Search Results for author: Yi Liu

Found 137 papers, 41 papers with code

CLIO: Role-interactive Multi-event Head Attention Network for Document-level Event Extraction

no code implementations COLING 2022 Yubing Ren, Yanan Cao, Fang Fang, Ping Guo, Zheng Lin, Wei Ma, Yi Liu

Transforming the large amounts of unstructured text on the Internet into structured event knowledge is a critical, yet unsolved goal of NLP, especially when addressing document-level text.

Document-level Event Extraction Event Extraction

Towards Better Entity Linking with Multi-View Enhanced Distillation

1 code implementation27 May 2023 Yi Liu, Yuan Tian, Jianxun Lian, Xinlong Wang, Yanan Cao, Fang Fang, Wen Zhang, Haizhen Huang, Denvy Deng, Qi Zhang

Aiming at learning entity representations that can match divergent mentions, this paper proposes a Multi-View Enhanced Distillation (MVD) framework, which can effectively transfer knowledge of multiple fine-grained and mention-relevant parts within entities from cross-encoders to dual-encoders.

Entity Linking Knowledge Distillation +1

DeepGate2: Functionality-Aware Circuit Representation Learning

no code implementations25 May 2023 Zhengyuan Shi, Hongyang Pan, Sadaf Khan, Min Li, Yi Liu, Junhua Huang, Hui-Ling Zhen, Mingxuan Yuan, Zhufei Chu, Qiang Xu

Circuit representation learning aims to obtain neural representations of circuit elements and has emerged as a promising research direction that can be applied to various EDA and logic reasoning tasks.

Representation Learning

Jailbreaking ChatGPT via Prompt Engineering: An Empirical Study

no code implementations23 May 2023 Yi Liu, Gelei Deng, Zhengzi Xu, Yuekang Li, Yaowen Zheng, Ying Zhang, Lida Zhao, Tianwei Zhang, Yang Liu

Our study investigates three key research questions: (1) the number of different prompt types that can jailbreak LLMs, (2) the effectiveness of jailbreak prompts in circumventing LLM constraints, and (3) the resilience of ChatGPT against these jailbreak prompts.

Prompt Engineering

Automatic Code Summarization via ChatGPT: How Far Are We?

no code implementations22 May 2023 Weisong Sun, Chunrong Fang, Yudu You, Yun Miao, Yi Liu, Yuekang Li, Gelei Deng, Shenghan Huang, Yuchen Chen, Quanjun Zhang, Hanwei Qian, Yang Liu, Zhenyu Chen

To support software developers in understanding and maintaining programs, various automatic code summarization techniques have been proposed to generate a concise natural language comment for a given code snippet.

Code Summarization

Communication Efficient Federated Learning for Multilingual Neural Machine Translation with Adapter

1 code implementation21 May 2023 Yi Liu, Xiaohan Bi, Lei LI, Sishuo Chen, Wenkai Yang, Xu sun

However, as pre-trained language models (PLMs) continue to increase in size, the communication cost for transmitting parameters during synchronization has become a training speed bottleneck.

Federated Learning Machine Translation +1

SFP: Spurious Feature-targeted Pruning for Out-of-Distribution Generalization

no code implementations19 May 2023 Yingchun Wang, Jingcai Guo, Yi Liu, Song Guo, Weizhan Zhang, Xiangyong Cao, Qinghua Zheng

Based on the idea that in-distribution (ID) data with spurious features may have a lower experience risk, in this paper, we propose a novel Spurious Feature-targeted model Pruning framework, dubbed SFP, to automatically explore invariant substructures without referring to the above drawbacks.

Out-of-Distribution Generalization

SegGPT Meets Co-Saliency Scene

no code implementations8 May 2023 Yi Liu, Shoukun Xu, Dingwen Zhang, Jungong Han

Co-salient object detection targets at detecting co-existed salient objects among a group of images.

Co-Salient Object Detection object-detection +1

AsConvSR: Fast and Lightweight Super-Resolution Network with Assembled Convolutions

no code implementations5 May 2023 Jiaming Guo, Xueyi Zou, Yuyi Chen, Yi Liu, Jia Hao, Jianzhuang Liu, Youliang Yan

In recent years, videos and images in 720p (HD), 1080p (FHD) and 4K (UHD) resolution have become more popular for display devices such as TVs, mobile phones and VR.


DETRs Beat YOLOs on Real-time Object Detection

3 code implementations17 Apr 2023 Wenyu Lv, Shangliang Xu, Yian Zhao, Guanzhong Wang, Jinman Wei, Cheng Cui, Yuning Du, Qingqing Dang, Yi Liu

In this paper, we first analyze the influence of NMS in modern real-time object detectors on inference speed, and establish an end-to-end speed benchmark.

2D object detection object-detection +1

PP-MobileSeg: Explore the Fast and Accurate Semantic Segmentation Model on Mobile Devices

1 code implementation11 Apr 2023 Shiyu Tang, Ting Sun, Juncai Peng, Guowei Chen, Yuying Hao, Manhui Lin, Zhihong Xiao, Jiangbin You, Yi Liu

To address this issue, we propose PP-MobileSeg, a semantic segmentation model that achieves state-of-the-art performance on mobile devices.

Semantic Segmentation

Object-Aware Distillation Pyramid for Open-Vocabulary Object Detection

1 code implementation CVPR 2023 Luting Wang, Yi Liu, Penghui Du, Zihan Ding, Yue Liao, Qiaosong Qi, Biaolong Chen, Si Liu

When extracting object knowledge from PVLMs, the former adaptively transforms object proposals and adopts object-aware mask attention to obtain precise and complete knowledge of objects.

