Search Results for author: Yong Li

Found 156 papers, 72 papers with code

Efficient Hyper-parameter Search for Knowledge Graph Embedding

1 code implementation ACL 2022 Yongqi Zhang, Zhanke Zhou, Quanming Yao, Yong Li

Based on the analysis, we propose an efficient two-stage search algorithm KGTuner, which efficiently explores HP configurations on small subgraph at the first stage and transfers the top-performed configurations for fine-tuning on the large full graph at the second stage.

AutoML Knowledge Graph Embedding

LLM4SBR: A Lightweight and Effective Framework for Integrating Large Language Models in Session-based Recommendation

no code implementations21 Feb 2024 Shutong Qiao, Chen Gao, Junhao Wen, Wei Zhou, Qun Luo, Peixuan Chen, Yong Li

However, constrained by high time and space costs, as well as the brief and anonymous nature of session data, the first LLM recommendation framework suitable for industrial deployment has yet to emerge in the field of SBR.

Session-Based Recommendations

A Generative Pre-Training Framework for Spatio-Temporal Graph Transfer Learning

1 code implementation19 Feb 2024 Yuan Yuan, Chenyang Shao, Jingtao Ding, Depeng Jin, Yong Li

To bridge this gap, we propose a novel generative pre-training framework, GPDiff, for STG transfer learning.

Denoising Transfer Learning

UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction

no code implementations19 Feb 2024 Yuan Yuan, Jingtao Ding, Jie Feng, Depeng Jin, Yong Li

Urban spatio-temporal prediction is crucial for informed decision-making, such as transportation management, resource optimization, and urban planning.

Decision Making Management

Large Language Model-driven Meta-structure Discovery in Heterogeneous Information Network

no code implementations18 Feb 2024 Lin Chen, Fengli Xu, Nian Li, Zhenyu Han, Meng Wang, Yong Li, Pan Hui

We propose a novel REasoning meta-STRUCTure search (ReStruct) framework that integrates LLM reasoning into the evolutionary procedure.

Language Modelling Large Language Model +1

Beyond Imitation: Generating Human Mobility from Context-aware Reasoning with Large Language Models

no code implementations15 Feb 2024 Chenyang Shao, Fengli Xu, Bingbing Fan, Jingtao Ding, Yuan Yuan, Meng Wang, Yong Li

In this paper, we design a novel Mobility Generation as Reasoning (MobiGeaR) framework that prompts LLM to recursively generate mobility behaviour.

In-Context Learning

RIS-Enhanced Cognitive Integrated Sensing and Communication: Joint Beamforming and Spectrum Sensing

no code implementations10 Feb 2024 Yongqing Xu, Yong Li, Tony Q. S. Quek

Cognitive radio (CR) and integrated sensing and communication (ISAC) are both critical technologies for the sixth generation (6G) wireless networks.

Social Physics Informed Diffusion Model for Crowd Simulation

1 code implementation8 Feb 2024 Hongyi Chen, Jingtao Ding, Yong Li, Yue Wang, Xiao-Ping Zhang

In this paper, we propose a social physics-informed diffusion model named SPDiff to mitigate the above gap.

Denoising Physics-informed machine learning

Estimating On-road Transportation Carbon Emissions from Open Data of Road Network and Origin-destination Flow Data

1 code implementation7 Feb 2024 Jinwei Zeng, Yu Liu, Jingtao Ding, Jian Yuan, Yong Li

To relieve this issue by utilizing the strong pattern recognition of artificial intelligence, we incorporate two sources of open data representative of the transportation demand and capacity factors, the origin-destination (OD) flow data and the road network data, to build a hierarchical heterogeneous graph learning method for on-road carbon emission estimation (HENCE).

Graph Learning

DefInt: A Default-interventionist Framework for Efficient Reasoning with Hybrid Large Language Models

no code implementations4 Feb 2024 Yu Shang, Yu Li, Fengli Xu, Yong Li

Previous works like chain-of-thought (CoT) and tree-of-thoughts(ToT) have predominately focused on enhancing accuracy, but overlook the rapidly increasing token cost, which could be particularly problematic for open-ended real-world tasks with huge solution spaces.

Large Language Model Agent for Hyper-Parameter Optimization

no code implementations2 Feb 2024 Siyi Liu, Chen Gao, Yong Li

Hyperparameter optimization is critical in modern machine learning, requiring expert knowledge, numerous trials, and high computational and human resources.

Hyperparameter Optimization Language Modelling +1

Privacy-Preserving Face Recognition in Hybrid Frequency-Color Domain

no code implementations24 Jan 2024 Dong Han, Yong Li, Joachim Denzler

Lastly, secure multiparty computation is implemented for safely computing the embedding distance during model inference.

Attribute Face Recognition +1

Large language model empowered participatory urban planning

no code implementations24 Jan 2024 Zhilun Zhou, Yuming Lin, Yong Li

Participatory urban planning is the mainstream of modern urban planning and involves the active engagement of different stakeholders.

Language Modelling Large Language Model

UV-SAM: Adapting Segment Anything Model for Urban Village Identification

1 code implementation16 Jan 2024 Xin Zhang, Yu Liu, Yuming Lin, Qingmin Liao, Yong Li

Urban villages, defined as informal residential areas in or around urban centers, are characterized by inadequate infrastructures and poor living conditions, closely related to the Sustainable Development Goals (SDGs) on poverty, adequate housing, and sustainable cities.

Image Classification Semantic Segmentation

Urban Generative Intelligence (UGI): A Foundational Platform for Agents in Embodied City Environment

1 code implementation19 Dec 2023 Fengli Xu, Jun Zhang, Chen Gao, Jie Feng, Yong Li

Urban environments, characterized by their complex, multi-layered networks encompassing physical, social, economic, and environmental dimensions, face significant challenges in the face of rapid urbanization.

Short-Term Multi-Horizon Line Loss Rate Forecasting of a Distribution Network Using Attention-GCN-LSTM

no code implementations19 Dec 2023 Jie Liu, Yijia Cao, Yong Li, Yixiu Guo, Wei Deng

Accurately predicting line loss rates is vital for effective line loss management in distribution networks, especially over short-term multi-horizons ranging from one hour to one week.

Management

GLOP: Learning Global Partition and Local Construction for Solving Large-scale Routing Problems in Real-time

1 code implementation13 Dec 2023 Haoran Ye, Jiarui Wang, Helan Liang, Zhiguang Cao, Yong Li, Fanzhang Li

The recent end-to-end neural solvers have shown promise for small-scale routing problems but suffered from limited real-time scaling-up performance.

A Survey of Generative AI for Intelligent Transportation Systems

no code implementations13 Dec 2023 Huan Yan, Yong Li

Intelligent transportation systems play a crucial role in modern traffic management and optimization, greatly improving traffic efficiency and safety.

Decision Making Image Generation +2

Mixed Attention Network for Cross-domain Sequential Recommendation

1 code implementation14 Nov 2023 GuanYu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li, Meng Wang

Recent proposed cross-domain sequential recommendation models such as PiNet and DASL have a common drawback relying heavily on overlapped users in different domains, which limits their usage in practical recommender systems.

