, Xiufen Zou

Motivation: Identifying interaction clusters of large gene regulatory networks (GRNs) is critical for its further investigation, while this task is very challenging, attributed to data noise in experiment data, large scale of GRNs, and inconsistency between gene expression profiles and function modules, etc.

Microchain: A Hybrid Consensus Mechanism for Lightweight Distributed Ledger for IoT

no code implementations24 Sep 2019 Ronghua Xu, Yu Chen, Erik Blasch, Genshe Chen

In this paper, Microchain, based on a hybrid Proof-of-Credit (PoC)-Voting-based Chain Finality (VCF) consensus protocol, is proposed to provide a secure, scalable and lightweight distributed ledger for IoT systems.

Distributed, Parallel, and Cluster Computing

I-SAFE: Instant Suspicious Activity identiFication at the Edge using Fuzzy Decision Making

no code implementations12 Sep 2019 Seyed Yahya Nikouei, Yu Chen, Alexander Aved, Erik Blasch, Timothy R. Faughnan

This paper presents a forensic surveillance strategy by introducing an Instant Suspicious Activity identiFication at the Edge (I-SAFE) using fuzzy decision making.

Decision Making Edge-computing

Error Analysis of Elitist Randomized Search Heuristics

no code implementations3 Sep 2019 Cong Wang, Yu Chen, Jun He, Chengwang Xie

When globally optimal solutions of complicated optimization problems cannot be located by evolutionary algorithms (EAs) in polynomial expected running time, the hitting time/running time analysis is not flexible enough to accommodate the requirement of theoretical study, because sometimes we have no idea on what approximation ratio is available in polynomial expected running time.

No Peeking through My Windows: Conserving Privacy in Personal Drones

no code implementations26 Aug 2019 Alem Fitwi, Yu Chen, Sencun Zhu

Hence, this mechanism detects window objects in every image or frame of a real-time video and masks them chaotically to protect the privacy of people.

Object Detection

Machine Translation from an Intercomprehension Perspective

no code implementations WS 2019 Yu Chen, Tania Avgustinova

Within the first shared task on machine translation between similar languages, we present our first attempts on Czech to Polish machine translation from an intercomprehension perspective.

Machine Translation Translation

GraphFlow: Exploiting Conversation Flow with Graph Neural Networks for Conversational Machine Comprehension

1 code implementation31 Jul 2019 Yu Chen, Lingfei Wu, Mohammed J. Zaki

The proposed GraphFlow model can effectively capture conversational flow in a dialog, and shows competitive performance compared to existing state-of-the-art methods on CoQA, QuAC and DoQA benchmarks.

Machine Reading Comprehension

Delving Deep into Liver Focal Lesion Detection: A Preliminary Study

no code implementations24 Jul 2019 Jiechao Ma, Yingqian Chen, Yu Chen, Fengkai Wan, Sumin Xue, Ziping Li, Shiting Feng

Hepatocellular carcinoma (HCC) is the second most frequent cause of malignancy-related death and is one of the diseases with the highest incidence in the world.

Computed Tomography (CT) Image Registration +1

EnforceNet: Monocular Camera Localization in Large Scale Indoor Sparse LiDAR Point Cloud

no code implementations16 Jul 2019 Yu Chen, Guan Wang

Pose estimation is a fundamental building block for robotic applications such as autonomous vehicles, UAV, and large scale augmented reality.

Autonomous Vehicles Camera Localization +1

OctopusNet: A Deep Learning Segmentation Network for Multi-modal Medical Images

no code implementations5 Jun 2019 Yu Chen, Jia-Wei Chen, Dong Wei, Yuexiang Li, Yefeng Zheng

Two approaches are widely used in the literature to fuse multiple modalities in the segmentation networks: early-fusion (which stacks multiple modalities as different input channels) and late-fusion (which fuses the segmentation results from different modalities at the very end).

