Search Results for author: Yang Li

Found 318 papers, 83 papers with code

Emotion Inference in Multi-Turn Conversations with Addressee-Aware Module and Ensemble Strategy

no code implementations EMNLP 2021 Dayu Li, Xiaodan Zhu, Yang Li, Suge Wang, Deyu Li, Jian Liao, Jianxing Zheng

Emotion inference in multi-turn conversations aims to predict the participant’s emotion in the next upcoming turn without knowing the participant’s response yet, and is a necessary step for applications such as dialogue planning.

ACFlow: Flow Models for Arbitrary Conditional Likelihoods

1 code implementation ICML 2020 Yang Li, Shoaib Akbar, Junier Oliva

However, a majority of generative modeling approaches are focused solely on the joint distribution $p(x)$ and utilize models where it is intractable to obtain the conditional distribution of some arbitrary subset of features $x_u$ given the rest of the observed covariates $x_o$: $p(x_u \mid x_o)$.


Tackling Cooperative Incompatibility for Zero-Shot Human-AI Coordination

no code implementations5 Jun 2023 Yang Li, Shao Zhang, Jichen Sun, WenHao Zhang, Yali Du, Ying Wen, Xinbing Wang, Wei Pan

Achieving coordination between humans and artificial intelligence in scenarios involving previously unencountered humans remains a substantial obstacle within Zero-Shot Human-AI Coordination, which aims to develop AI agents capable of efficiently working alongside previously unknown human teammates.

Improving Stability and Performance of Spiking Neural Networks through Enhancing Temporal Consistency

no code implementations23 May 2023 Dongcheng Zhao, Guobin Shen, Yiting Dong, Yang Li, Yi Zeng

Notably, our algorithm has achieved state-of-the-art performance on neuromorphic datasets DVS-CIFAR10 and N-Caltech101, and can achieve superior performance in the test phase with timestep T=1.

Dive into the Power of Neuronal Heterogeneity

no code implementations19 May 2023 Guobin Shen, Dongcheng Zhao, Yiting Dong, Yang Li, Yi Zeng

The biological neural network is a vast and diverse structure with high neural heterogeneity.

Continuous Control

Feature Chirality in Deep Learning Models

no code implementations6 May 2023 Shipeng Ji, Yang Li, Ruizhi Fu, Jiabao Wang, Zhuang Miao

As deep learning applications extensively increase by leaps and bounds, their interpretability has become increasingly prominent.

MH-DETR: Video Moment and Highlight Detection with Cross-modal Transformer

no code implementations29 Apr 2023 Yifang Xu, Yunzhuo Sun, Yang Li, Yilei Shi, Xiaoxiang Zhu, Sidan Du

With the increasing demand for video understanding, video moment and highlight detection (MHD) has emerged as a critical research topic.

Highlight Detection Video Understanding

MINN: Learning the dynamics of differential-algebraic equations and application to battery modeling

no code implementations27 Apr 2023 Yicun Huang, Changfu Zou, Yang Li, Torsten Wik

The concept of integrating physics-based and data-driven approaches has become popular for modeling sustainable energy systems.

OpenBox: A Python Toolkit for Generalized Black-box Optimization

1 code implementation26 Apr 2023 Huaijun Jiang, Yu Shen, Yang Li, Wentao Zhang, Ce Zhang, Bin Cui

Black-box optimization (BBO) has a broad range of applications, including automatic machine learning, experimental design, and database knob tuning.

Experimental Design

Binary stochasticity enabled highly efficient neuromorphic deep learning achieves better-than-software accuracy

no code implementations25 Apr 2023 Yang Li, Wei Wang, Ming Wang, Chunmeng Dou, Zhengyu Ma, Huihui Zhou, Peng Zhang, Nicola Lepri, Xumeng Zhang, Qing Luo, Xiaoxin Xu, Guanhua Yang, Feng Zhang, Ling Li, Daniele Ielmini, Ming Liu

We propose a binary stochastic learning algorithm that modifies all elementary neural network operations, by introducing (i) stochastic binarization of both the forwarding signals and the activation function derivatives, (ii) signed binarization of the backpropagating errors, and (iii) step-wised weight updates.


Road Genome: A Topology Reasoning Benchmark for Scene Understanding in Autonomous Driving

1 code implementation20 Apr 2023 Huijie Wang, Zhenbo Liu, Yang Li, Tianyu Li, Li Chen, Chonghao Sima, Yuting Wang, Shengyin Jiang, Feng Wen, Hang Xu, Ping Luo, Junchi Yan, Wei zhang, Jun Yao, Yu Qiao, Hongyang Li

By introducing Road Genome (OpenLane-V2), we intend to shift the community's attention and take a step further beyond perception - to the task of topology reasoning for scene structure.