Sequential Recommendation

Inverse Learning with Extremely Sparse Feedback for Recommendation

1 code implementation14 Nov 2023 GuanYu Lin, Chen Gao, Yu Zheng, Yinfeng Li, Jianxin Chang, Yanan Niu, Yang song, Kun Gai, Zhiheng Li, Depeng Jin, Yong Li

In this paper, we propose a meta-learning method to annotate the unlabeled data from loss and gradient perspectives, which considers the noises in both positive and negative instances.

Meta-Learning

Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration

no code implementations10 Nov 2023 Wenjie Fu, Huandong Wang, Chen Gao, Guanghua Liu, Yong Li, Tao Jiang

Prior attempts have quantified the privacy risks of language models (LMs) via MIAs, but there is still no consensus on whether existing MIA algorithms can cause remarkable privacy leakage on practical Large Language Models (LLMs).

Inference Attack Membership Inference Attack +1

A Practical Large-Scale Roadside Multi-View Multi-Sensor Spatial Synchronization Framework for Intelligent Transportation Systems

no code implementations4 Nov 2023 Yong Li, Zhiguo Zhao, Yunli Chen, Rui Tian

To address these challenges, our research introduces a parallel spatial transformation (PST)-based framework for large-scale, multi-view, multi-sensor scenarios.

Camera Calibration

ROAM: memory-efficient large DNN training via optimized operator ordering and memory layout

no code implementations30 Oct 2023 Huiyao Shu, Ang Wang, Ziji Shi, Hanyu Zhao, Yong Li, Lu Lu

However, a memory-efficient execution plan that includes a reasonable operator execution order and tensor memory layout can significantly increase the models' memory efficiency and reduce overheads from high-level techniques.

Large Language Model-Empowered Agents for Simulating Macroeconomic Activities

no code implementations16 Oct 2023 Nian Li, Chen Gao, Yong Li, Qingmin Liao

In this work, we take an early step in introducing a novel approach that leverages LLMs in macroeconomic simulation.

Decision Making Language Modelling +2

Stance Detection with Collaborative Role-Infused LLM-Based Agents

no code implementations16 Oct 2023 Xiaochong Lan, Chen Gao, Depeng Jin, Yong Li

Next, in the reasoning-enhanced debating stage, for each potential stance, we designate a specific LLM-based agent to advocate for it, guiding the LLM to detect logical connections between text features and stance, tackling the second challenge.

CoLA Stance Detection

Relation-aware Ensemble Learning for Knowledge Graph Embedding

2 code implementations13 Oct 2023 Ling Yue, Yongqi Zhang, Quanming Yao, Yong Li, Xian Wu, Ziheng Zhang, Zhenxi Lin, Yefeng Zheng

Knowledge graph (KG) embedding is a fundamental task in natural language processing, and various methods have been proposed to explore semantic patterns in distinctive ways.

Ensemble Learning Knowledge Graph Embedding +1

Dual-stage Flows-based Generative Modeling for Traceable Urban Planning

no code implementations3 Oct 2023 Xuanming Hu, Wei Fan, Dongjie Wang, Pengyang Wang, Yong Li, Yanjie Fu

We design several experiments to indicate that our framework can outperform compared to other generative models for the urban planning task.

DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization

1 code implementation NeurIPS 2023 Haoran Ye, Jiarui Wang, Zhiguang Cao, Helan Liang, Yong Li

As a Neural Combinatorial Optimization method, DeepACO performs better than or on par with problem-specific methods on canonical routing problems.

Combinatorial Optimization

Flash-LLM: Enabling Cost-Effective and Highly-Efficient Large Generative Model Inference with Unstructured Sparsity

1 code implementation19 Sep 2023 Haojun Xia, Zhen Zheng, Yuchao Li, Donglin Zhuang, Zhongzhu Zhou, Xiafei Qiu, Yong Li, Wei Lin, Shuaiwen Leon Song

Therefore, we propose Flash-LLM for enabling low-cost and highly-efficient large generative model inference with the sophisticated support of unstructured sparsity on high-performance but highly restrictive Tensor Cores.

Towards Generative Modeling of Urban Flow through Knowledge-enhanced Denoising Diffusion

1 code implementation19 Sep 2023 Zhilun Zhou, Jingtao Ding, Yu Liu, Depeng Jin, Yong Li

To capture the effect of multiple factors on urban flow, such as region features and urban environment, we employ diffusion model to generate urban flow for regions under different conditions.

Denoising

Central Similarity Multi-View Hashing for Multimedia Retrieval

no code implementations26 Aug 2023 Jian Zhu, Wen Cheng, Yu Cui, Chang Tang, Yuyang Dai, Yong Li, Lingfang Zeng

Hash representation learning of multi-view heterogeneous data is the key to improving the accuracy of multimedia retrieval.

Representation Learning Retrieval

Learning and Optimization of Implicit Negative Feedback for Industrial Short-video Recommender System

no code implementations25 Aug 2023 Yunzhu Pan, Nian Li, Chen Gao, Jianxin Chang, Yanan Niu, Yang song, Depeng Jin, Yong Li

Short-video recommendation is one of the most important recommendation applications in today's industrial information systems.

Recommendation Systems

A Probabilistic Fluctuation based Membership Inference Attack for Diffusion Models

no code implementations23 Aug 2023 Wenjie Fu, Huandong Wang, Chen Gao, Guanghua Liu, Yong Li, Tao Jiang

Membership Inference Attack (MIA) identifies whether a record exists in a machine learning model's training set by querying the model.

Inference Attack Membership Inference Attack +1

Edit Temporal-Consistent Videos with Image Diffusion Model

no code implementations17 Aug 2023 Yuanzhi Wang, Yong Li, Xiaoya Zhang, Xin Liu, Anbo Dai, Antoni B. Chan, Zhen Cui

In addition to the utilization of a pretrained T2I 2D Unet for spatial content manipulation, we establish a dedicated temporal Unet architecture to faithfully capture the temporal coherence of the input video sequences.

Video Temporal Consistency

Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation

no code implementations8 Aug 2023 Yunzhu Pan, Chen Gao, Jianxin Chang, Yanan Niu, Yang song, Kun Gai, Depeng Jin, Yong Li

To enhance the robustness of our model, we then introduce a multi-task learning module to simultaneously optimize two kinds of feedback -- passive-negative feedback and traditional randomly-sampled negative feedback.

Multi-Task Learning Sequential Recommendation

Uncertainty-aware Consistency Learning for Cold-Start Item Recommendation

no code implementations7 Aug 2023 Taichi Liu, Chen Gao, Zhenyu Wang, Dong Li, Jianye Hao, Depeng Jin, Yong Li

Graph Neural Network (GNN)-based models have become the mainstream approach for recommender systems.

