Search Results for author: Yu Chen

Found 152 papers, 50 papers with code

基于情感增强非参数模型的社交媒体观点聚类(A Sentiment Enhanced Nonparametric Model for Social Media Opinion Clustering)

no code implementations CCL 2022 Kan Liu, Yu Chen, Jiarui He

“本文旨在使用文本聚类技术, 将社交媒体文本根据用户主张的观点汇总, 直观呈现网民群体所持有的不同立场。针对社交媒体文本模式复杂与情感丰富等特点, 本文提出使用情感分布增强方法改进现有的非参数短文本聚类算法, 以高斯分布建模文本情感, 捕获文本情感特征的同时能够自动确定聚类簇数量并实现观点聚类。在公开数据集上的实验显示, 该方法在多项聚类指标上取得了超越现有模型的聚类表现, 并在主观性较强的数据集中具有更显著的优势。”

Are Language-Agnostic Sentence Representations Actually Language-Agnostic?

no code implementations RANLP 2021 Yu Chen, Tania Avgustinova

With the emergence of pre-trained multilingual models, multilingual embeddings have been widely applied in various natural language processing tasks.

Sentence Embeddings Translation

Sample-based Dynamic Hierarchical Transformer with Layer and Head Flexibility via Contextual Bandit

no code implementations5 Dec 2023 Fanfei Meng, LeLe Zhang, Yu Chen, Yuxin Wang

Transformer requires a fixed number of layers and heads which makes them inflexible to the complexity of individual samples and expensive in training and inference.

Thompson Sampling

FedEmb: A Vertical and Hybrid Federated Learning Algorithm using Network And Feature Embedding Aggregation

no code implementations30 Nov 2023 Fanfei Meng, LeLe Zhang, Yu Chen, Yuxin Wang

Federated learning (FL) is an emerging paradigm for decentralized training of machine learning models on distributed clients, without revealing the data to the central server.

Federated Learning Privacy Preserving

Interpreting Differentiable Latent States for Healthcare Time-series Data

no code implementations29 Nov 2023 Yu Chen, Nivedita Bijlani, Samaneh Kouchaki, Payam Barnaghi

Understanding the meaning of latent states is crucial for interpreting machine learning models, assuming they capture underlying patterns.

Predicting Patient Outcomes Time Series

SCALAR-NeRF: SCAlable LARge-scale Neural Radiance Fields for Scene Reconstruction

no code implementations28 Nov 2023 Yu Chen, Gim Hee Lee

We enhance the overlapping regions across different blocks by scaling up the bounding boxes of each local block.

Multi-Scale 3D Gaussian Splatting for Anti-Aliased Rendering

no code implementations28 Nov 2023 Zhiwen Yan, Weng Fei Low, Yu Chen, Gim Hee Lee

3D Gaussians have recently emerged as a highly efficient representation for 3D reconstruction and rendering.

3D Reconstruction

Scaling Law of Large Sequential Recommendation Models

no code implementations19 Nov 2023 Gaowei Zhang, Yupeng Hou, Hongyu Lu, Yu Chen, Wayne Xin Zhao, Ji-Rong Wen

We find that scaling up the model size can greatly boost the performance on these challenging tasks, which again verifies the benefits of large recommendation models.

Sequential Recommendation

Adapting Large Language Models by Integrating Collaborative Semantics for Recommendation

1 code implementation15 Nov 2023 Bowen Zheng, Yupeng Hou, Hongyu Lu, Yu Chen, Wayne Xin Zhao, Ming Chen, Ji-Rong Wen

To address this challenge, in this paper, we propose a new LLM-based recommendation model called LC-Rec, which can better integrate language and collaborative semantics for recommender systems.

Quantization Recommendation Systems

Electric Vehicle Aggregation Review: Benefits and Vulnerabilities of Managing a Growing EV Fleet

no code implementations26 Oct 2023 Kelsey Nelson, Javad Mohammadi, Yu Chen, Erik Blasch, Alex Aved, David Ferris, Erika Ardiles Cruz, Philip Morrone

Electric vehicles (EVs) are becoming more popular within the United States, making up an increasingly large portion of the US's electricity consumption.

HateRephrase: Zero- and Few-Shot Reduction of Hate Intensity in Online Posts using Large Language Models

no code implementations21 Oct 2023 Vibhor Agarwal, Yu Chen, Nishanth Sastry

We develop 4 different prompts based on task description, hate definition, few-shot demonstrations and chain-of-thoughts for comprehensive experiments and conduct experiments on open-source LLMs such as LLaMA-1, LLaMA-2 chat, Vicuna as well as OpenAI's GPT-3. 5.