3D Lane Detection Autonomous Driving +1

Multi-Microgrid Collaborative Optimization Scheduling Using an Improved Multi-Agent Soft Actor-Critic Algorithm

no code implementations1 Apr 2023 Jiankai Gao, Yang Li, Bin Wang, Haibo Wu

The implementation of a multi-microgrid (MMG) system with multiple renewable energy sources enables the facilitation of electricity trading.

Algorithm AutoML +4

CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Evaluations on HumanEval-X

1 code implementation30 Mar 2023 Qinkai Zheng, Xiao Xia, Xu Zou, Yuxiao Dong, Shan Wang, Yufei Xue, Zihan Wang, Lei Shen, Andi Wang, Yang Li, Teng Su, Zhilin Yang, Jie Tang

Large pre-trained code generation models, such as OpenAI Codex, can generate syntax- and function-correct code, making the coding of programmers more productive and our pursuit of artificial general intelligence closer.

Code Generation

MSAT: Biologically Inspired Multi-Stage Adaptive Threshold for Conversion of Spiking Neural Networks

no code implementations23 Mar 2023 Xiang He, Yang Li, Dongcheng Zhao, Qingqun Kong, Yi Zeng

The self-adaptation to membrane potential and input allows a timely adjustment of the threshold to fire spike faster and transmit more information.

Sentiment Analysis Sentiment Classification +2

Improving the Performance of Spiking Neural Networks on Event-based Datasets with Knowledge Transfer

no code implementations23 Mar 2023 Xiang He, Dongcheng Zhao, Yang Li, Guobin Shen, Qingqun Kong, Yi Zeng

To enhance the generalizability of SNNs on event-based datasets, we propose a knowledge-transfer framework that leverages static images to assist in the training on neuromorphic datasets.

Transfer Learning

Ensemble Nonlinear Model Predictive Control for Residential Solar-Battery Energy Management

no code implementations18 Mar 2023 Yang Li, D. Mahinda Vilathgamuwa, Daniel E. Quevedo, Chih Feng Lee, Changfu Zou

In a dynamic distribution market environment, residential prosumers with solar power generation and battery energy storage devices can flexibly interact with the power grid via power exchange.

energy management Management

Mpox-AISM: AI-Mediated Super Monitoring for Forestalling Monkeypox Spread

no code implementations17 Mar 2023 Yubiao Yue, Zhenzhang Li, Xinyue Zhang, Jialong Xu, Jinbao Liu, Yang Li

The challenge on forestalling monkeypox (Mpox) spread is the timely, convenient and accurate diagnosis for earlystage infected individuals.

Data Augmentation Self-Supervised Learning +1

A Unified and Efficient Coordinating Framework for Autonomous DBMS Tuning

no code implementations10 Mar 2023 Xinyi Zhang, Zhuo Chang, Hong Wu, Yang Li, Jia Chen, Jian Tan, Feifei Li, Bin Cui

To tune different components for DBMS, a coordinating mechanism is needed to make the multiple agents cognizant of each other.

Thompson Sampling

Attention-based Graph Convolution Fusing Latent Structures and Multiple Features for Graph Neural Networks

1 code implementation2 Mar 2023 Yang Li, Yuichi Tanaka

Instead, we propose two methods to improve the representational power of AGCs by utilizing 1) structural information in a high-dimensional space and 2) multiple attention functions when calculating their weights.

Transfer Learning for Bayesian Optimization: A Survey

no code implementations12 Feb 2023 Tianyi Bai, Yang Li, Yu Shen, Xinyi Zhang, Wentao Zhang, Bin Cui

A wide spectrum of design and decision problems, including parameter tuning, A/B testing and drug design, intrinsically are instances of black-box optimization.

Bayesian Optimization Transfer Learning

Cooperative Open-ended Learning Framework for Zero-shot Coordination

no code implementations9 Feb 2023 Yang Li, Shao Zhang, Jichen Sun, Yali Du, Ying Wen, Xinbing Wang, Wei Pan

However, these approaches can result in a loss of learning and an inability to cooperate with certain strategies within the population, known as cooperative incompatibility.