Recommendation Systems

EduChat: A Large-Scale Language Model-based Chatbot System for Intelligent Education

1 code implementation5 Aug 2023 Yuhao Dan, Zhikai Lei, Yiyang Gu, Yong Li, Jianghao Yin, Jiaju Lin, Linhao Ye, Zhiyan Tie, Yougen Zhou, Yilei Wang, Aimin Zhou, Ze Zhou, Qin Chen, Jie zhou, Liang He, Xipeng Qiu

Currently, EduChat is available online as an open-source project, with its code, data, and model parameters available on platforms (e. g., GitHub https://github. com/icalk-nlp/EduChat, Hugging Face https://huggingface. co/ecnu-icalk ).

Chatbot Language Modelling +1

NEON: Living Needs Prediction System in Meituan

no code implementations31 Jul 2023 Xiaochong Lan, Chen Gao, Shiqi Wen, Xiuqi Chen, Yingge Che, Han Zhang, Huazhou Wei, Hengliang Luo, Yong Li

To address these two challenges, we design a system of living NEeds predictiON named NEON, consisting of three phases: feature mining, feature fusion, and multi-task prediction.

Watch out Venomous Snake Species: A Solution to SnakeCLEF2023

1 code implementation19 Jul 2023 Feiran Hu, Peng Wang, Yangyang Li, Chenlong Duan, Zijian Zhu, Fei Wang, Faen Zhang, Yong Li, Xiu-Shen Wei

The SnakeCLEF2023 competition aims to the development of advanced algorithms for snake species identification through the analysis of images and accompanying metadata.

Data Augmentation

Detecting Vulnerable Nodes in Urban Infrastructure Interdependent Network

1 code implementation19 Jul 2023 Jinzhu Mao, Liu Cao, Chen Gao, Huandong Wang, Hangyu Fan, Depeng Jin, Yong Li

Understanding and characterizing the vulnerability of urban infrastructures, which refers to the engineering facilities essential for the regular running of cities and that exist naturally in the form of networks, is of great value to us.

Efficient and Joint Hyperparameter and Architecture Search for Collaborative Filtering

1 code implementation12 Jul 2023 Yan Wen, Chen Gao, Lingling Yi, Liwei Qiu, Yaqing Wang, Yong Li

Automated Machine Learning (AutoML) techniques have recently been introduced to design Collaborative Filtering (CF) models in a data-specific manner.

AutoML Collaborative Filtering

OpenSiteRec: An Open Dataset for Site Recommendation

no code implementations3 Jul 2023 Xinhang Li, Xiangyu Zhao, Yejing Wang, Yu Liu, Yong Li, Cheng Long, Yong Zhang, Chunxiao Xing

As a representative information retrieval task, site recommendation, which aims at predicting the optimal sites for a brand or an institution to open new branches in an automatic data-driven way, is beneficial and crucial for brand development in modern business.

Benchmarking Information Retrieval +1

Multi-Scale Simulation of Complex Systems: A Perspective of Integrating Knowledge and Data

no code implementations17 Jun 2023 Huandong Wang, Huan Yan, Can Rong, Yuan Yuan, Fenyu Jiang, Zhenyu Han, Hongjie Sui, Depeng Jin, Yong Li

In this survey, we will systematically review the literature on multi-scale simulation of complex systems from the perspective of knowledge and data.

Carbon emissions and sustainability of launching 5G mobile networks in China

no code implementations14 Jun 2023 Tong Li, Li Yu, Yibo Ma, Tong Duan, Wenzhen Huang, Yan Zhou, Depeng Jin, Yong Li, Tao Jiang

We show that the decline in carbon efficiency leads to a carbon efficiency trap, estimated to cause additional carbon emissions of 23. 82 +- 1. 07 megatons in China.

Complexity-aware Large Scale Origin-Destination Network Generation via Diffusion Model

no code implementations8 Jun 2023 Can Rong, Jingtao Ding, Zhicheng Liu, Yong Li

The Origin-Destination~(OD) networks provide an estimation of the flow of people from every region to others in the city, which is an important research topic in transportation, urban simulation, etc.

Denoising

Origin-Destination Network Generation via Gravity-Guided GAN

no code implementations6 Jun 2023 Can Rong, Huandong Wang, Yong Li

Origin-destination (OD) flow, which contains valuable population mobility information including direction and volume, is critical in many urban applications, such as urban planning, transportation management, etc.

Graph Attention Management

How Graph Convolutions Amplify Popularity Bias for Recommendation?

1 code implementation24 May 2023 Jiajia Chen, Jiancan Wu, Jiawei Chen, Xin Xin, Yong Li, Xiangnan He

Through theoretical analyses, we identify two fundamental factors: (1) with graph convolution (\textit{i. e.,} neighborhood aggregation), popular items exert larger influence than tail items on neighbor users, making the users move towards popular items in the representation space; (2) after multiple times of graph convolution, popular items would affect more high-order neighbors and become more influential.

Recommendation Systems

Road Planning for Slums via Deep Reinforcement Learning

1 code implementation22 May 2023 Yu Zheng, Hongyuan Su, Jingtao Ding, Depeng Jin, Yong Li

Existing re-blocking or heuristic methods are either time-consuming which cannot generalize to different slums, or yield sub-optimal road plans in terms of accessibility and construction costs.

Blocking reinforcement-learning

Spatio-temporal Diffusion Point Processes

2 code implementations21 May 2023 Yuan Yuan, Jingtao Ding, Chenyang Shao, Depeng Jin, Yong Li

To enhance the learning of each step, an elaborated spatio-temporal co-attention module is proposed to capture the interdependence between the event time and space adaptively.

Epidemiology Point Processes

Model Checking Strategies from Synthesis Over Finite Traces

no code implementations15 May 2023 Suguman Bansal, Yong Li, Lucas Martinelli Tabajara, Moshe Y. Vardi, Andrew Wells

Our central result is that LTLf model checking of non-terminating transducers is \emph{exponentially harder} than that of terminating transducers.

Template-based eukaryotic genome editing directed by SviCas3

no code implementations10 May 2023 Wang-Yu Tong, Yong Li, Shou-Dong Ye, An-Jing Wang, Yan-Yan Tang, Mei-Li Li, Zhong-Fan Yu, Ting-Ting Xia, Qing-Yang Liu, Si-Qi Zhu

RNA-guided gene editing based on the CRISPR-Cas system is currently the most effective genome editing technique.

Simplifying Low-Light Image Enhancement Networks with Relative Loss Functions

1 code implementation6 Apr 2023 Yu Zhang, Xiaoguang Di, Junde Wu, Rao Fu, Yong Li, Yue Wang, Yanwu Xu, Guohui YANG, Chunhui Wang

In this paper, to make the learning easier in low-light image enhancement, we introduce FLW-Net (Fast and LightWeight Network) and two relative loss functions.

Low-Light Image Enhancement

Decoupled Multimodal Distilling for Emotion Recognition

1 code implementation CVPR 2023 Yong Li, Yuanzhi Wang, Zhen Cui

Specially, the representation of each modality is decoupled into two parts, i. e., modality-irrelevant/-exclusive spaces, in a self-regression manner.