Strain engineering of epitaxial oxide heterostructures beyond substrate limitations

no code implementations3 May 2019 Xiong Deng, Chao Chen, Deyang Chen, Xiangbin Cai, Xiaozhe Yin, Chao Xu, Fei Sun, Caiwen Li, Yan Li, Han Xu, Mao Ye, Guo Tian, Zhen Fan, Zhipeng Hou, Minghui Qin, Yu Chen, Zhenlin Luo, Xubing Lu, Guofu Zhou, Lang Chen, Ning Wang, Ye Zhu, Xingsen Gao, Jun-Ming Liu

The limitation of commercially available single-crystal substrates and the lack of continuous strain tunability preclude the ability to take full advantage of strain engineering for further exploring novel properties and exhaustively studying fundamental physics in complex oxides.

Materials Science

Facilitating Bayesian Continual Learning by Natural Gradients and Stein Gradients

no code implementations24 Apr 2019 Yu Chen, Tom Diethe, Neil Lawrence

Conventional models tend to forget the knowledge of previous tasks while learning a new task, a phenomenon known as catastrophic forgetting.

Continual Learning

$β^3$-IRT: A New Item Response Model and its Applications

1 code implementation10 Mar 2019 Yu Chen, Telmo Silva Filho, Ricardo B. C. Prudêncio, Tom Diethe, Peter Flach

Item Response Theory (IRT) aims to assess latent abilities of respondents based on the correctness of their answers in aptitude test items with different difficulty levels.

Clustering Bioactive Molecules in 3D Chemical Space with Unsupervised Deep Learning

no code implementations9 Feb 2019 Chu Qin, Ying Tan, Shang Ying Chen, Xian Zeng, Xingxing Qi, Tian Jin, Huan Shi, Yiwei Wan, Yu Chen, Jingfeng Li, Weidong He, Yali Wang, Peng Zhang, Feng Zhu, Hongping Zhao, Yuyang Jiang, Yuzong Chen

We ex-plored the superior learning capability of deep autoencoders for unsupervised clustering of 1. 39 mil-lion bioactive molecules into band-clusters in a 3-dimensional latent chemical space.

Drug Discovery

Towards Highly Accurate and Stable Face Alignment for High-Resolution Videos

1 code implementation1 Nov 2018 Ying Tai, Yicong Liang, Xiaoming Liu, Lei Duan, Jilin Li, Chengjie Wang, Feiyue Huang, Yu Chen

In recent years, heatmap regression based models have shown their effectiveness in face alignment and pose estimation.

Face Alignment Pose Estimation +1

Average Convergence Rate of Evolutionary Algorithms II: Continuous Optimization

no code implementations27 Oct 2018 Yu Chen, Jun He

But for hard functions such as the deceptive function, the ACR of both the (1+1) adaptive random univariate search and evolutionary programming is exponential.

A Theoretical Framework of Approximation Error Analysis of Evolutionary Algorithms

no code implementations26 Oct 2018 Jun He, Yu Chen, Yuren Zhou

In the empirical study of evolutionary algorithms, the solution quality is evaluated by either the fitness value or approximation error.

Sublinear Algorithms for $(Δ+ 1)$ Vertex Coloring

2 code implementations24 Jul 2018 Sepehr Assadi, Yu Chen, Sanjeev Khanna

Any graph with maximum degree $\Delta$ admits a proper vertex coloring with $\Delta + 1$ colors that can be found via a simple sequential greedy algorithm in linear time and space.

Data Structures and Algorithms

Fisher Efficient Inference of Intractable Models

1 code implementation NeurIPS 2019 Song Liu, Takafumi Kanamori, Wittawat Jitkrittum, Yu Chen

For example, the asymptotic variance of MLE solution attains equality of the asymptotic Cram{\'e}r-Rao lower bound (efficiency bound), which is the minimum possible variance for an unbiased estimator.

Density Ratio Estimation

A Federated Capability-based Access Control Mechanism for Internet of Things (IoTs)

no code implementations1 May 2018 Ronghua Xu, Yu Chen, Erik Blasch, Genshe Chen

Implemented and tested on both resources-constrained devices, like smart sensors and Raspberry PI, and non-resource-constrained devices, like laptops and smart phones, our experimental results demonstrate the feasibility of the proposed FedCAC approach to offer a scalable, lightweight and fine-grained access control solution to IoT systems connected to a system network.