Rover: An online Spark SQL tuning service via generalized transfer learning

no code implementations8 Feb 2023 Yu Shen, Xinyuyang Ren, Yupeng Lu, Huaijun Jiang, Huanyong Xu, Di Peng, Yang Li, Wentao Zhang, Bin Cui

When applying transfer learning to accelerate the tuning process, we notice two domain-specific challenges: 1) most previous work focus on transferring tuning history, while expert knowledge from Spark engineers is of great potential to improve the tuning performance but is not well studied so far; 2) history tasks should be carefully utilized, where using dissimilar ones lead to a deteriorated performance in production.

Bayesian Optimization Transfer Learning

DivBO: Diversity-aware CASH for Ensemble Learning

no code implementations7 Feb 2023 Yu Shen, Yupeng Lu, Yang Li, Yaofeng Tu, Wentao Zhang, Bin Cui

To tackle this issue and further enhance the ensemble performance, we propose DivBO, a diversity-aware framework to inject explicit search of diversity into the CASH problems.

AutoML Bayesian Optimization +1

HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline

no code implementations4 Feb 2023 Yang Li, Xinyan Chen, Wenxuan Guo, Xijun Li, Wanqian Luo, Junhua Huang, Hui-Ling Zhen, Mingxuan Yuan, Junchi Yan

Industrial SAT formula generation is a critical yet challenging task for heuristic development and the surging learning-based methods in practical SAT applications.

PLay: Parametrically Conditioned Layout Generation using Latent Diffusion

no code implementations27 Jan 2023 Chin-Yi Cheng, Forrest Huang, Gang Li, Yang Li

Layout design is an important task in various design fields, including user interfaces, document, and graphic design.

Layout Design

HTTE: A Hybrid Technique For Travel Time Estimation In Sparse Data Environments

no code implementations12 Jan 2023 Nikolaos Zygouras, Nikolaos Panagiotou, Yang Li, Dimitrios Gunopulos, Leonidas Guibas

Travel time estimation is a critical task, useful to many urban applications at the individual citizen and the stakeholder level.

Finding the Most Transferable Tasks for Brain Image Segmentation

no code implementations3 Jan 2023 Yicong Li, Yang Tan, Jingyun Yang, Yang Li, Xiao-Ping Zhang

Furthermore, within the same modality, transferring from the source task that has stronger RoI shape similarity with the target task can significantly improve the final transfer performance.

Brain Image Segmentation Image Segmentation +2

Federated Multi-Agent Deep Reinforcement Learning Approach via Physics-Informed Reward for Multi-Microgrid Energy Management

no code implementations29 Dec 2022 Yuanzheng Li, Shangyang He, Yang Li, Yang Shi, Zhigang Zeng

Then, these local models are periodically uploaded to a server and their parameters are aggregated to build a global agent, which will be broadcasted to MGs and replace their local agents.

energy management Federated Learning +4

An Information-Theoretic Approach to Transferability in Task Transfer Learning

no code implementations20 Dec 2022 Yajie Bao, Yang Li, Shao-Lun Huang, Lin Zhang, Lizhong Zheng, Amir Zamir, Leonidas Guibas

Task transfer learning is a popular technique in image processing applications that uses pre-trained models to reduce the supervision cost of related tasks.

Model Selection Transfer Learning

ENGNN: A General Edge-Update Empowered GNN Architecture for Radio Resource Management in Wireless Networks

no code implementations14 Dec 2022 Yunqi Wang, Yang Li, Qingjiang Shi, Yik-Chung Wu

In order to achieve high data rate and ubiquitous connectivity in future wireless networks, a key task is to efficiently manage the radio resource by judicious beamforming and power allocation.


Super-resolution Probabilistic Rain Prediction from Satellite Data Using 3D U-Nets and EarthFormers

1 code implementation6 Dec 2022 Yang Li, Haiyu Dong, Zuliang Fang, Jonathan Weyn, Pete Luferenko

To further improve the model performance, multi-model ensemble and threshold optimization were used to produce the final probabilistic rain prediction.

Decision Making Super-Resolution

Learning Cooperative Beamforming with Edge-Update Empowered Graph Neural Networks

no code implementations23 Nov 2022 Yunqi Wang, Yang Li, Qingjiang Shi, Yik-Chung Wu

However, the current GNNs are only equipped with the node-update mechanism, which restricts it from modeling more complicated problems such as the cooperative beamforming design, where the beamformers are on the graph edges of wireless networks.