Open Vocabulary Object Detection

Angel-PTM: A Scalable and Economical Large-scale Pre-training System in Tencent

no code implementations6 Mar 2023 Xiaonan Nie, Yi Liu, Fangcheng Fu, Jinbao Xue, Dian Jiao, Xupeng Miao, Yangyu Tao, Bin Cui

Recent years have witnessed the unprecedented achievements of large-scale pre-trained models, especially the Transformer models.

Management Scheduling

Video4MRI: An Empirical Study on Brain Magnetic Resonance Image Analytics with CNN-based Video Classification Frameworks

no code implementations24 Feb 2023 Yuxuan Zhang, Qingzhong Wang, Jiang Bian, Yi Liu, Yanwu Xu, Dejing Dou, Haoyi Xiong

Due to the high similarity between MRI data and videos, we conduct extensive empirical studies on video recognition techniques for MRI classification to answer the questions: (1) can we directly use video recognition models for MRI classification, (2) which model is more appropriate for MRI, (3) are the common tricks like data augmentation in video recognition still useful for MRI classification?

Classification Data Augmentation +3

Knowledge Enhancement for Contrastive Multi-Behavior Recommendation

no code implementations13 Jan 2023 Hongrui Xuan, Yi Liu, Bohan Li, Hongzhi Yin

In particular, we design the multi-behavior learning module to extract users' personalized behavior information for user-embedding enhancement, and utilize knowledge graph in the knowledge enhancement module to derive more robust knowledge-aware representations for items.

Contrastive Learning Recommendation Systems +1

Efficient Preference-Based Reinforcement Learning Using Learned Dynamics Models

no code implementations11 Jan 2023 Yi Liu, Gaurav Datta, Ellen Novoseller, Daniel S. Brown

Preference-based reinforcement learning (PbRL) can enable robots to learn to perform tasks based on an individual's preferences without requiring a hand-crafted reward function.

reinforcement-learning Reinforcement Learning (RL)

SIRL: Similarity-based Implicit Representation Learning

no code implementations2 Jan 2023 Andreea Bobu, Yi Liu, Rohin Shah, Daniel S. Brown, Anca D. Dragan

This, in turn, is what enables the robot to disambiguate between what needs to go into the representation versus what is spurious, as well as what aspects of behavior can be compressed together versus not.

Contrastive Learning Data Augmentation +1

Efficient Stein Variational Inference for Reliable Distribution-lossless Network Pruning

no code implementations7 Dec 2022 Yingchun Wang, Song Guo, Jingcai Guo, Weizhan Zhang, Yida Xu, Jie Zhang, Yi Liu

Extensive experiments based on small Cifar-10 and large-scaled ImageNet demonstrate that our method can obtain sparser networks with great generalization performance while providing quantified reliability for the pruned model.

Network Pruning Variational Inference

InternVideo: General Video Foundation Models via Generative and Discriminative Learning

1 code implementation6 Dec 2022 Yi Wang, Kunchang Li, Yizhuo Li, Yinan He, Bingkun Huang, Zhiyu Zhao, Hongjie Zhang, Jilan Xu, Yi Liu, Zun Wang, Sen Xing, Guo Chen, Junting Pan, Jiashuo Yu, Yali Wang, LiMin Wang, Yu Qiao

Specifically, InternVideo efficiently explores masked video modeling and video-language contrastive learning as the pretraining objectives, and selectively coordinates video representations of these two complementary frameworks in a learnable manner to boost various video applications.

Action Classification Contrastive Learning +8

CaDM: Codec-aware Diffusion Modeling for Neural-enhanced Video Streaming

no code implementations15 Nov 2022 Qihua Zhou, Ruibin Li, Song Guo, Peiran Dong, Yi Liu, Jingcai Guo, Zhenda Xu

Recent years have witnessed the dramatic growth of Internet video traffic, where the video bitstreams are often compressed and delivered in low quality to fit the streamer's uplink bandwidth.

Denoising Super-Resolution

Feature Correlation-guided Knowledge Transfer for Federated Self-supervised Learning

no code implementations14 Nov 2022 Yi Liu, Song Guo, Jie Zhang, Qihua Zhou, Yingchun Wang, Xiaohan Zhao

We prove that FedFoA is a model-agnostic training framework and can be easily compatible with state-of-the-art unsupervised FL methods.

Federated Learning Knowledge Distillation +3

PP-YOLOE-R: An Efficient Anchor-Free Rotated Object Detector

2 code implementations4 Nov 2022 Xinxin Wang, Guanzhong Wang, Qingqing Dang, Yi Liu, Xiaoguang Hu, dianhai yu

With multi-scale training and testing, PP-YOLOE-R-l and PP-YOLOE-R-x further improve the detection precision to 80. 02 and 80. 73 mAP.

object-detection Object Detection In Aerial Images +2

MCSCSet: A Specialist-annotated Dataset for Medical-domain Chinese Spelling Correction

1 code implementation21 Oct 2022 Wangjie Jiang, Zhihao Ye, Zijing Ou, Ruihui Zhao, Jianguang Zheng, Yi Liu, Siheng Li, Bang Liu, Yujiu Yang, Yefeng Zheng

In this work, we define the task of Medical-domain Chinese Spelling Correction and propose MCSCSet, a large scale specialist-annotated dataset that contains about 200k samples.

Optical Character Recognition (OCR) Spelling Correction

VideoPipe 2022 Challenge: Real-World Video Understanding for Urban Pipe Inspection

no code implementations20 Oct 2022 Yi Liu, Xuan Zhang, Ying Li, Guixin Liang, Yabing Jiang, Lixia Qiu, Haiping Tang, Fei Xie, Wei Yao, Yi Dai, Yu Qiao, Yali Wang

For this reason, we propose to advance research areas of video understanding, with a shift from traditional action recognition to industrial anomaly analysis.