Networking and Internet Architecture

BlendCAC: A BLockchain-ENabled Decentralized Capability-based Access Control for IoTs

no code implementations24 Apr 2018 Ronghua Xu, Yu Chen, Erik Blasch, Genshe Chen

The BlendCAC aims at an effective access control processes to devices, services and information in large scale IoT systems.

Networking and Internet Architecture Cryptography and Security Distributed, Parallel, and Cluster Computing

Cross-domain Human Parsing via Adversarial Feature and Label Adaptation

no code implementations4 Jan 2018 Si Liu, Yao Sun, Defa Zhu, Guanghui Ren, Yu Chen, Jiashi Feng, Jizhong Han

Our proposed model explicitly learns a feature compensation network, which is specialized for mitigating the cross-domain differences.

Human Parsing

Spot the Difference by Object Detection

1 code implementation3 Jan 2018 Junhui Wu, Yun Ye, Yu Chen, Zhi Weng

In this paper, we propose a simple yet effective solution to a change detection task that detects the difference between two images, which we call "spot the difference".

Object Detection

Who is Smarter? Intelligence Measure of Learning-based Cognitive Radios

no code implementations26 Dec 2017 Monireh Dabaghchian, Amir Alipour-Fanid, Songsong Liu, Kai Zeng, Xiaohua LI, Yu Chen

Then we apply factor analysis on the performance data to identify and quantize the intelligence factors and cognitive capabilities of the CR.

FSRNet: End-to-End Learning Face Super-Resolution with Facial Priors

3 code implementations CVPR 2018 Yu Chen, Ying Tai, Xiaoming Liu, Chunhua Shen, Jian Yang

We present a novel deep end-to-end trainable Face Super-Resolution Network (FSRNet), which makes full use of the geometry prior, i. e., facial landmark heatmaps and parsing maps, to super-resolve very low-resolution (LR) face images without well-aligned requirement.

Face Alignment Super-Resolution

Adversarial Learning of Structure-Aware Fully Convolutional Networks for Landmark Localization

no code implementations1 Nov 2017 Yu Chen, Chunhua Shen, Hao Chen, Xiu-Shen Wei, Lingqiao Liu, Jian Yang

In contrast, human vision is able to predict poses by exploiting geometric constraints of landmark point inter-connectivity.

Pose Estimation

KATE: K-Competitive Autoencoder for Text

1 code implementation4 May 2017 Yu Chen, Mohammed J. Zaki

Autoencoders have been successful in learning meaningful representations from image datasets.

Document Classification Topic Models

Ensemble-driven support vector clustering: From ensemble learning to automatic parameter estimation

no code implementations3 Aug 2016 Dong Huang, Chang-Dong Wang, Jian-Huang Lai, Yun Liang, Shan Bian, Yu Chen

Support vector clustering (SVC) is a versatile clustering technique that is able to identify clusters of arbitrary shapes by exploiting the kernel trick.

Ensemble Learning

Inferring Gene Regulatory Network Using An Evolutionary Multi-Objective Method

no code implementations16 Dec 2015 Yu Chen, Xiufen Zou

Inference of gene regulatory networks (GRNs) based on experimental data is a challenging task in bioinformatics.

A binary differential evolution algorithm learning from explored solutions

no code implementations6 Jan 2014 Yu Chen, Weicheng Xie, Xiufen Zou

Although real-coded differential evolution (DE) algorithms can perform well on continuous optimization problems (CoOPs), it is still a challenging task to design an efficient binary-coded DE algorithm.

Joint Grammar and Treebank Development for Mandarin Chinese with HPSG

no code implementations LREC 2012 Yi Zhang, Rui Wang, Yu Chen

We present the ongoing development of MCG, a linguistically deep and precise grammar for Mandarin Chinese together with its accompanying treebank, both based on the linguistic framework of HPSG, and using MRS as the semantic representation.

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