A Dual-scale Lead-seperated Transformer With Lead-orthogonal Attention And Meta-information For Ecg Classification

no code implementations23 Nov 2022 Yang Li, Guijin Wang, Zhourui Xia, Wenming Yang, Li Sun

Auxiliary diagnosis of cardiac electrophysiological status can be obtained through the analysis of 12-lead electrocardiograms (ECGs).

ECG Classification

Learn from Yesterday: A Semi-Supervised Continual Learning Method for Supervision-Limited Text-to-SQL Task Streams

1 code implementation21 Nov 2022 Yongrui Chen, Xinnan Guo, Tongtong Wu, Guilin Qi, Yang Li, Yang Dong

The first solution Vanilla is to perform self-training, augmenting the supervised training data with predicted pseudo-labeled instances of the current task, while replacing the full volume retraining with episodic memory replay to balance the training efficiency with the performance of previous tasks.

Continual Learning Text-To-SQL

Hierarchical Estimation for Effective and Efficient Sampling Graph Neural Network

no code implementations16 Nov 2022 Yang Li, Bingbing Xu, Qi Cao, Yige Yuan, HuaWei Shen

On account that previous studies either lacks variance analysis or only focus on a particular sampling paradigm, we firstly propose an unified node sampling variance analysis framework and analyze the core challenge "circular dependency" for deriving the minimum variance sampler, i. e., sampling probability depends on node embeddings while node embeddings can not be calculated until sampling is finished.

Time Series Analysis

Accounting for Temporal Variability in Functional Magnetic Resonance Imaging Improves Prediction of Intelligence

1 code implementation11 Nov 2022 Yang Li, Xin Ma, Raj Sunderraman, Shihao Ji, Suprateek Kundu

We compare the prediction performance for different intelligence measures based on static FC, dynamic FC, and region level time series acquired from the Adolescent Brain Cognitive Development (ABCD) study involving close to 7000 individuals.

feature selection Time Series Analysis

CCPrompt: Counterfactual Contrastive Prompt-Tuning for Many-Class Classification

no code implementations11 Nov 2022 Yang Li, Canran Xu, Tao Shen, Jing Jiang, Guodong Long

The sharing task description is unable to stimulate the unique task-related information in each training sample, especially for tasks with the finite-label space.

Classification Entity Typing +5

A Random Forest and Current Fault Texture Feature-Based Method for Current Sensor Fault Diagnosis in Three-Phase PWM VSR

no code implementations8 Nov 2022 Lei Kou, Xiao-dong Gong, Yi Zheng, Xiu-hui Ni, Yang Li, Quan-de Yuan, Ya-nan Dong

The current sensor faults may bring hidden danger or damage to the whole system; therefore, this paper proposed a random forest (RF) and current fault texture feature-based method for current sensor fault diagnosis in three-phase PWM VSR systems.

Fault Detection

Factorized Blank Thresholding for Improved Runtime Efficiency of Neural Transducers

no code implementations2 Nov 2022 Duc Le, Frank Seide, Yuhao Wang, Yang Li, Kjell Schubert, Ozlem Kalinli, Michael L. Seltzer

We show how factoring the RNN-T's output distribution can significantly reduce the computation cost and power consumption for on-device ASR inference with no loss in accuracy.

Wind Power Forecasting Considering Data Privacy Protection: A Federated Deep Reinforcement Learning Approach

no code implementations2 Nov 2022 Yang Li, Ruinong Wang, Yuanzheng Li, Meng Zhang, Chao Long

To handle the data privacy and openness, we propose a forecasting scheme that combines federated learning and deep reinforcement learning (DRL) for ultra-short-term wind power forecasting, called federated deep reinforcement learning (FedDRL).

Federated Learning Privacy Preserving +2

Review on Monitoring, Operation and Maintenance of Smart Offshore Wind Farms

no code implementations1 Nov 2022 Lei Kou, Yang Li, Fangfang Zhang, Xiaodong Gong, Yinghong Hu, Quande Yuan, Wende Ke

In recent years, with the development of wind energy, the number and scale of wind farms are developing rapidly.

Self-supervised Graph-based Point-of-interest Recommendation

no code implementations22 Oct 2022 Yang Li, Tong Chen, Peng-Fei Zhang, Zi Huang, Hongzhi Yin

In order to counteract the scarcity and incompleteness of POI check-ins, we propose a novel self-supervised learning paradigm in \ssgrec, where the trajectory representations are contrastively learned from two augmented views on geolocations and temporal transitions.