GASCOM: Graph-based Attentive Semantic Context Modeling for Online Conversation Understanding

no code implementations21 Oct 2023 Vibhor Agarwal, Yu Chen, Nishanth Sastry

Specifically, we design two novel algorithms that utilise both the graph structure of the online conversation as well as the semantic information from individual posts for retrieving relevant context nodes from the whole conversation.

Graph Attention Hate Speech Detection

LocSelect: Target Speaker Localization with an Auditory Selective Hearing Mechanism

no code implementations16 Oct 2023 Yu Chen, Xinyuan Qian, Zexu Pan, Kainan Chen, Haizhou Li

The prevailing noise-resistant and reverberation-resistant localization algorithms primarily emphasize separating and providing directional output for each speaker in multi-speaker scenarios, without association with the identity of speakers.

On the Equivalence of Graph Convolution and Mixup

no code implementations29 Sep 2023 Xiaotian Han, Hanqing Zeng, Yu Chen, Shaoliang Nie, Jingzhou Liu, Kanika Narang, Zahra Shakeri, Karthik Abinav Sankararaman, Song Jiang, Madian Khabsa, Qifan Wang, Xia Hu

We establish this equivalence mathematically by demonstrating that graph convolution networks (GCN) and simplified graph convolution (SGC) can be expressed as a form of Mixup.

Data Augmentation

Hide and Seek (HaS): A Lightweight Framework for Prompt Privacy Protection

1 code implementation6 Sep 2023 Yu Chen, Tingxin Li, Huiming Liu, Yang Yu

Numerous companies have started offering services based on large language models (LLM), such as ChatGPT, which inevitably raises privacy concerns as users' prompts are exposed to the model provider.

LM-Infinite: Simple On-the-Fly Length Generalization for Large Language Models

1 code implementation30 Aug 2023 Chi Han, Qifan Wang, Wenhan Xiong, Yu Chen, Heng Ji, Sinong Wang

In these situations, the $\textit{length generalization failure}$ of LLMs on long sequences becomes more prominent.

Text Generation

Rotation-Invariant Completion Network

no code implementations23 Aug 2023 Yu Chen, Pengcheng Shi

To assess the performance of RICNet and existing methods on point clouds with various poses, we applied random transformations to the point clouds in the MVP dataset and conducted experiments on them.

Point Cloud Completion

DReg-NeRF: Deep Registration for Neural Radiance Fields

1 code implementation ICCV 2023 Yu Chen, Gim Hee Lee

Although Neural Radiance Fields (NeRF) is popular in the computer vision community recently, registering multiple NeRFs has yet to gain much attention.

Novel View Synthesis Point Cloud Registration +1

Streaming CTR Prediction: Rethinking Recommendation Task for Real-World Streaming Data

no code implementations14 Jul 2023 Qi-Wei Wang, Hongyu Lu, Yu Chen, Da-Wei Zhou, De-Chuan Zhan, Ming Chen, Han-Jia Ye

The Click-Through Rate (CTR) prediction task is critical in industrial recommender systems, where models are usually deployed on dynamic streaming data in practical applications.

Click-Through Rate Prediction Recommendation Systems

FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods

1 code implementation15 Jun 2023 Xiaotian Han, Jianfeng Chi, Yu Chen, Qifan Wang, Han Zhao, Na Zou, Xia Hu

This paper introduces the Fair Fairness Benchmark (\textsf{FFB}), a benchmarking framework for in-processing group fairness methods.

Benchmarking Fairness

NPVForensics: Jointing Non-critical Phonemes and Visemes for Deepfake Detection

no code implementations12 Jun 2023 Yu Chen, Yang Yu, Rongrong Ni, Yao Zhao, Haoliang Li

Next, we design a phoneme-viseme awareness module for cross-modal feature fusion and representation alignment, so that the modality gap can be reduced and the intrinsic complementarity of the two modalities can be better explored.

DeepFake Detection Face Swapping

Inference and Sampling of Point Processes from Diffusion Excursions

no code implementations1 Jun 2023 Ali Hasan, Yu Chen, Yuting Ng, Mohamed Abdelghani, Anderson Schneider, Vahid Tarokh

In this framework, we relate the return times of a diffusion in a continuous path space to new arrivals of the point process.