Temporal Defect Localization Video Defect Classification

EISeg: An Efficient Interactive Segmentation Tool based on PaddlePaddle

1 code implementation17 Oct 2022 Yuying Hao, Yi Liu, Yizhou Chen, Lin Han, Juncai Peng, Shiyu Tang, Guowei Chen, Zewu Wu, Zeyu Chen, Baohua Lai

In recent years, the rapid development of deep learning has brought great advancements to image and video segmentation methods based on neural networks.

Image Segmentation Interactive Segmentation +3

Boosting the Transferability of Adversarial Attacks with Reverse Adversarial Perturbation

2 code implementations12 Oct 2022 Zeyu Qin, Yanbo Fan, Yi Liu, Li Shen, Yong Zhang, Jue Wang, Baoyuan Wu

Furthermore, RAP can be naturally combined with many existing black-box attack techniques, to further boost the transferability.

Adversarial Attack

PP-StructureV2: A Stronger Document Analysis System

1 code implementation11 Oct 2022 Chenxia Li, Ruoyu Guo, Jun Zhou, Mengtao An, Yuning Du, Lingfeng Zhu, Yi Liu, Xiaoguang Hu, dianhai yu

For Table Recognition model, we utilize PP-LCNet, CSP-PAN and SLAHead to optimize the backbone module, feature fusion module and decoding module, respectively, which improved the table structure accuracy by 6\% with comparable inference speed.

Key Information Extraction Knowledge Distillation +2

Periodic Graph Transformers for Crystal Material Property Prediction

2 code implementations23 Sep 2022 Keqiang Yan, Yi Liu, Yuchao Lin, Shuiwang Ji

Our Matformer is designed to be invariant to periodicity and can capture repeating patterns explicitly.

Band Gap Formation Energy +1

A Nonparametric Contextual Bandit with Arm-level Eligibility Control for Customer Service Routing

no code implementations8 Sep 2022 Ruofeng Wen, Wenjun Zeng, Yi Liu

Routing contacts to eligible SMEs turns out to be a non-trivial problem because SMEs' domain eligibility is subject to training quality and can change over time.

Thompson Sampling

DeepGen: Diverse Search Ad Generation and Real-Time Customization

no code implementations6 Aug 2022 Konstantin Golobokov, Junyi Chai, Victor Ye Dong, Mandy Gu, Bingyu Chi, Jie Cao, Yulan Yan, Yi Liu

In addition, our system creates a customized ad in real-time in response to the user's search query, therefore highlighting different aspects of the same product based on what the user is looking for.

Text Generation

Ultra-low Latency Adaptive Local Binary Spiking Neural Network with Accuracy Loss Estimator

no code implementations31 Jul 2022 Changqing Xu, Yijian Pei, Zili Wu, Yi Liu, YinTang Yang

Spiking neural network (SNN) is a brain-inspired model which has more spatio-temporal information processing capacity and computational energy efficiency.


Learning Hierarchical Protein Representations via Complete 3D Graph Networks

1 code implementation26 Jul 2022 Limei Wang, Haoran Liu, Yi Liu, Jerry Kurtin, Shuiwang Ji

In this work, we propose to develop a novel hierarchical graph network, known as ProNet, to capture the relations.

Representation Learning

An Ultra-low Power TinyML System for Real-time Visual Processing at Edge

no code implementations11 Jul 2022 Kunran Xu, Huawei Zhang, Yishi Li, Yuhao Zhang, Rui Lai, Yi Liu

Tiny machine learning (TinyML), executing AI workloads on resource and power strictly restricted systems, is an important and challenging topic.

object-detection Object Detection

Distilling Ensemble of Explanations for Weakly-Supervised Pre-Training of Image Segmentation Models

1 code implementation4 Jul 2022 Xuhong LI, Haoyi Xiong, Yi Liu, Dingfu Zhou, Zeyu Chen, Yaqing Wang, Dejing Dou

Though image classification datasets could provide the backbone networks with rich visual features and discriminative ability, they are incapable of fully pre-training the target model (i. e., backbone+segmentation modules) in an end-to-end manner.

Classification Image Classification +2

Assessing the Effects of Hyperparameters on Knowledge Graph Embedding Quality

1 code implementation1 Jul 2022 Oliver Lloyd, Yi Liu, Tom Gaunt

We regressed the embedding quality on those hyperparameter configurations, using this model to generate Sobol sensitivity indices for each of the hyperparameters.

Knowledge Graph Embedding Knowledge Graphs +2

Tell Me the Evidence? Dual Visual-Linguistic Interaction for Answer Grounding

no code implementations21 Jun 2022 Junwen Pan, Guanlin Chen, Yi Liu, Jiexiang Wang, Cheng Bian, Pengfei Zhu, Zhicheng Zhang

Answer grounding aims to reveal the visual evidence for visual question answering (VQA), which entails highlighting relevant positions in the image when answering questions about images.

Question Answering Visual Grounding +1

ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs

1 code implementation17 Jun 2022 Limei Wang, Yi Liu, Yuchao Lin, Haoran Liu, Shuiwang Ji

To incorporate 3D information completely and efficiently, we propose a novel message passing scheme that operates within 1-hop neighborhood.

Multiple Domain Cyberspace Attack and Defense Game Based on Reward Randomization Reinforcement Learning

no code implementations23 May 2022 Lei Zhang, Yu Pan, Yi Liu, Qibin Zheng, Zhisong Pan

In order to improve the defense ability of defender, a game model based on reward randomization reinforcement learning is proposed.

reinforcement-learning Reinforcement Learning (RL)

Improved-Flow Warp Module for Remote Sensing Semantic Segmentation

no code implementations9 May 2022 Yinjie Zhang, Yi Liu, Wei Guo

Second, the offsets help with the low-resolution deep feature up-sampling process to improve the feature accordance, which boosts the accuracy of semantic segmentation.