Knowledge Distillation Multimodal Emotion Recognition +1

Logical Expressiveness of Graph Neural Network for Knowledge Graph Reasoning

no code implementations22 Mar 2023 Haiquan Qiu, Yongqi Zhang, Yong Li, Quanming Yao

Our results first show that GNN can capture logical rules from graded modal logic, providing a new theoretical tool for analyzing the expressiveness of GNN for KG reasoning; and a query labeling trick makes it easier for GNN to capture logical rules, explaining why SOTA methods are mainly based on labeling trick.

Robust Preference-Guided Denoising for Graph based Social Recommendation

1 code implementation15 Mar 2023 Yuhan Quan, Jingtao Ding, Chen Gao, Lingling Yi, Depeng Jin, Yong Li

Graph Neural Network(GNN) based social recommendation models improve the prediction accuracy of user preference by leveraging GNN in exploiting preference similarity contained in social relations.

Denoising Relation

Joint Beamforming for RIS-Assisted Integrated Sensing and Communication Systems

no code implementations3 Mar 2023 Yongqing Xu, Yong Li, J. Andrew Zhang, Marco Di Renzo, Tony Q. S. Quek

However, due to multiple performance metrics used for communication and sensing, the limited degrees-of-freedom (DoF) in optimizing ISAC systems poses a challenge.

Knowledge-infused Contrastive Learning for Urban Imagery-based Socioeconomic Prediction

1 code implementation25 Feb 2023 Yu Liu, Xin Zhang, Jingtao Ding, Yanxin Xi, Yong Li

To address such issues, in this paper, we propose a Knowledge-infused Contrastive Learning (KnowCL) model for urban imagery-based socioeconomic prediction.

Contrastive Learning Representation Learning

Learning to Simulate Daily Activities via Modeling Dynamic Human Needs

1 code implementation9 Feb 2023 Yuan Yuan, Huandong Wang, Jingtao Ding, Depeng Jin, Yong Li

To enhance the fidelity and utility of the generated activity data, our core idea is to model the evolution of human needs as the underlying mechanism that drives activity generation in the simulation model.

Imitation Learning Scheduling

Dual-interest Factorization-heads Attention for Sequential Recommendation

1 code implementation8 Feb 2023 GuanYu Lin, Chen Gao, Yu Zheng, Jianxin Chang, Yanan Niu, Yang song, Zhiheng Li, Depeng Jin, Yong Li

In this paper, we propose Dual-interest Factorization-heads Attention for Sequential Recommendation (short for DFAR) consisting of feedback-aware encoding layer, dual-interest disentangling layer and prediction layer.

Disentanglement Sequential Recommendation

TAP: Accelerating Large-Scale DNN Training Through Tensor Automatic Parallelisation

no code implementations1 Feb 2023 Ziji Shi, Le Jiang, Ang Wang, Jie Zhang, Xianyan Jia, Yong Li, Chencan Wu, Jialin Li, Wei Lin

However, finding a suitable model parallel schedule for an arbitrary neural network is a non-trivial task due to the exploding search space.

Physics-Informed Neural Networks for Prognostics and Health Management of Lithium-Ion Batteries

1 code implementation2 Jan 2023 Pengfei Wen, Zhi-Sheng Ye, Yong Li, Shaowei Chen, Pu Xie, Shuai Zhao

Physics-Informed Neural Network (PINN) is an efficient tool to fuse empirical or physical dynamic models with data-driven models.

Management

Style Projected Clustering for Domain Generalized Semantic Segmentation

no code implementations CVPR 2023 Wei Huang, Chang Chen, Yong Li, Jiacheng Li, Cheng Li, Fenglong Song, Youliang Yan, Zhiwei Xiong

In contrast to existing methods, we instead utilize the difference between images to build a better representation space, where the distinct style features are extracted and stored as the bases of representation.

Clustering Semantic Segmentation

Distribution-Consistent Modal Recovering for Incomplete Multimodal Learning

1 code implementation ICCV 2023 Yuanzhi Wang, Zhen Cui, Yong Li

Recovering missed modality is popular in incomplete multimodal learning because it usually benefits downstream tasks.

Density Estimation

Towards Real World HDRTV Reconstruction: A Data Synthesis-based Approach

no code implementations6 Nov 2022 Zhen Cheng, Tao Wang, Yong Li, Fenglong Song, Chang Chen, Zhiwei Xiong

To solve this problem, we propose a learning-based data synthesis approach to learn the properties of real-world SDRTVs by integrating several tone mapping priors into both network structures and loss functions.

Tone Mapping

Revisiting and Advancing Chinese Natural Language Understanding with Accelerated Heterogeneous Knowledge Pre-training

1 code implementation11 Oct 2022 Taolin Zhang, Junwei DOng, Jianing Wang, Chengyu Wang, Ang Wang, Yinghui Liu, Jun Huang, Yong Li, Xiaofeng He

Recently, knowledge-enhanced pre-trained language models (KEPLMs) improve context-aware representations via learning from structured relations in knowledge graphs, and/or linguistic knowledge from syntactic or dependency analysis.

Knowledge Graphs Language Modelling +2

Mutual Harmony: Sequential Recommendation with Dual Contrastive Network

1 code implementation18 Sep 2022 GuanYu Lin, Chen Gao, Yinfeng Li, Yu Zheng, Zhiheng Li, Depeng Jin, Dong Li, Jianye Hao, Yong Li

Such user-centric recommendation will make it impossible for the provider to expose their new items, failing to consider the accordant interactions between user and item dimensions.

Contrastive Learning Representation Learning +1

Intrinsically Motivated Reinforcement Learning based Recommendation with Counterfactual Data Augmentation

no code implementations17 Sep 2022 Xiaocong Chen, Siyu Wang, Lina Yao, Lianyong Qi, Yong Li

It is more challenging to balance the exploration and exploitation in DRL RS where RS agent need to deeply explore the informative trajectories and exploit them efficiently in the context of recommender systems.

counterfactual Data Augmentation +3

Causal Inference in Recommender Systems: A Survey and Future Directions

1 code implementation26 Aug 2022 Chen Gao, Yu Zheng, Wenjie Wang, Fuli Feng, Xiangnan He, Yong Li

Existing recommender systems extract user preferences based on the correlation in data, such as behavioral correlation in collaborative filtering, feature-feature, or feature-behavior correlation in click-through rate prediction.

Causal Inference Click-Through Rate Prediction +2

DisenHCN: Disentangled Hypergraph Convolutional Networks for Spatiotemporal Activity Prediction

1 code implementation14 Aug 2022 Yinfeng Li, Chen Gao, Quanming Yao, Tong Li, Depeng Jin, Yong Li

In particular, we first unify the fine-grained user similarity and the complex matching between user preferences and spatiotemporal activity into a heterogeneous hypergraph.