Point Processes

Short-term Temporal Dependency Detection under Heterogeneous Event Dynamic with Hawkes Processes

1 code implementation28 May 2023 Yu Chen, Fengpei Li, Anderson Schneider, Yuriy Nevmyvaka, Asohan Amarasingham, Henry Lam

Then we proposed a robust and computationally-efficient method modified from MLE that does not rely on the prior estimation of the heterogeneous intensity and is thus applicable in a data-limited regime (e. g., few-shot, no repeated observations).

AMELI: Enhancing Multimodal Entity Linking with Fine-Grained Attributes

no code implementations24 May 2023 Barry Menglong Yao, Yu Chen, Qifan Wang, Sijia Wang, Minqian Liu, Zhiyang Xu, Licheng Yu, Lifu Huang

We propose attribute-aware multimodal entity linking, where the input is a mention described with a text and image, and the goal is to predict the corresponding target entity from a multimodal knowledge base (KB) where each entity is also described with a text description, a visual image and a set of attributes and values.

Entity Linking

Coarse-to-Fine Contrastive Learning in Image-Text-Graph Space for Improved Vision-Language Compositionality

no code implementations23 May 2023 Harman Singh, Pengchuan Zhang, Qifan Wang, Mengjiao Wang, Wenhan Xiong, Jingfei Du, Yu Chen

Along with this, we propose novel negative mining techniques in the scene graph space for improving attribute binding and relation understanding.

 Ranked #1 on Image Retrieval on CREPE (Vision-Language) (Recall@1 (HN-Comp, UC) metric)

Contrastive Learning Image Retrieval +2

Provably Convergent Schrödinger Bridge with Applications to Probabilistic Time Series Imputation

1 code implementation12 May 2023 Yu Chen, Wei Deng, Shikai Fang, Fengpei Li, Nicole Tianjiao Yang, Yikai Zhang, Kashif Rasul, Shandian Zhe, Anderson Schneider, Yuriy Nevmyvaka

We show that optimizing the transport cost improves the performance and the proposed algorithm achieves the state-of-the-art result in healthcare and environmental data while exhibiting the advantage of exploring both temporal and feature patterns in probabilistic time series imputation.

Imputation Time Series

A Lightweight Recurrent Learning Network for Sustainable Compressed Sensing

1 code implementation23 Apr 2023 Yu Zhou, Yu Chen, Xiao Zhang, Pan Lai, Lei Huang, Jianmin Jiang

While the initial reconstruction sub-network has a hierarchical structure to progressively recover the image, reducing the number of parameters, the residual reconstruction sub-network facilitates recurrent residual feature extraction via recurrent learning to perform both feature fusion and deep reconstructions across different scales.

Scalable Multiple Patterning Layout Decomposition Implemented by a Distribution Evolutionary Algorithm

no code implementations9 Apr 2023 Yu Chen, Yongjian Xu, Ning Xu

As the feature size of semiconductor technology shrinks to 10 nm and beyond, the multiple patterning lithography (MPL) attracts more attention from the industry.

MMVC: Learned Multi-Mode Video Compression with Block-based Prediction Mode Selection and Density-Adaptive Entropy Coding

1 code implementation CVPR 2023 Bowen Liu, Yu Chen, Rakesh Chowdary Machineni, Shiyu Liu, Hun-Seok Kim

In this paper, we propose multi-mode video compression (MMVC), a block wise mode ensemble deep video compression framework that selects the optimal mode for feature domain prediction adapting to different motion patterns.

Benchmarking MS-SSIM +4

Data-Driven Safe Controller Synthesis for Deterministic Systems: A Posteriori Method With Validation Tests

no code implementations3 Apr 2023 Yu Chen, Chao Shang, Xiaolin Huang, Xiang Yin

We first formulate the safety synthesis problem as a robust convex program (RCP) based on notion of control barrier function.

DBARF: Deep Bundle-Adjusting Generalizable Neural Radiance Fields

no code implementations CVPR 2023 Yu Chen, Gim Hee Lee

Recent works such as BARF and GARF can bundle adjust camera poses with neural radiance fields (NeRF) which is based on coordinate-MLPs.

AdaSfM: From Coarse Global to Fine Incremental Adaptive Structure from Motion

no code implementations28 Jan 2023 Yu Chen, Zihao Yu, Shu Song, Tianning Yu, Jianming Li, Gim Hee Lee

Despite the impressive results achieved by many existing Structure from Motion (SfM) approaches, there is still a need to improve the robustness, accuracy, and efficiency on large-scale scenes with many outlier matches and sparse view graphs.

You Don't Know When I Will Arrive: Unpredictable Controller Synthesis for Temporal Logic Tasks

no code implementations23 Nov 2022 Yu Chen, Shuo Yang, Rahul Mangharam, Xiang Yin

This problem is particularly challenging since future information is involved in the synthesis process.