Semantic Segmentation

Rotated Object Detection via Scale-invariant Mahalanobis Distance in Aerial Images

no code implementations2 Apr 2022 Siyang Wen, Wei Guo, Yi Liu, Ruijie Wu

The eight-parameter (coordinates of box vectors) methods in rotated object detection usually use ln-norm losses (L1 loss, L2 loss, and smooth L1 loss) as loss functions.

object-detection Object Detection In Aerial Images

Ultra-low Latency Spiking Neural Networks with Spatio-Temporal Compression and Synaptic Convolutional Block

no code implementations18 Mar 2022 Changqing Xu, Yi Liu, YinTang Yang

We evaluate the proposed method for event streams classification tasks on neuromorphic N-MNIST, CIFAR10-DVS, DVS128 gesture datasets.


The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining

no code implementations14 Mar 2022 Yi Liu, Lei Xu, Xingliang Yuan, Cong Wang, Bo Li

Existing machine unlearning techniques focus on centralized training, where access to all holders' training data is a must for the server to conduct the unlearning process.

Federated Learning

Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization

no code implementations4 Feb 2022 Yifeng Zheng, Shangqi Lai, Yi Liu, Xingliang Yuan, Xun Yi, Cong Wang

In this paper, we present a system design which offers efficient protection of individual model updates throughout the learning procedure, allowing clients to only provide obscured model updates while a cloud server can still perform the aggregation.

Federated Learning

Distributional Reinforcement Learning via Sinkhorn Iterations

no code implementations1 Feb 2022 Ke Sun, Yingnan Zhao, Yi Liu, Wulong Liu, Bei Jiang, Linglong Kong

Distributional reinforcement learning~(RL) is a class of state-of-the-art algorithms that estimate the entire distribution of the total return rather than only its expectation.

Atari Games Distributional Reinforcement Learning +2

Evolutionary Action Selection for Gradient-based Policy Learning

no code implementations12 Jan 2022 Yan Ma, Tianxing Liu, Bingsheng Wei, Yi Liu, Kang Xu, Wei Li

Evolutionary Algorithms (EAs) and Deep Reinforcement Learning (DRL) have recently been integrated to take the advantage of the both methods for better exploration and exploitation. The evolutionary part in these hybrid methods maintains a population of policy networks. However, existing methods focus on optimizing the parameters of policy network, which is usually high-dimensional and tricky for EA. In this paper, we shift the target of evolution from high-dimensional parameter space to low-dimensional action space. We propose Evolutionary Action Selection-Twin Delayed Deep Deterministic Policy Gradient (EAS-TD3), a novel hybrid method of EA and DRL. In EAS, we focus on optimizing the action chosen by the policy network and attempt to obtain high-quality actions to promote policy learning through an evolutionary algorithm.

Continuous Control

FamilySeer: Towards Optimized Tensor Codes by Exploiting Computation Subgraph Similarity

no code implementations1 Jan 2022 Shanjun Zhang, Mingzhen Li, Hailong Yang, Yi Liu, Zhongzhi Luan, Depei Qian

Currently, the DL compilers partition the input DL models into several subgraphs and leverage the auto-tuning to find the optimal tensor codes of these subgraphs.

PP-HumanSeg: Connectivity-Aware Portrait Segmentation with a Large-Scale Teleconferencing Video Dataset

1 code implementation14 Dec 2021 Lutao Chu, Yi Liu, Zewu Wu, Shiyu Tang, Guowei Chen, Yuying Hao, Juncai Peng, Zhiliang Yu, Zeyu Chen, Baohua Lai, Haoyi Xiong

This work is the first to construct a large-scale video portrait dataset that contains 291 videos from 23 conference scenes with 14K fine-labeled frames and extensions to multi-camera teleconferencing.

Portrait Segmentation Semantic Segmentation

Direct Training via Backpropagation for Ultra-low Latency Spiking Neural Networks with Multi-threshold

no code implementations25 Nov 2021 Changqing Xu, Yi Liu, YinTang Yang

In our proposed training method, we proposed three approximated derivative for spike activity to solve the problem of the non-differentiable issue which cause difficulties for direct training SNNs based on BP.

Damped Anderson Mixing for Deep Reinforcement Learning: Acceleration, Convergence, and Stabilization

no code implementations NeurIPS 2021 Ke Sun, Yafei Wang, Yi Liu, Yingnan Zhao, Bo Pan, Shangling Jui, Bei Jiang, Linglong Kong

Anderson mixing has been heuristically applied to reinforcement learning (RL) algorithms for accelerating convergence and improving the sampling efficiency of deep RL.

reinforcement-learning Reinforcement Learning (RL)

Locally Adaptive Structure and Texture Similarity for Image Quality Assessment

no code implementations16 Oct 2021 Keyan Ding, Yi Liu, Xueyi Zou, Shiqi Wang, Kede Ma

The latest advances in full-reference image quality assessment (IQA) involve unifying structure and texture similarity based on deep representations.

Image Quality Assessment Image Super-Resolution

Resource-constrained Federated Edge Learning with Heterogeneous Data: Formulation and Analysis

no code implementations14 Oct 2021 Yi Liu, Yuanshao Zhu, James J. Q. Yu

Similarly, due to the heterogeneity of the connected remote devices, FEEL faces the challenge of heterogeneous data and non-IID (Independent and Identically Distributed) data.

Binary Classification Ensemble Learning +1

Dyn-Backdoor: Backdoor Attack on Dynamic Link Prediction

no code implementations8 Oct 2021 Jinyin Chen, Haiyang Xiong, Haibin Zheng, Jian Zhang, Guodong Jiang, Yi Liu

Backdoor attacks induce the DLP methods to make wrong prediction by the malicious training data, i. e., generating a subgraph sequence as the trigger and embedding it to the training data.