Activity Prediction Graph Embedding +1

Practitioners Versus Users: A Value-Sensitive Evaluation of Current Industrial Recommender System Design

no code implementations8 Aug 2022 Zhilong Chen, Jinghua Piao, Xiaochong Lan, Hancheng Cao, Chen Gao, Zhicong Lu, Yong Li

Recommender systems are playing an increasingly important role in alleviating information overload and supporting users' various needs, e. g., consumption, socialization, and entertainment.

Fairness Recommendation Systems

KGTuner: Efficient Hyper-parameter Search for Knowledge Graph Learning

1 code implementation5 May 2022 Yongqi Zhang, Zhanke Zhou, Quanming Yao, Yong Li

While hyper-parameters (HPs) are important for knowledge graph (KG) learning, existing methods fail to search them efficiently.

Graph Learning

A Review-aware Graph Contrastive Learning Framework for Recommendation

1 code implementation26 Apr 2022 Jie Shuai, Kun Zhang, Le Wu, Peijie Sun, Richang Hong, Meng Wang, Yong Li

Second, while most current models suffer from limited user behaviors, can we exploit the unique self-supervised signals in the review-aware graph to guide two recommendation components better?

Contrastive Learning Recommendation Systems +1

PICASSO: Unleashing the Potential of GPU-centric Training for Wide-and-deep Recommender Systems

1 code implementation11 Apr 2022 Yuanxing Zhang, Langshi Chen, Siran Yang, Man Yuan, Huimin Yi, Jie Zhang, Jiamang Wang, Jianbo Dong, Yunlong Xu, Yue Song, Yong Li, Di Zhang, Wei Lin, Lin Qu, Bo Zheng

However, we observe that GPU devices in training recommender systems are underutilized, and they cannot attain an expected throughput improvement as what it has achieved in CV and NLP areas.

Marketing Recommendation Systems

Canonical Mean Filter for Almost Zero-Shot Multi-Task classification

no code implementations8 Apr 2022 Yong Li, Heng Wang, Xiang Ye

Motivated by ANIL, we rethink the role of adaption in the feature extractor of CNAPs, which is a state-of-the-art representative few-shot method.

Neighboring Backdoor Attacks on Graph Convolutional Network

no code implementations17 Jan 2022 Liang Chen, Qibiao Peng, Jintang Li, Yang Liu, Jiawei Chen, Yong Li, Zibin Zheng

To address such a challenge, we set the trigger as a single node, and the backdoor is activated when the trigger node is connected to the target node.

Backdoor Attack

Structure Enhanced Graph Neural Networks for Link Prediction

no code implementations14 Jan 2022 Baole Ai, Zhou Qin, Wenting Shen, Yong Li

Graph Neural Networks (GNNs) have shown promising results in various tasks, among which link prediction is an important one.

Link Prediction

LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimization

no code implementations15 Dec 2021 Huiming Chen, Huandong Wang, Quanming Yao, Yong Li, Depeng Jin, Qiang Yang

Federated optimization (FedOpt), which targets at collaboratively training a learning model across a large number of distributed clients, is vital for federated learning.

Federated Learning

Progressive Feature Interaction Search for Deep Sparse Network

no code implementations NeurIPS 2021 Chen Gao, Yinfeng Li, Quanming Yao, Depeng Jin, Yong Li

Deep sparse networks (DSNs), of which the crux is exploring the high-order feature interactions, have become the state-of-the-art on the prediction task with high-sparsity features.

Neural Architecture Search

Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks

1 code implementation5 Nov 2021 Zirui Zhu, Chen Gao, Xu Chen, Nian Li, Depeng Jin, Yong Li

With the hypergraph convolutional networks, the social relations can be modeled in a more fine-grained manner, which more accurately depicts real users' preferences, and benefits the recommendation performance.

Knowledge-driven Site Selection via Urban Knowledge Graph

no code implementations1 Nov 2021 Yu Liu, Jingtao Ding, Yong Li

Specifically, motivated by distilled knowledge and rich semantics in KG, we firstly construct an urban KG (UrbanKG) with cities' key elements and semantic relationships captured.

Feature Engineering

Improving Location Recommendation with Urban Knowledge Graph

no code implementations1 Nov 2021 Chang Liu, Chen Gao, Depeng Jin, Yong Li

We first conduct information propagation on two sub-graphs to learn the representations of POIs and users.

counterfactual

Spatio-Temporal Urban Knowledge Graph Enabled Mobility Prediction

no code implementations1 Nov 2021 Huandong Wang, Qiaohong Yu, Yu Liu, Depeng Jin, Yong Li

Further, a complex embedding model with elaborately designed scoring functions is proposed to measure the plausibility of facts in STKG to solve the knowledge graph completion problem, which considers temporal dynamics of the mobility patterns and utilizes PoI categories as the auxiliary information and background knowledge.

Knowledge Graph Completion

M6-10T: A Sharing-Delinking Paradigm for Efficient Multi-Trillion Parameter Pretraining

no code implementations8 Oct 2021 Junyang Lin, An Yang, Jinze Bai, Chang Zhou, Le Jiang, Xianyan Jia, Ang Wang, Jie Zhang, Yong Li, Wei Lin, Jingren Zhou, Hongxia Yang

Recent expeditious developments in deep learning algorithms, distributed training, and even hardware design for large models have enabled training extreme-scale models, say GPT-3 and Switch Transformer possessing hundreds of billions or even trillions of parameters.

TabGNN: Multiplex Graph Neural Network for Tabular Data Prediction

1 code implementation20 Aug 2021 Xiawei Guo, Yuhan Quan, Huan Zhao, Quanming Yao, Yong Li, WeiWei Tu

Tabular data prediction (TDP) is one of the most popular industrial applications, and various methods have been designed to improve the prediction performance.

Real-time Image Enhancer via Learnable Spatial-aware 3D Lookup Tables

no code implementations ICCV 2021 Tao Wang, Yong Li, Jingyang Peng, Yipeng Ma, Xian Wang, Fenglong Song, Youliang Yan

One is a 1D weight vector used for image-level scenario adaptation, the other is a 3D weight map aimed for pixel-wise category fusion.

Image Enhancement

DGCN: Diversified Recommendation with Graph Convolutional Networks

2 code implementations16 Aug 2021 Yu Zheng, Chen Gao, Liang Chen, Depeng Jin, Yong Li

These years much effort has been devoted to improving the accuracy or relevance of the recommendation system.

Collaborative Filtering

One-shot Transfer Learning for Population Mapping

1 code implementation13 Aug 2021 Erzhuo Shao, Jie Feng, Yingheng Wang, Tong Xia, Yong Li

Thus, obtaining fine-grained population distribution from coarse-grained distribution becomes an important problem.

Population Mapping Scheduling +1

Learning Fair Face Representation With Progressive Cross Transformer

no code implementations11 Aug 2021 Yong Li, Yufei Sun, Zhen Cui, Shiguang Shan, Jian Yang

To mitigate racial bias and meantime preserve robust FR, we abstract face identity-related representation as a signal denoising problem and propose a progressive cross transformer (PCT) method for fair face recognition.