Robot Task Planning

Markov decision processes with maximum entropy rate for Surveillance Tasks

no code implementations23 Nov 2022 Yu Chen, ShaoYuan Li, Xiang Yin

We consider the problem of synthesizing optimal policies for Markov decision processes (MDP) for both utility objective and security constraint.

Temporal-Spatial dependencies ENhanced deep learning model (TSEN) for household leverage series forecasting

no code implementations17 Oct 2022 Hu Yang, Yi Huang, Haijun Wang, Yu Chen

Analyzing both temporal and spatial patterns for an accurate forecasting model for financial time series forecasting is a challenge due to the complex nature of temporal-spatial dynamics: time series from different locations often have distinct patterns; and for the same time series, patterns may vary as time goes by.

Time Series Time Series Forecasting

Predictive Scale-Bridging Simulations through Active Learning

no code implementations20 Sep 2022 Satish Karra, Mohamed Mehana, Nicholas Lubbers, Yu Chen, Abdourahmane Diaw, Javier E. Santos, Aleksandra Pachalieva, Robert S. Pavel, Jeffrey R. Haack, Michael McKerns, Christoph Junghans, Qinjun Kang, Daniel Livescu, Timothy C. Germann, Hari S. Viswanathan

Throughout computational science, there is a growing need to utilize the continual improvements in raw computational horsepower to achieve greater physical fidelity through scale-bridging over brute-force increases in the number of mesh elements.

Active Learning

Effective Multi-User Delay-Constrained Scheduling with Deep Recurrent Reinforcement Learning

1 code implementation30 Aug 2022 Pihe Hu, Ling Pan, Yu Chen, Zhixuan Fang, Longbo Huang

Multi-user delay constrained scheduling is important in many real-world applications including wireless communication, live streaming, and cloud computing.

Cloud Computing reinforcement-learning +2

A Compacted Structure for Cross-domain learning on Monocular Depth and Flow Estimation

no code implementations25 Aug 2022 Yu Chen, Xu Cao, Xiaoyi Lin, Baoru Huang, Xiao-Yun Zhou, Jian-Qing Zheng, Guang-Zhong Yang

A dual-head mechanism is used to predict optical flow for rigid and non-rigid motion based on a divide-and-conquer manner, which significantly improves the optical flow estimation performance.

Autonomous Driving Optical Flow Estimation

DeFakePro: Decentralized DeepFake Attacks Detection using ENF Authentication

no code implementations22 Jul 2022 Deeraj Nagothu, Ronghua Xu, Yu Chen, Erik Blasch, Alexander Aved

The similarity in ENF signal fluctuations is utilized in the PoENF algorithm to authenticate the media broadcasted in conferencing tools.

DeepFake Detection Face Swapping

Real-Time Elderly Monitoring for Senior Safety by Lightweight Human Action Recognition

no code implementations21 Jul 2022 Han Sun, Yu Chen

Real-time monitoring and action recognition are essential to raise an alert timely when abnormal behaviors or unusual activities occur.

Action Recognition Privacy Preserving +1

Nearly Minimax Optimal Reinforcement Learning with Linear Function Approximation

no code implementations23 Jun 2022 Pihe Hu, Yu Chen, Longbo Huang

We study reinforcement learning with linear function approximation where the transition probability and reward functions are linear with respect to a feature mapping $\boldsymbol{\phi}(s, a)$.

reinforcement-learning Reinforcement Learning (RL)

Efficient Deep Visual and Inertial Odometry with Adaptive Visual Modality Selection

1 code implementation12 May 2022 Mingyu Yang, Yu Chen, Hun-Seok Kim

In recent years, deep learning-based approaches for visual-inertial odometry (VIO) have shown remarkable performance outperforming traditional geometric methods.

Pose Estimation

A Distribution Evolutionary Algorithm for the Graph Coloring Problem

no code implementations29 Mar 2022 Yongjian Xu, Huabin Cheng, Ning Xu, Yu Chen, Chengwang Xie

Unlike existing estimation of distribution algorithms where a probability model is updated by generated solutions, DEA-PPM employs a distribution population based on a novel probability model, and an orthogonal exploration strategy is introduced to search the distribution space with the assistance of an refinement strategy.

Combinatorial Optimization

Fast fluorescence lifetime imaging analysis via extreme learning machine

no code implementations25 Mar 2022 Zhenya Zang, Dong Xiao, Quan Wang, Zinuo Li, Wujun Xie, Yu Chen, David Day Uei Li

As there is no back-propagation process for ELM during the training phase, the training speed is much higher than existing neural network approaches.