Backdoor Attack Dynamic Link Prediction

Interpreting Distributional Reinforcement Learning: A Regularization Perspective

no code implementations7 Oct 2021 Ke Sun, Yingnan Zhao, Yi Liu, Enze Shi, Yafei Wang, Xiaodong Yan, Bei Jiang, Linglong Kong

Distributional reinforcement learning~(RL) is a class of state-of-the-art algorithms that estimate the whole distribution of the total return rather than only its expectation.

Atari Games Distributional Reinforcement Learning +2

Gaussian Differential Privacy Transformation: from identification to application

no code implementations29 Sep 2021 Yi Liu, Ke Sun, Bei Jiang, Linglong Kong

Gaussian differential privacy (GDP) is a single-parameter family of privacy notions that provides coherent guarantees to avoid the exposure of individuals from machine learning models.

Towards Understanding Distributional Reinforcement Learning: Regularization, Optimization, Acceleration and Sinkhorn Algorithm

no code implementations29 Sep 2021 Ke Sun, Yingnan Zhao, Yi Liu, Enze Shi, Yafei Wang, Aref Sadeghi, Xiaodong Yan, Bei Jiang, Linglong Kong

Distributional reinforcement learning~(RL) is a class of state-of-the-art algorithms that estimate the whole distribution of the total return rather than only its expectation.

Atari Games Distributional Reinforcement Learning +2

Exploring the Robustness of Distributional Reinforcement Learning against Noisy State Observations

no code implementations29 Sep 2021 Ke Sun, Yi Liu, Yingnan Zhao, Hengshuai Yao, Shangling Jui, Linglong Kong

In real scenarios, state observations that an agent observes may contain measurement errors or adversarial noises, misleading the agent to take suboptimal actions or even collapse while training.

Distributional Reinforcement Learning reinforcement-learning +1

BioCopy: A Plug-And-Play Span Copy Mechanism in Seq2Seq Models

no code implementations EMNLP (sustainlp) 2021 Yi Liu, Guoan Zhang, Puning Yu, Jianlin Su, Shengfeng Pan

Copy mechanisms explicitly obtain unchanged tokens from the source (input) sequence to generate the target (output) sequence under the neural seq2seq framework.


How Does Knowledge Graph Embedding Extrapolate to Unseen Data: A Semantic Evidence View

1 code implementation24 Sep 2021 Ren Li, Yanan Cao, Qiannan Zhu, Guanqun Bi, Fang Fang, Yi Liu, Qian Li

However, most existing KGE works focus on the design of delicate triple modeling function, which mainly tells us how to measure the plausibility of observed triples, but offers limited explanation of why the methods can extrapolate to unseen data, and what are the important factors to help KGE extrapolate.

Knowledge Graph Completion Knowledge Graph Embedding +1

Exploring the Training Robustness of Distributional Reinforcement Learning against Noisy State Observations

no code implementations17 Sep 2021 Ke Sun, Yi Liu, Yingnan Zhao, Hengshuai Yao, Shangling Jui, Linglong Kong

In real scenarios, state observations that an agent observes may contain measurement errors or adversarial noises, misleading the agent to take suboptimal actions or even collapse while training.

Density Estimation Distributional Reinforcement Learning +2

BoA-PTA, A Bayesian Optimization Accelerated Error-Free SPICE Solver

no code implementations31 Jul 2021 Wei W. Xing, Xiang Jin, Yi Liu, Dan Niu, Weishen Zhao, Zhou Jin

One of the greatest challenges in IC design is the repeated executions of computationally expensive SPICE simulations, particularly when highly complex chip testing/verification is involved.

Bayesian Optimization Variational Inference

EGC2: Enhanced Graph Classification with Easy Graph Compression

1 code implementation16 Jul 2021 Jinyin Chen, Haiyang Xiong, Haibin Zhenga, Dunjie Zhang, Jian Zhang, Mingwei Jia, Yi Liu

To achieve lower-complexity defense applied to graph classification models, EGC2 utilizes a centrality-based edge-importance index to compress the graphs, filtering out trivial structures and adversarial perturbations in the input graphs, thus improving the model's robustness.

Graph Classification

A Map of Bandits for E-commerce

no code implementations1 Jul 2021 Yi Liu, Lihong Li

The rich body of Bandit literature not only offers a diverse toolbox of algorithms, but also makes it hard for a practitioner to find the right solution to solve the problem at hand.


Mask-Embedded Discriminator With Region-Based Semantic Regularization for Semi-Supervised Class-Conditional Image Synthesis

no code implementations CVPR 2021 Yi Liu, Xiaoyang Huo, Tianyi Chen, Xiangping Zeng, Si Wu, Zhiwen Yu, Hau-San Wong

Semi-supervised generative learning (SSGL) makes use of unlabeled data to achieve a trade-off between the data collection/annotation effort and generation performance, when adequate labeled data are not available.

Image Generation

Optical Mouse: 3D Mouse Pose From Single-View Video

no code implementations17 Jun 2021 Bo Hu, Bryan Seybold, Shan Yang, David Ross, Avneesh Sud, Graham Ruby, Yi Liu

We present a method to infer the 3D pose of mice, including the limbs and feet, from monocular videos.

Machine Learning Regression based Single Event Transient Modeling Method for Circuit-Level Simulation

no code implementations22 May 2021 Changqing Xu, Yi Liu, XinFang Liao, JiaLiang Cheng, YinTang Yang

A multilayer feedfordward neural network is used to build the SET pulse current model by learning the data from TCAD simulation.

BIG-bench Machine Learning regression

DIG: A Turnkey Library for Diving into Graph Deep Learning Research

1 code implementation23 Mar 2021 Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Haiyang Yu, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora Oztekin, Xuan Zhang, Shuiwang Ji

Although there exist several libraries for deep learning on graphs, they are aiming at implementing basic operations for graph deep learning.