Denoising Face Recognition

Graph Jigsaw Learning for Cartoon Face Recognition

1 code implementation14 Jul 2021 Yong Li, Lingjie Lao, Zhen Cui, Shiguang Shan, Jian Yang

To mitigate this issue, we propose the GraphJigsaw that constructs jigsaw puzzles at various stages in the classification network and solves the puzzles with the graph convolutional network (GCN) in a progressive manner.

Classification Face Recognition

Towards Understanding the Effectiveness of Attention Mechanism

no code implementations29 Jun 2021 Xiang Ye, Zihang He, Heng Wang, Yong Li

Instead, we verify the crucial role of feature map multiplication in attention mechanism and uncover a fundamental impact of feature map multiplication on the learned landscapes of CNNs: with the high order non-linearity brought by the feature map multiplication, it played a regularization role on CNNs, which made them learn smoother and more stable landscapes near real samples compared to vanilla CNNs.

Sequential Recommendation with Graph Neural Networks

1 code implementation27 Jun 2021 Jianxin Chang, Chen Gao, Yu Zheng, Yiqun Hui, Yanan Niu, Yang song, Depeng Jin, Yong Li

This helps explicitly distinguish users' core interests, by forming dense clusters in the interest graph.

Metric Learning Sequential Recommendation

Efficient Data-specific Model Search for Collaborative Filtering

no code implementations14 Jun 2021 Chen Gao, Quanming Yao, Depeng Jin, Yong Li

In this way, we can combinatorially generalize data-specific CF models, which have not been visited in the literature, from SOTA ones.

AutoML Collaborative Filtering +1

Consistent Instance False Positive Improves Fairness in Face Recognition

1 code implementation CVPR 2021 Xingkun Xu, Yuge Huang, Pengcheng Shen, Shaoxin Li, Jilin Li, Feiyue Huang, Yong Li, Zhen Cui

Then, an additional penalty term, which is in proportion to the ratio of instance FPR overall FPR, is introduced into the denominator of the softmax-based loss.

Face Recognition Fairness

M6-T: Exploring Sparse Expert Models and Beyond

no code implementations31 May 2021 An Yang, Junyang Lin, Rui Men, Chang Zhou, Le Jiang, Xianyan Jia, Ang Wang, Jie Zhang, Jiamang Wang, Yong Li, Di Zhang, Wei Lin, Lin Qu, Jingren Zhou, Hongxia Yang

Mixture-of-Experts (MoE) models can achieve promising results with outrageous large amount of parameters but constant computation cost, and thus it has become a trend in model scaling.

Playing the Game of 2048

Spatio-Temporal Dual Graph Neural Networks for Travel Time Estimation

no code implementations28 May 2021 Guangyin Jin, Huan Yan, Fuxian Li, Jincai Huang, Yong Li

To address the above problems, a novel graph-based deep learning framework for travel time estimation is proposed in this paper, namely Spatio-Temporal Dual Graph Neural Networks (STDGNN).

Graph Learning Multi-Task Learning +1

Meta Auxiliary Learning for Facial Action Unit Detection

no code implementations14 May 2021 Yong Li, Shiguang Shan

The learned sample weights alleviate the negative transfer from two aspects: 1) balance the loss of each task automatically, and 2) suppress the weights of FE samples that have large uncertainties.

Action Unit Detection Auxiliary Learning +4

Role-Aware Modeling for N-ary Relational Knowledge Bases

1 code implementation20 Apr 2021 Yu Liu, Quanming Yao, Yong Li

N-ary relational knowledge bases (KBs) represent knowledge with binary and beyond-binary relational facts.

Knowledge Graphs

Monitoring urban ecosystem service value using dynamic multi-level grids

no code implementations15 Apr 2021 Zhenfeng Shao, Yong Li, Xiao Huang, Bowen Cai, Lin Ding, Wenkang Pan, Ya zhang

Ecosystem valuation is a method of assigning a monetary value to an ecosystem with its goods and services, often referred to as ecosystem service value (ESV).

valid

Learning Normal Dynamics in Videos with Meta Prototype Network

1 code implementation CVPR 2021 Hui Lv, Chen Chen, Zhen Cui, Chunyan Xu, Yong Li, Jian Yang

Frame reconstruction (current or future frame) based on Auto-Encoder (AE) is a popular method for video anomaly detection.

Anomaly Detection Meta-Learning +1

SCEI: A Smart-Contract Driven Edge Intelligence Framework for IoT Systems

no code implementations12 Mar 2021 Chenhao Xu, Jiaqi Ge, Yong Li, Yao Deng, Longxiang Gao, Mengshi Zhang, Yong Xiang, Xi Zheng

Federated learning (FL) enables collaborative training of a shared model on edge devices while maintaining data privacy.

Edge-computing Federated Learning +1

M6: A Chinese Multimodal Pretrainer

no code implementations1 Mar 2021 Junyang Lin, Rui Men, An Yang, Chang Zhou, Ming Ding, Yichang Zhang, Peng Wang, Ang Wang, Le Jiang, Xianyan Jia, Jie Zhang, Jianwei Zhang, Xu Zou, Zhikang Li, Xiaodong Deng, Jie Liu, Jinbao Xue, Huiling Zhou, Jianxin Ma, Jin Yu, Yong Li, Wei Lin, Jingren Zhou, Jie Tang, Hongxia Yang

In this work, we construct the largest dataset for multimodal pretraining in Chinese, which consists of over 1. 9TB images and 292GB texts that cover a wide range of domains.

Image Generation

Genetic Meta-Structure Search for Recommendation on Heterogeneous Information Network

1 code implementation21 Feb 2021 Zhenyu Han, Fengli Xu, Jinghan Shi, Yu Shang, Haorui Ma, Pan Hui, Yong Li

To address these challenges, we propose Genetic Meta-Structure Search (GEMS) to automatically optimize meta-structure designs for recommendation on HINs.

Recommendation Systems

Policy-Aware Mobility Model Explains the Growth of COVID-19 in Cities

no code implementations21 Feb 2021 Zhenyu Han, Fengli Xu, Yong Li, Tao Jiang, Depeng Jin, Jianhua Lu, James A. Evans

With the continued spread of coronavirus, the task of forecasting distinctive COVID-19 growth curves in different cities, which remain inadequately explained by standard epidemiological models, is critical for medical supply and treatment.

Reinforced Contact Tracing and Epidemic Intervention

no code implementations4 Feb 2021 Tao Feng, Sirui Song, Tong Xia, Yong Li

In this paper, we develop an Individual-based Reinforcement Learning Epidemic Control Agent (IDRLECA) to search for smart epidemic control strategies that can simultaneously minimize infections and the cost of mobility intervention.

Learnable Embedding Sizes for Recommender Systems

1 code implementation ICLR 2021 Siyi Liu, Chen Gao, Yihong Chen, Depeng Jin, Yong Li

Existing works that try to address the problem always cause a significant drop in recommendation performance or suffers from the limitation of unaffordable training time cost.