Self-Supervised Learning

Understanding Embodied Reference with Touch-Line Transformer

1 code implementation11 Oct 2022 Yang Li, Xiaoxue Chen, Hao Zhao, Jiangtao Gong, Guyue Zhou, Federico Rossano, Yixin Zhu

Human studies have revealed that objects referred to or pointed to do not lie on the elbow-wrist line, a common misconception; instead, they lie on the so-called virtual touch line.

Contrastive Bayesian Analysis for Deep Metric Learning

1 code implementation10 Oct 2022 Shichao Kan, Zhiquan He, Yigang Cen, Yang Li, Vladimir Mladenovic, Zhihai He

Recent methods for deep metric learning have been focusing on designing different contrastive loss functions between positive and negative pairs of samples so that the learned feature embedding is able to pull positive samples of the same class closer and push negative samples from different classes away from each other.

Contrastive Learning Metric Learning

Spotlight: Mobile UI Understanding using Vision-Language Models with a Focus

no code implementations29 Sep 2022 Gang Li, Yang Li

Specifically, we enhance a vision-language model that only takes the screenshot of the UI and a region of interest on the screen -- the focus -- as the input.

Language Modelling Multi-Task Learning

MUG: Interactive Multimodal Grounding on User Interfaces

no code implementations29 Sep 2022 Tao Li, Gang Li, Jingjie Zheng, Purple Wang, Yang Li

To investigate the problem, we create a new dataset that consists of 77, 820 sequences of human user-agent interaction on mobile interfaces in which 20% involves multiple rounds of interactions.

Controlling mean exit time of stochastic dynamical systems based on quasipotential and machine learning

no code implementations27 Sep 2022 Yang Li, Shenglan Yuan, Shengyuan Xu

The mean exit time escaping basin of attraction in the presence of white noise is of practical importance in various scientific fields.

Optimal dispatch of low-carbon integrated energy system considering nuclear heating and carbon trading

no code implementations24 Sep 2022 Yang Li, Fanjin Bu, Jiankai Gao, Guoqing Lia

The development of miniaturized nuclear power (NP) units and the improvement of the carbon trading market provide a new way to realize the low-carbon operation of integrated energy systems (IES).


Enabling Conversational Interaction with Mobile UI using Large Language Models

1 code implementation18 Sep 2022 Bryan Wang, Gang Li, Yang Li

This paper investigates the feasibility of enabling versatile conversational interactions with mobile UIs using a single LLM.

SDFE-LV: A Large-Scale, Multi-Source, and Unconstrained Database for Spotting Dynamic Facial Expressions in Long Videos

no code implementations18 Sep 2022 Xiaolin Xu, Yuan Zong, Wenming Zheng, Yang Li, Chuangao Tang, Xingxun Jiang, Haolin Jiang

In this paper, we present a large-scale, multi-source, and unconstrained database called SDFE-LV for spotting the onset and offset frames of a complete dynamic facial expression from long videos, which is known as the topic of dynamic facial expression spotting (DFES) and a vital prior step for lots of facial expression analysis tasks.

Deep Learning-Based Automatic Diagnosis System for Developmental Dysplasia of the Hip

no code implementations7 Sep 2022 Yang Li, Leo Yan Li-Han, Hua Tian

To the best of our knowledge, this is the first study for objective DDH diagnosis by leveraging deep learning keypoint detection and integrating different anatomical measurements, which can provide reliable and explainable support for clinical decision-making.

Decision Making Keypoint Detection

Video-based Cross-modal Auxiliary Network for Multimodal Sentiment Analysis

1 code implementation30 Aug 2022 Rongfei Chen, Wenju Zhou, Yang Li, Huiyu Zhou

Multimodal sentiment analysis has a wide range of applications due to its information complementarity in multimodal interactions.

Classification Image Classification +1

Distance-Aware Occlusion Detection with Focused Attention

1 code implementation23 Aug 2022 Yang Li, Yucheng Tu, Xiaoxue Chen, Hao Zhao, Guyue Zhou

In this work, (1) we propose a novel three-decoder architecture as the infrastructure for focused attention; 2) we use the generalized intersection box prediction task to effectively guide our model to focus on occlusion-specific regions; 3) our model achieves a new state-of-the-art performance on distance-aware relationship detection.

Human-Object Interaction Detection Relationship Detection +1

Resilience assessment and improvement for electric power transmission systems against typhoon disasters: A data-model hybrid driven approach

no code implementations19 Aug 2022 Rui Yang, Yang Li

In response to the damage to electric power transmission systems caused by typhoon disasters in coastal areas, a planning-targeted resilience assessment framework that considers the impact of multiple factors is established to accurately find the weak links of the transmission system and improve the system resilience.