Benchmarking Graph Generation +1

The ADENUIM Telescope- A new beam telescope for the DESY II Test Beam Facility

no code implementations22 Feb 2021 Yi Liu, Yao Teng, Chenfei Yang, Changqing Feng, Ingrid-Maria Gregor, Lennart Huth, Marcel Stanitzki

The coincident signal of all scintillators is used as trigger and then used as a trigger and distributed to the entire system, including all the telescope planes and any devices under test from test beam users.

Instrumentation and Detectors Instrumentation and Methods for Astrophysics High Energy Physics - Experiment

Spherical Message Passing for 3D Graph Networks

1 code implementation ICLR 2022 Yi Liu, Limei Wang, Meng Liu, Xuan Zhang, Bora Oztekin, Shuiwang Ji

Based on such observations, we propose the spherical message passing (SMP) as a novel and powerful scheme for 3D molecular learning.

Representation Learning

PaddleSeg: A High-Efficient Development Toolkit for Image Segmentation

1 code implementation15 Jan 2021 Yi Liu, Lutao Chu, Guowei Chen, Zewu Wu, Zeyu Chen, Baohua Lai, Yuying Hao

The toolkit aims to help both developers and researchers in the whole process of designing segmentation models, training models, optimizing performance and inference speed, and deploying models.

Autonomous Driving Human Part Segmentation +4

A Multi-Stage Attentive Transfer Learning Framework for Improving COVID-19 Diagnosis

no code implementations14 Jan 2021 Yi Liu, Shuiwang Ji

The method is then integrated to the last stage of the proposed transfer learning framework to reuse the complex patterns learned from the same CT images.

Computed Tomography (CT) COVID-19 Diagnosis +3

CleftNet: Augmented Deep Learning for Synaptic Cleft Detection from Brain Electron Microscopy

no code implementations12 Jan 2021 Yi Liu, Shuiwang Ji

The effectiveness of our methods is evaluated on both online and offline tasks.

Social Media, Content Moderation, and Technology

no code implementations12 Jan 2021 Yi Liu, Pinar Yildirim, Z. John Zhang

This means that platforms under different revenue models can have different incentives to improve their content moderation technology.


Semi-Supervised Single-Stage Controllable GANs for Conditional Fine-Grained Image Generation

no code implementations ICCV 2021 Tianyi Chen, Yi Liu, Yunfei Zhang, Si Wu, Yong Xu, Feng Liangbing, Hau San Wong

To ensure disentanglement among the variables, we maximize mutual information between the class-independent variable and synthesized images, map real images to the latent space of a generator to perform consistency regularization of cross-class attributes, and incorporate class semantic-based regularization into a discriminator's feature space.

Disentanglement Image Generation

Poisoning Semi-supervised Federated Learning via Unlabeled Data: Attacks and Defenses

no code implementations8 Dec 2020 Yi Liu, Xingliang Yuan, Ruihui Zhao, Cong Wang, Dusit Niyato, Yefeng Zheng

Extensive case studies have shown that our attacks are effective on different datasets and common semi-supervised learning methods.

Federated Learning Quantization

Towards Communication-efficient and Attack-Resistant Federated Edge Learning for Industrial Internet of Things

no code implementations8 Dec 2020 Yi Liu, Ruihui Zhao, Jiawen Kang, Abdulsalam Yassine, Dusit Niyato, Jialiang Peng

Second, we propose an asynchronous local differential privacy mechanism, which improves communication efficiency and mitigates gradient leakage attacks by adding well-designed noise to the gradients of edge nodes.


A Systematic Literature Review on Federated Learning: From A Model Quality Perspective

no code implementations1 Dec 2020 Yi Liu, Li Zhang, Ning Ge, Guanghao Li

In this process, the server uses an incentive mechanism to encourage clients to contribute high-quality and large-volume data to improve the global model.

Federated Learning

Topology-Aware Graph Pooling Networks

no code implementations19 Oct 2020 Hongyang Gao, Yi Liu, Shuiwang Ji

In addition, graph topology is incorporated in global voting to compute the importance score of each node globally in the entire graph.

Graph Classification

Large-Scale Analysis of Iliopsoas Muscle Volumes in the UK Biobank

1 code implementation12 Aug 2020 Julie Fitzpatrick, Nicolas Basty, Madeleine Cule, Yi Liu, Jimmy D. Bell, E. Louise Thomas, Brandon Whitcher

We also found that iliopsoas volume was significantly related to height, BMI and age, and that there was an acceleration in muscle volume decrease in men with age.

Scalable and Communication-efficient Decentralized Federated Edge Learning with Multi-blockchain Framework

no code implementations10 Aug 2020 Jiawen Kang, Zehui Xiong, Chunxiao Jiang, Yi Liu, Song Guo, Yang Zhang, Dusit Niyato, Cyril Leung, Chunyan Miao

This framework can achieve scalable and flexible decentralized FEL by individually manage local model updates or model sharing records for performance isolation.

Cryptography and Security

PR-NN: RNN-based Detection for Coded Partial-Response Channels

2 code implementations30 Jul 2020 Simeng Zheng, Yi Liu, Paul H. Siegel

In this paper, we investigate the use of recurrent neural network (RNN)-based detection of magnetic recording channels with inter-symbol interference (ISI).

Federated Learning in the Sky: Aerial-Ground Air Quality Sensing Framework with UAV Swarms

no code implementations23 Jul 2020 Yi Liu, Jiangtian Nie, Xuandi Li, Syed Hassan Ahmed, Wei Yang Bryan Lim, Chunyan Miao

To this end, this paper proposes a new federated learning-based aerial-ground air quality sensing framework for fine-grained 3D air quality monitoring and forecasting.

Federated Learning

Deep Anomaly Detection for Time-series Data in Industrial IoT: A Communication-Efficient On-device Federated Learning Approach

no code implementations19 Jul 2020 Yi Liu, Sahil Garg, Jiangtian Nie, Yang Zhang, Zehui Xiong, Jiawen Kang, M. Shamim Hossain

Third, to adapt the proposed framework to the timeliness of industrial anomaly detection, we propose a gradient compression mechanism based on Top-\textit{k} selection to improve communication efficiency.