Edge-computing Efficient Neural Network

Asymptotically Unbiased Estimation for Delayed Feedback Modeling via Label Correction

1 code implementation14 Feb 2022 Yu Chen, Jiaqi Jin, Hui Zhao, Pengjie Wang, Guojun Liu, Jian Xu, Bo Zheng

Moreover, to estimate CVR upon the freshly observed but biased distribution with fake negatives, the importance sampling is widely used to reduce the distribution bias.

Compact Graph Structure Learning via Mutual Information Compression

2 code implementations14 Jan 2022 Nian Liu, Xiao Wang, Lingfei Wu, Yu Chen, Xiaojie Guo, Chuan Shi

Furthermore, we maintain the performance of estimated views and the final view and reduce the mutual information of every two views.

Graph structure learning

CdtGRN: Construction of qualitative time-delayed gene regulatory networks with a deep learning method

no code implementations30 Oct 2021 Ruijie Xu, Lin Zhang, Yu Chen

Therefore, it is of great significance to elucidate the regulation mechanism over time points.

Influence of Binomial Crossover on Approximation Error of Evolutionary Algorithms

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

Although differential evolution (DE) algorithms perform well on a large variety of complicated optimization problems, only a few theoretical studies are focused on the working principle of DE algorithms.

Evolutionary Algorithms

X-GOAL: Multiplex Heterogeneous Graph Prototypical Contrastive Learning

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

X-GOAL is comprised of two components: the GOAL framework, which learns node embeddings for each homogeneous graph layer, and an alignment regularization, which jointly models different layers by aligning layer-specific node embeddings.

Contrastive Learning Graph Learning +2

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

2 code implementations Findings (ACL) 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.

Ranked #10 on Video Retrieval on VATEX (using extra training data)

Language Modelling Retrieval +3

Deep Learning in Latent Space for Video Prediction and Compression

1 code implementation 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 +9

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.

Navigate regression

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

3 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

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

1 code implementation 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

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.

BIG-bench 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.

reinforcement-learning Reinforcement Learning (RL)

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, Sylwan Rahardja

Over the decades, traditional outlier detectors have ignored the group-level factor when calculating outlier scores for objects in data by evaluating only the object-level factor, failing to capture the collective outliers.

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.


Discriminative Representation Loss (DRL): A More Efficient Approach than Gradient Re-Projection in Continual Learning

no code implementations28 Sep 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

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.

Benchmarking Continual Learning

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

2 code implementations 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

Semi-Discriminative Representation Loss for Online Continual Learning

1 code implementation19 Jun 2020 Yu Chen, Tom Diethe, Peter Flach

The use of episodic memory in continual learning has demonstrated effectiveness for 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 Retrieval +1

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 +1

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 +3

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.

Descriptive Face Recognition +1

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).

Evolutionary Algorithms

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 Clustering

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

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 Graph structure learning +2

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

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 +2

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.

Clustering Test

Continual Density Ratio Estimation (CDRE): A new method for evaluating generative models in continual learning

no code implementations25 Sep 2019 Yu Chen, Song Liu, Tom Diethe, Peter Flach

We propose a new method Continual Density Ratio Estimation (CDRE), which can estimate density ratios between a target distribution of real samples and a distribution of samples generated by a model while the model is changing over time and the data of the target distribution is not available after a certain time point.

Continual Learning Density Ratio Estimation

Iterative Deep Graph Learning for Graph Neural Networks

no code implementations25 Sep 2019 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 learning graph structure and graph embedding simultaneously.

Graph Embedding Graph Learning +2

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.

Evolutionary Algorithms

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 Object Detection +1

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 Test +1

Seeing is Not Believing: Camouflage Attacks on Image Scaling Algorithms

no code implementations USENIX Security Symposium 2019 Qixue Xiao, Yufei Chen, Chao Shen, Yu Chen, Kang Li

We also present an algorithm that can successfully enable attacks against famous cloud-based image services (such as those from Microsoft Azure, Aliyun, Baidu, and Tencent) and cause obvious misclassification effects, even when the details of image processing (such as the exact scaling algorithm and scale dimension parameters) are hidden in the cloud.

Data Poisoning Image Classification

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.

Graph structure learning 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 +2

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 Task 2

$β^3$-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.

Clustering 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 +3

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.

Evolutionary Algorithms

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.

Evolutionary Algorithms

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".

Change Detection object-detection +1

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

4 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 Retrieval +1

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.

Clustering 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.

Evolutionary Algorithms

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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