Recommendation Systems Representation Learning

AttnMove: History Enhanced Trajectory Recovery via Attentional Network

no code implementations3 Jan 2021 Tong Xia, Yunhan Qi, Jie Feng, Fengli Xu, Funing Sun, Diansheng Guo, Yong Li

A considerable amount of mobility data has been accumulated due to the proliferation of location-based service.

Rewriting by Generating: Learn Heuristics for Large-scale Vehicle Routing Problems

no code implementations1 Jan 2021 Hansen Wang, Zefang Zong, Tong Xia, Shuyu Luo, Meng Zheng, Depeng Jin, Yong Li

The large-scale vehicle routing problem is defined based on the classical VRP with usually more than one thousand customers.

Differentiable Learning of Graph-like Logical Rules from Knowledge Graphs

no code implementations1 Jan 2021 Hongzhi Shi, Quanming Yao, Yong Li

The score also helps relax the discrete space into a continuous one and can be uniformly transformed into matrix form by the Einstein summation convention.

Knowledge Graphs

Probability-Density-Based Deep Learning Paradigm for the Fuzzy Design of Functional Metastructures

1 code implementation11 Nov 2020 Ying-Tao Luo, Peng-Qi Li, Dong-Ting Li, Yu-Gui Peng, Zhi-Guo Geng, Shu-Huan Xie, Yong Li, Andrea Alu, Jie Zhu, Xue-Feng Zhu

In quantum mechanics, a norm squared wave function can be interpreted as the probability density that describes the likelihood of a particle to be measured in a given position or momentum.

Automorphic Equivalence-aware Graph Neural Network

1 code implementation NeurIPS 2021 Fengli Xu, Quanming Yao, Pan Hui, Yong Li

Distinguishing the automorphic equivalence of nodes in a graph plays an essential role in many scientific domains, e. g., computational biologist and social network analysis.

Representation Learning

Mitigating Sybil Attacks on Differential Privacy based Federated Learning

no code implementations20 Oct 2020 Yupeng Jiang, Yong Li, Yipeng Zhou, Xi Zheng

The state-of-the-art privacy-preserving technique in the context of federated learning is user-level differential privacy.

Cryptography and Security Distributed, Parallel, and Cluster Computing

Group-Buying Recommendation for Social E-Commerce

1 code implementation14 Oct 2020 Jun Zhang, Chen Gao, Depeng Jin, Yong Li

Group-buying recommendation for social e-commerce, which recommends an item list when users want to launch a group, plays an important role in the group success ratio and sales.

MicroRec: Efficient Recommendation Inference by Hardware and Data Structure Solutions

no code implementations12 Oct 2020 Wenqi Jiang, Zhenhao He, Shuai Zhang, Thomas B. Preußer, Kai Zeng, Liang Feng, Jiansong Zhang, Tongxuan Liu, Yong Li, Jingren Zhou, Ce Zhang, Gustavo Alonso

MicroRec accelerates recommendation inference by (1) redesigning the data structures involved in the embeddings to reduce the number of lookups needed and (2) taking advantage of the availability of High-Bandwidth Memory (HBM) in FPGA accelerators to tackle the latency by enabling parallel lookups.

Recommendation Systems

Simplify and Robustify Negative Sampling for Implicit Collaborative Filtering

1 code implementation NeurIPS 2020 Jingtao Ding, Yuhan Quan, Quanming Yao, Yong Li, Depeng Jin

Negative sampling approaches are prevalent in implicit collaborative filtering for obtaining negative labels from massive unlabeled data.

Collaborative Filtering

Scene Segmentation with Dual Relation-aware Attention Network

1 code implementation TNNLS 2020 Jun Fu, Jing Liu, Jie Jiang, Yong Li, Yongjun Bao, Hanqing Lu

We conduct extensive experiments to validate the effectiveness of our network and achieve new state-of-the-art segmentation performance on four challenging scene segmentation data sets, i. e., Cityscapes, ADE20K, PASCAL Context, and COCO Stuff data sets.

Relation Scene Segmentation +1

Reinforced Epidemic Control: Saving Both Lives and Economy

1 code implementation4 Aug 2020 Sirui Song, Zefang Zong, Yong Li, Xue Liu, Yang Yu

Saving lives or economy is a dilemma for epidemic control in most cities while smart-tracing technology raises people's privacy concerns.

reinforcement-learning Reinforcement Learning (RL)

DeepNetQoE: Self-adaptive QoE Optimization Framework of Deep Networks

no code implementations17 Jul 2020 Rui Wang, Min Chen, Nadra Guizani, Yong Li, Hamid Gharavi, Kai Hwang

A self-adaptive QoE model is set up that relates the model's accuracy with the computing resources required for training which will allow the experience value of the model to improve.

Crowd Counting

Generalizing Tensor Decomposition for N-ary Relational Knowledge Bases

1 code implementation8 Jul 2020 Yu Liu, Quanming Yao, Yong Li

With the rapid development of knowledge bases (KBs), link prediction task, which completes KBs with missing facts, has been broadly studied in especially binary relational KBs (a. k. a knowledge graph) with powerful tensor decomposition related methods.

Link Prediction Tensor Decomposition

Proving Non-Inclusion of Büchi Automata based on Monte Carlo Sampling

no code implementations5 Jul 2020 Yong Li, Andrea Turrini, Xuechao Sun, Lijun Zhang

While this is well-understood in the termination analysis of programs, this is not the case for the language inclusion analysis of B\"uchi automata, where research mainly focused on improving algorithms for proving language inclusion, with the search for counterexamples left to the expensive complementation operation.

Disentangling User Interest and Conformity for Recommendation with Causal Embedding

3 code implementations19 Jun 2020 Yu Zheng, Chen Gao, Xiang Li, Xiangnan He, Depeng Jin, Yong Li

We further demonstrate that the learned embeddings successfully capture the desired causes, and show that DICE guarantees the robustness and interpretability of recommendation.

Causal Inference

On the Power of Unambiguity in Büchi Complementation

no code implementations18 May 2020 Yong Li, Moshe Y. Vardi, Lijun Zhang

In this work, we exploit the power of \emph{unambiguity} for the complementation problem of B\"uchi automata by utilizing reduced run directed acyclic graphs (DAGs) over infinite words, in which each vertex has at most one predecessor.

Bundle Recommendation with Graph Convolutional Networks

1 code implementation7 May 2020 Jianxin Chang, Chen Gao, Xiangnan He, Yong Li, Depeng Jin

Existing solutions integrate user-item interaction modeling into bundle recommendation by sharing model parameters or learning in a multi-task manner, which cannot explicitly model the affiliation between items and bundles, and fail to explore the decision-making when a user chooses bundles.

Decision Making

Urban Anomaly Analytics: Description, Detection, and Prediction

no code implementations25 Apr 2020 Mingyang Zhang, Tong Li, Yue Yu, Yong Li, Pan Hui, Yu Zheng

Urban anomalies may result in loss of life or property if not handled properly.