Anomaly Detection Federated Learning +1

Deep Learning of High-Order Interactions for Protein Interface Prediction

no code implementations18 Jul 2020 Yi Liu, Hao Yuan, Lei Cai, Shuiwang Ji

However, these methods do not incorporate the important sequential information from amino acid chains and the high-order pairwise interactions.

Protein Interface Prediction Vocal Bursts Intensity Prediction

Image Processing and Quality Control for Abdominal Magnetic Resonance Imaging in the UK Biobank

2 code implementations2 Jul 2020 Nicolas Basty, Yi Liu, Madeleine Cule, E. Louise Thomas, Jimmy D. Bell, Brandon Whitcher

An end-to-end image analysis pipeline is presented for the abdominal MRI protocol used in the UK Biobank on the first 38, 971 participants.

Variable Selection via Thompson Sampling

no code implementations1 Jul 2020 Yi Liu, Veronika Rockova

Thompson sampling is a heuristic algorithm for the multi-armed bandit problem which has a long tradition in machine learning.

BIG-bench Machine Learning Interpretable Machine Learning +3

Assessing the Impact of COVID-19 on the Objective and Analysis of Oncology Clinical Trials -- Application of the Estimand Framework

no code implementations8 Jun 2020 Evgeny Degtyarev, Kaspar Rufibach, Yue Shentu, Godwin Yung, Michelle Casey, Stefan Englert, Feng Liu, Yi Liu, Oliver Sailer, Jonathan Siegel, Steven Sun, Rui Tang, Jiangxiu Zhou

We identify key intercurrent events that may occur due to COVID-19 in oncology clinical trials with a focus on time-to-event endpoints and discuss considerations pertaining to the other estimand attributes introduced in the ICH E9 addendum.

Federated Learning for 6G Communications: Challenges, Methods, and Future Directions

no code implementations4 Jun 2020 Yi Liu, Xingliang Yuan, Zehui Xiong, Jiawen Kang, Xiaofei Wang, Dusit Niyato

As the 5G communication networks are being widely deployed worldwide, both industry and academia have started to move beyond 5G and explore 6G communications.

Federated Learning

Exemplar-based Generative Facial Editing

no code implementations31 May 2020 Jingtao Guo, Yi Liu, Zhenzhen Qian, Zuowei Zhou

Image synthesis has witnessed substantial progress due to the increasing power of generative model.

Facial Editing Image Generation

Activation functions are not needed: the ratio net

1 code implementation14 May 2020 Chi-Chun Zhou, Hai-Long Tu, Yue-Jie Hou, Zhen Ling, Yi Liu, Jian Hua

We compare the effectiveness and efficiency of the ratio net and that of the RBF and the MLP with various kinds of activation functions in the classification task on the mnist database of handwritten digits and the Internet Movie Database (IMDb) which is a binary sentiment analysis dataset.

General Classification Sentiment Analysis

A Secure Federated Learning Framework for 5G Networks

no code implementations12 May 2020 Yi Liu, Jialiang Peng, Jiawen Kang, Abdullah M. Iliyasu, Dusit Niyato, Ahmed A. Abd El-Latif

In this article, we propose a blockchain-based secure FL framework to create smart contracts and prevent malicious or unreliable participants from involving in FL.

Federated Learning

Privacy-preserving Traffic Flow Prediction: A Federated Learning Approach

1 code implementation19 Mar 2020 Yi Liu, James J. Q. Yu, Jiawen Kang, Dusit Niyato, Shuyu Zhang

Through extensive case studies on a real-world dataset, it is shown that FedGRU's prediction accuracy is 90. 96% higher than the advanced deep learning models, which confirm that FedGRU can achieve accurate and timely traffic prediction without compromising the privacy and security of raw data.

Federated Learning Privacy Preserving +1

The Deep Learning Compiler: A Comprehensive Survey

1 code implementation6 Feb 2020 Mingzhen Li, Yi Liu, Xiaoyan Liu, Qingxiao Sun, Xin You, Hailong Yang, Zhongzhi Luan, Lin Gan, Guangwen Yang, Depei Qian

In this paper, we perform a comprehensive survey of existing DL compilers by dissecting the commonly adopted design in details, with emphasis on the DL oriented multi-level IRs, and frontend/backend optimizations.

MulGAN: Facial Attribute Editing by Exemplar

no code implementations28 Dec 2019 Jingtao Guo, Zhenzhen Qian, Zuowei Zhou, Yi Liu

These methods encode attribute-related information in images into the predefined region of the latent feature space by employing a pair of images with opposite attributes as input to train model, the face attribute transfer between the input image and the exemplar can be achieved by exchanging their attribute-related latent feature region.

THUEE system description for NIST 2019 SRE CTS Challenge

no code implementations25 Dec 2019 Yi Liu, Tianyu Liang, Can Xu, Xianwei Zhang, Xianhong Chen, Wei-Qiang Zhang, Liang He, Dandan song, Ruyun Li, Yangcheng Wu, Peng Ouyang, Shouyi Yin

This paper describes the systems submitted by the department of electronic engineering, institute of microelectronics of Tsinghua university and TsingMicro Co. Ltd. (THUEE) to the NIST 2019 speaker recognition evaluation CTS challenge.

Speaker Recognition

PPGAN: Privacy-preserving Generative Adversarial Network

no code implementations4 Oct 2019 Yi Liu, Jialiang Peng, James J. Q. Yu, Yi Wu

To address this issue, we propose a Privacy-preserving Generative Adversarial Network (PPGAN) model, in which we achieve differential privacy in GANs by adding well-designed noise to the gradient during the model learning procedure.