GraphTTA: Test Time Adaptation on Graph Neural Networks

no code implementations19 Aug 2022 Guanzi Chen, Jiying Zhang, Xi Xiao, Yang Li

In this paper, we present a novel test time adaptation strategy named Graph Adversarial Pseudo Group Contrast (GAPGC), for graph neural networks TTA, to better adapt to the Out Of Distribution (OOD) test data.

Contrastive Learning

Human Decision Makings on Curriculum Reinforcement Learning with Difficulty Adjustment

no code implementations4 Aug 2022 Yilei Zeng, Jiali Duan, Yang Li, Emilio Ferrara, Lerrel Pinto, C. -C. Jay Kuo, Stefanos Nikolaidis

In this work, we guide the curriculum reinforcement learning results towards a preferred performance level that is neither too hard nor too easy via learning from the human decision process.

reinforcement-learning Reinforcement Learning (RL)

A Real-time Edge-AI System for Reef Surveys

no code implementations1 Aug 2022 Yang Li, Jiajun Liu, Brano Kusy, Ross Marchant, Brendan Do, Torsten Merz, Joey Crosswell, Andy Steven, Lachlan Tychsen-Smith, David Ahmedt-Aristizabal, Jeremy Oorloff, Peyman Moghadam, Russ Babcock, Megha Malpani, Ard Oerlemans

Crown-of-Thorn Starfish (COTS) outbreaks are a major cause of coral loss on the Great Barrier Reef (GBR) and substantial surveillance and control programs are ongoing to manage COTS populations to ecologically sustainable levels.

object-detection Object Detection

A Universal PINNs Method for Solving Partial Differential Equations with a Point Source

1 code implementation Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence 2022 Xiang Huang, Hongsheng Liu, Beiji Shi, Zidong Wang, Kang Yang, Yang Li, Min Wang, Haotian Chu, Jing Zhou, Fan Yu, Bei Hua, Bin Dong, Lei Chen

In recent years, deep learning technology has been used to solve partial differential equations (PDEs), among which the physics-informed neural networks (PINNs)method emerges to be a promising method for solving both forward and inverse PDE problems.

BrainCog: A Spiking Neural Network based Brain-inspired Cognitive Intelligence Engine for Brain-inspired AI and Brain Simulation

no code implementations18 Jul 2022 Yi Zeng, Dongcheng Zhao, Feifei Zhao, Guobin Shen, Yiting Dong, Enmeng Lu, Qian Zhang, Yinqian Sun, Qian Liang, Yuxuan Zhao, Zhuoya Zhao, Hongjian Fang, Yuwei Wang, Yang Li, Xin Liu, Chengcheng Du, Qingqun Kong, Zizhe Ruan, Weida Bi

These brain-inspired AI models have been effectively validated on various supervised, unsupervised, and reinforcement learning tasks, and they can be used to enable AI models to be with multiple brain-inspired cognitive functions.

Decision Making

Transferability-Guided Cross-Domain Cross-Task Transfer Learning

no code implementations12 Jul 2022 Yang Tan, Yang Li, Shao-Lun Huang, Xiao-Ping Zhang

We propose two novel transferability metrics F-OTCE (Fast Optimal Transport based Conditional Entropy) and JC-OTCE (Joint Correspondence OTCE) to evaluate how much the source model (task) can benefit the learning of the target task and to learn more transferable representations for cross-domain cross-task transfer learning.

Transfer Learning

Generalizing to Unseen Domains with Wasserstein Distributional Robustness under Limited Source Knowledge

no code implementations11 Jul 2022 Jingge Wang, Liyan Xie, Yao Xie, Shao-Lun Huang, Yang Li

Domain generalization aims at learning a universal model that performs well on unseen target domains, incorporating knowledge from multiple source domains.

Domain Generalization Rotated MNIST

An Unsupervised STDP-based Spiking Neural Network Inspired By Biologically Plausible Learning Rules and Connections

no code implementations6 Jul 2022 Yiting Dong, Dongcheng Zhao, Yang Li, Yi Zeng

By integrating the above three adaptive mechanisms and STB-STDP, our model greatly accelerates the training of unsupervised spiking neural networks and improves the performance of unsupervised SNNs on complex tasks.