Edge Intelligence: Architectures, Challenges, and Applications

no code implementations26 Mar 2020 Dianlei Xu, Tong Li, Yong Li, Xiang Su, Sasu Tarkoma, Tao Jiang, Jon Crowcroft, Pan Hui

Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis in locations close to where data is captured based on artificial intelligence.

Price-aware Recommendation with Graph Convolutional Networks

1 code implementation9 Mar 2020 Yu Zheng, Chen Gao, Xiangnan He, Yong Li, Depeng Jin

Price, an important factor in marketing --- which determines whether a user will make the final purchase decision on an item --- surprisingly, has received relatively little scrutiny.

Collaborative Filtering Marketing +1

Hybrid Compositional Reasoning for Reactive Synthesis from Finite-Horizon Specifications

1 code implementation19 Nov 2019 Suguman Bansal, Yong Li, Lucas M. Tabajara, Moshe Y. Vardi

Our approach utilizes both explicit and symbolic representations of the state-space, and effectively leverages their complementary strengths.

Adaptive Context Network for Scene Parsing

no code implementations ICCV 2019 Jun Fu, Jing Liu, Yuhang Wang, Yong Li, Yongjun Bao, Jinhui Tang, Hanqing Lu

Recent works attempt to improve scene parsing performance by exploring different levels of contexts, and typically train a well-designed convolutional network to exploit useful contexts across all pixels equally.

Scene Parsing Semantic Segmentation

UrbanRhythm: Revealing Urban Dynamics Hidden in Mobility Data

no code implementations3 Nov 2019 Sirui Song, Tong Xia, Depeng Jin, Pan Hui, Yong Li

In this paper, to reveal urban dynamics, we propose a novel system UrbanRhythm to reveal the urban dynamics hidden in human mobility data.

Clustering

Adversarial Representation Learning for Robust Patient-Independent Epileptic Seizure Detection

1 code implementation18 Sep 2019 Xiang Zhang, Lina Yao, Manqing Dong, Zhe Liu, Yu Zhang, Yong Li

Furthermore, to enhance the explainability, we develop an attention mechanism to automatically learn the importance of each EEG channels in the seizure diagnosis procedure.

EEG Electroencephalogram (EEG) +3

Efficient Neural Interaction Function Search for Collaborative Filtering

2 code implementations28 Jun 2019 Quanming Yao, Xiangning Chen, James Kwok, Yong Li, Cho-Jui Hsieh

Motivated by the recent success of automated machine learning (AutoML), we propose in this paper the search for simple neural interaction functions (SIF) in CF.

AutoML Collaborative Filtering

Self-Supervised Representation Learning From Videos for Facial Action Unit Detection

1 code implementation CVPR 2019 Yong Li, Jiabei Zeng, Shiguang Shan, Xilin Chen

In this paper, we aim to learn discriminative representation for facial action unit (AU) detection from large amount of videos without manual annotations.

Action Unit Detection Facial Action Unit Detection +2

LambdaOpt: Learn to Regularize Recommender Models in Finer Levels

1 code implementation28 May 2019 Yihong Chen, Bei Chen, Xiangnan He, Chen Gao, Yong Li, Jian-Guang Lou, Yue Wang

We show how to employ LambdaOpt on matrix factorization, a classical model that is representative of a large family of recommender models.

Hyperparameter Optimization Recommendation Systems

Learning Phase Competition for Traffic Signal Control

1 code implementation12 May 2019 Guanjie Zheng, Yuanhao Xiong, Xinshi Zang, Jie Feng, Hua Wei, Huichu Zhang, Yong Li, Kai Xu, Zhenhui Li

Increasingly available city data and advanced learning techniques have empowered people to improve the efficiency of our city functions.

Reinforcement Learning (RL)

AliGraph: A Comprehensive Graph Neural Network Platform

no code implementations23 Feb 2019 Rong Zhu, Kun Zhao, Hongxia Yang, Wei. Lin, Chang Zhou, Baole Ai, Yong Li, Jingren Zhou

An increasing number of machine learning tasks require dealing with large graph datasets, which capture rich and complex relationship among potentially billions of elements.

Distributed, Parallel, and Cluster Computing

A Noise-Sensitivity-Analysis-Based Test Prioritization Technique for Deep Neural Networks

no code implementations1 Jan 2019 Long Zhang, Xuechao Sun, Yong Li, Zhen-Yu Zhang

Deep neural networks (DNNs) have been widely used in the fields such as natural language processing, computer vision and image recognition.

Test

DeepDPM: Dynamic Population Mapping via Deep Neural Network

no code implementations25 Oct 2018 Zefang Zong, Jie Feng, Kechun Liu, Hongzhi Shi, Yong Li

In this paper, we first propose the idea to generate dynamic population distributions in full-time series, then we design dynamic population mapping via deep neural network(DeepDPM), a model that describes both spatial and temporal patterns using coarse data and point of interest information.

Population Mapping Super-Resolution +2

Learning to Recommend with Multiple Cascading Behaviors

no code implementations21 Sep 2018 Chen Gao, Xiangnan He, Dahua Gan, Xiangning Chen, Fuli Feng, Yong Li, Tat-Seng Chua, Lina Yao, Yang song, Depeng Jin

To fully exploit the signal in the data of multiple types of behaviors, we perform a joint optimization based on the multi-task learning framework, where the optimization on a behavior is treated as a task.

Multi-Task Learning Recommendation Systems

Dual Attention Network for Scene Segmentation

12 code implementations CVPR 2019 Jun Fu, Jing Liu, Haijie Tian, Yong Li, Yongjun Bao, Zhiwei Fang, Hanqing Lu

Specifically, we append two types of attention modules on top of traditional dilated FCN, which model the semantic interdependencies in spatial and channel dimensions respectively.

Position Segmentation +2

Smartphone App Usage Prediction Using Points of Interest

no code implementations26 Nov 2017 Donghan Yu, Yong Li, Fengli Xu, Pengyu Zhang, Vassilis Kostakos

In this paper we present the first population-level, city-scale analysis of application usage on smartphones.

Transfer Learning

Trajectory Recovery From Ash: User Privacy Is NOT Preserved in Aggregated Mobility Data

no code implementations21 Feb 2017 Fengli Xu, Zhen Tu, Yong Li, Pengyu Zhang, Xiao-Ming Fu, Depeng Jin

By conducting experiments on two real-world datasets collected from both mobile application and cellular network, we reveal that the attack system is able to recover users' trajectories with accuracy about 73%~91% at the scale of tens of thousands to hundreds of thousands users, which indicates severe privacy leakage in such datasets.

Computers and Society Cryptography and Security

Improving Deep Neural Network with Multiple Parametric Exponential Linear Units

1 code implementation1 Jun 2016 Yang Li, Chunxiao Fan, Yong Li, Qiong Wu, Yue Ming

In this paper, we first propose a new activation function, Multiple Parametric Exponential Linear Units (MPELU), aiming to generalize and unify the rectified and exponential linear units.

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