Privacy Preserving

Employing Deep Part-Object Relationships for Salient Object Detection

1 code implementation ICCV 2019 Yi Liu, Qiang Zhang, Dingwen Zhang, Jungong Han

In the second step, we feed the primary capsules into two identical streams, within each of which low-level capsules (parts) will be assigned to their familiar high-level capsules (object) via a locally connected routing.

object-detection RGB Salient Object Detection +1

Building Change Detection for Remote Sensing Images Using a Dual Task Constrained Deep Siamese Convolutional Network Model

no code implementations17 Sep 2019 Yi Liu, Chao Pang, Zongqian Zhan, Xiaomeng Zhang, Xue Yang

In recent years, building change detection methods have made great progress by introducing deep learning, but they still suffer from the problem of the extracted features not being discriminative enough, resulting in incomplete regions and irregular boundaries.

Building change detection for remote sensing images Change Detection +3

Open DNN Box by Power Side-Channel Attack

no code implementations21 Jul 2019 Yun Xiang, Zhuangzhi Chen, Zuohui Chen, Zebin Fang, Haiyang Hao, Jinyin Chen, Yi Liu, Zhefu Wu, Qi Xuan, Xiaoniu Yang

However, recent studies indicate that they are also vulnerable to adversarial attacks.

Global Pixel Transformers for Virtual Staining of Microscopy Images

no code implementations1 Jul 2019 Yi Liu, Hao Yuan, Zhengyang Wang, Shuiwang Ji

It is also shown that our proposed global pixel transformer layer is useful to improve the fluorescence image prediction results.

MV-C3D: A Spatial Correlated Multi-View 3D Convolutional Neural Networks

no code implementations15 Jun 2019 Qi Xuan, Fuxian Li, Yi Liu, Yun Xiang

Experimental results on ModelNet10 and ModelNet40 datasets show that our MV-C3D technique can achieve outstanding performance with multi-view images which are captured from partial angles with less range.

3D Object Recognition

Normalization Gradients are Least-squares Residuals

no code implementations ICLR 2019 Yi Liu

Batch Normalization (BN) and its variants have seen widespread adoption in the deep learning community because they improve the training of deep neural networks.

Estimation of Inter-Sentiment Correlations Employing Deep Neural Network Models

no code implementations24 Nov 2018 Xinzhi Wang, Shengcheng Yuan, HUI ZHANG, Yi Liu

By contrast, in objective news bodies and titles, it is easy to regard text as caused love (gd).

DSNet: Deep and Shallow Feature Learning for Efficient Visual Tracking

no code implementations6 Nov 2018 Qiangqiang Wu, Yan Yan, Yanjie Liang, Yi Liu, Hanzi Wang

In recent years, Discriminative Correlation Filter (DCF) based tracking methods have achieved great success in visual tracking.

Image Classification Visual Tracking

An Efficient Bandit Algorithm for Realtime Multivariate Optimization

no code implementations22 Oct 2018 Daniel N. Hill, Houssam Nassif, Yi Liu, Anand Iyer, S. V. N. Vishwanathan

We further apply our algorithm to optimize a message that promotes adoption of an Amazon service.

Multi-glance Reading Model for Text Understanding

no code implementations WS 2018 Pengcheng Zhu, Yujiu Yang, Wenqiang Gao, Yi Liu

Based on the multi-glance mechanism, we design two types of recurrent neural network models for repeated reading: Glance Cell Model (GCM) and Glance Gate Model (GGM).

Document Classification Machine Translation +2

Multi-Modal Coreference Resolution with the Correlation between Space Structures

no code implementations21 Apr 2018 Qibin Zheng, Xingchun Diao, Jianjun Cao, Xiaolei Zhou, Yi Liu, Hongmei Li

In this paper, we bring a extrinsic correlation between the space structures of each modalities in coreference resolution.

coreference-resolution Coreference Resolution

Comparison of Multiple Features and Modeling Methods for Text-dependent Speaker Verification

no code implementations14 Jul 2017 Yi Liu, Liang He, Yao Tian, Zhuzi Chen, Jia Liu, Michael T. Johnson

Additionally, we also find that even though bottleneck features perform well for text-independent speaker verification, they do not outperform MFCCs on the most challenging Imposter-Correct trials on RedDots.

Speaker Identification Speaker Recognition +2

Teaching Compositionality to CNNs

no code implementations CVPR 2017 Austin Stone, Huayan Wang, Michael Stark, Yi Liu, D. Scott Phoenix, Dileep George

Convolutional neural networks (CNNs) have shown great success in computer vision, approaching human-level performance when trained for specific tasks via application-specific loss functions.

Object Recognition

Sparse Representation based Multi-sensor Image Fusion: A Review

no code implementations12 Feb 2017 Qiang Zhang, Yi Liu, Rick S. Blum, Jungong Han, DaCheng Tao

As a result of several successful applications in computer vision and image processing, sparse representation (SR) has attracted significant attention in multi-sensor image fusion.

Dictionary Learning Infrared And Visible Image Fusion

A backward pass through a CNN using a generative model of its activations

no code implementations8 Nov 2016 Huayan Wang, Anna Chen, Yi Liu, Dileep George, D. Scott Phoenix

Neural networks have shown to be a practical way of building a very complex mapping between a pre-specified input space and output space.

Hierarchical compositional feature learning

no code implementations7 Nov 2016 Miguel Lázaro-Gredilla, Yi Liu, D. Scott Phoenix, Dileep George

We introduce the hierarchical compositional network (HCN), a directed generative model able to discover and disentangle, without supervision, the building blocks of a set of binary images.

Formula of Volume of Revolution with Integration by Parts and Extension

no code implementations4 Sep 2016 Yi Liu, Jingwei Liu

A calculation formula of volume of revolution with integration by parts of definite integral is derived based on monotone function, and extended to a general case that curved trapezoids is determined by continuous, piecewise strictly monotone and differential function.

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