Spike Calibration: Fast and Accurate Conversion of Spiking Neural Network for Object Detection and Segmentation

no code implementations6 Jul 2022 Yang Li, Xiang He, Yiting Dong, Qingqun Kong, Yi Zeng

Spiking neural network (SNN) has been attached to great importance due to the properties of high biological plausibility and low energy consumption on neuromorphic hardware.

Bayesian Optimization object-detection +1

Auto-Encoder-Extreme Learning Machine Model for Boiler NOx Emission Concentration Prediction

no code implementations29 Jun 2022 Zhenhao Tang, Shikui Wang, Xiangying Chai, Shengxian Cao, Tinghui Ouyang, Yang Li

An automatic encoder (AE) extreme learning machine (ELM)-AE-ELM model is proposed to predict the NOx emission concentration based on the combination of mutual information algorithm (MI), AE, and ELM.

Warped Convolutional Networks: Bridge Homography to sl(3) algebra by Group Convolution

no code implementations23 Jun 2022 Xinrui Zhan, Yang Li, Wenyu Liu, Jianke Zhu

In this paper, we propose Warped Convolution Networks (WCN) to effectively learn and represent the homography by SL(3) group and sl(3) algebra with group convolution.

Homography Estimation Object Tracking

Efficient End-to-End AutoML via Scalable Search Space Decomposition

1 code implementation19 Jun 2022 Yang Li, Yu Shen, Wentao Zhang, Ce Zhang, Bin Cui

End-to-end AutoML has attracted intensive interests from both academia and industry which automatically searches for ML pipelines in a space induced by feature engineering, algorithm/model selection, and hyper-parameter tuning.

AutoML Feature Engineering +1

NAFS: A Simple yet Tough-to-beat Baseline for Graph Representation Learning

2 code implementations17 Jun 2022 Wentao Zhang, Zeang Sheng, Mingyu Yang, Yang Li, Yu Shen, Zhi Yang, Bin Cui

First, GNNs can learn higher-order structural information by stacking more layers but can not deal with large depth due to the over-smoothing issue.

Graph Representation Learning Link Prediction +1

Level 2 Autonomous Driving on a Single Device: Diving into the Devils of Openpilot

no code implementations16 Jun 2022 Li Chen, Tutian Tang, Zhitian Cai, Yang Li, Penghao Wu, Hongyang Li, Jianping Shi, Junchi Yan, Yu Qiao

Equipped with a wide span of sensors, predominant autonomous driving solutions are becoming more modular-oriented for safe system design.

Autonomous Driving

Graph Attention Multi-Layer Perceptron

1 code implementation9 Jun 2022 Wentao Zhang, Ziqi Yin, Zeang Sheng, Yang Li, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, Bin Cui

Graph neural networks (GNNs) have achieved great success in many graph-based applications.

Graph Attention

TransBO: Hyperparameter Optimization via Two-Phase Transfer Learning

no code implementations6 Jun 2022 Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Zhi Yang, Ce Zhang, Bin Cui

With the extensive applications of machine learning models, automatic hyperparameter optimization (HPO) has become increasingly important.

Hyperparameter Optimization Neural Architecture Search +2

Transfer Learning based Search Space Design for Hyperparameter Tuning

no code implementations6 Jun 2022 Yang Li, Yu Shen, Huaijun Jiang, Tianyi Bai, Wentao Zhang, Ce Zhang, Bin Cui

The extensive experiments show that our approach considerably boosts BO by designing a promising and compact search space instead of using the entire space, and outperforms the state-of-the-arts on a wide range of benchmarks, including machine learning and deep learning tuning tasks, and neural architecture search.

Bayesian Optimization BIG-bench Machine Learning +2

Data Encryption based on 9D Complex Chaotic System with Quaternion for Smart Grid

no code implementations3 Jun 2022 Fangfang Zhang, Zhe Huang, Lei Kou, Yang Li, Maoyong Cao, Fengying Ma

In this paper, a new 9D complex chaotic system with quaternion is proposed for the encryption of smart grid data.


Non-rigid Point Cloud Registration with Neural Deformation Pyramid

1 code implementation25 May 2022 Yang Li, Tatsuya Harada

Non-rigid point cloud registration is a key component in many computer vision and computer graphics applications.

Point Cloud Registration

Demand Response Method Considering Multiple Types of Flexible Loads in Industrial Parks

no code implementations24 May 2022 Jia Cui, Mingze Gao, Xiaoming Zhou, Yang Li, Wei Liu, Jiazheng Tian, XiMing Zhang

With the rapid development of the energy internet, the proportion of flexible loads in smart grid is getting much higher than before.

Multi-Agent Feedback Enabled Neural Networks for Intelligent Communications

1 code implementation22 May 2022 Fanglei Sun, Yang Li, Ying Wen, Jingchen Hu, Jun Wang, Yang Yang, Kai Li

The design of MAFENN framework and algorithm are dedicated to enhance the learning capability of the feedfoward DL networks or their variations with the simple data feedback.

Denoising Intelligent Communication

A BCS-GDE Multi-objective Optimization Algorithm for Combined Cooling, Heating and Power Model with Decision Strategies

no code implementations19 May 2022 Jiaze Sun, Jiahui Deng, Yang Li, Nan Han

The simulation results show that the model established in this paper can reduce economic cost by 72%, primary energy consumption by 73%, and pollutant emission by 88%.

Decision Making Scheduling

Cross-Utterance Conditioned VAE for Non-Autoregressive Text-to-Speech

1 code implementation ACL 2022 Yang Li, Cheng Yu, Guangzhi Sun, Hua Jiang, Fanglei Sun, Weiqin Zu, Ying Wen, Yang Yang, Jun Wang

Modelling prosody variation is critical for synthesizing natural and expressive speech in end-to-end text-to-speech (TTS) systems.

Deep-Attack over the Deep Reinforcement Learning

no code implementations2 May 2022 Yang Li, Quan Pan, Erik Cambria

Recent adversarial attack developments have made reinforcement learning more vulnerable, and different approaches exist to deploy attacks against it, where the key is how to choose the right timing of the attack.

Adversarial Attack reinforcement-learning +1

Phase Shift Design in RIS Empowered Wireless Networks: From Optimization to AI-Based Methods

no code implementations28 Apr 2022 Zongze Li, Shuai Wang, Qingfeng Lin, Yang Li, Miaowen Wen, Yik-Chung Wu, H. Vincent Poor

Reconfigurable intelligent surfaces (RISs) have a revolutionary capability to customize the radio propagation environment for wireless networks.

Efficient and Accurate Conversion of Spiking Neural Network with Burst Spikes

1 code implementation28 Apr 2022 Yang Li, Yi Zeng

Spiking neural network (SNN), as a brain-inspired energy-efficient neural network, has attracted the interest of researchers.

Efficient Neural Network

Probabilistic Charging Power Forecast of EVCS: Reinforcement Learning Assisted Deep Learning Approach

no code implementations17 Apr 2022 Yuanzheng Li, Shangyang He, Yang Li, Leijiao Ge, Suhua Lou, Zhigang Zeng

This paper tackles this issue by proposing a reinforcement learning assisted deep learning framework for the probabilistic EVCS charging power forecasting to capture its uncertainties.

reinforcement-learning Reinforcement Learning (RL) +1

Chinese Idiom Paraphrasing

1 code implementation15 Apr 2022 Jipeng Qiang, Yang Li, Chaowei Zhang, Yun Li, Yunhao Yuan, Yi Zhu, Xindong Wu

Idioms, are a kind of idiomatic expression in Chinese, most of which consist of four Chinese characters.

Machine Translation Paraphrase Generation

GMSS: Graph-Based Multi-Task Self-Supervised Learning for EEG Emotion Recognition

1 code implementation12 Apr 2022 Yang Li, Ji Chen, Fu Li, Boxun Fu, Hao Wu, Youshuo Ji, Yijin Zhou, Yi Niu, Guangming Shi, Wenming Zheng

GMSS has the ability to learn more general representations by integrating multiple self-supervised tasks, including spatial and frequency jigsaw puzzle tasks, and contrastive learning tasks.

Contrastive Learning EEG Emotion Recognition +2

Predicting and Explaining Mobile UI Tappability with Vision Modeling and Saliency Analysis

1 code implementation5 Apr 2022 Eldon Schoop, Xin Zhou, Gang Li, Zhourong Chen, Björn Hartmann, Yang Li

We use a deep learning based approach to predict whether a selected element in a mobile UI screenshot will be perceived by users as tappable, based on pixels only instead of view hierarchies required by previous work.

Data and Physics Driven Learning Models for Fast MRI -- Fundamentals and Methodologies from CNN, GAN to Attention and Transformers

no code implementations1 Apr 2022 Jiahao Huang, Yingying Fang, Yang Nan, Huanjun Wu, Yinzhe Wu, Zhifan Gao, Yang Li, Zidong Wang, Pietro Lio, Daniel Rueckert, Yonina C. Eldar, Guang Yang

Research studies have shown no qualms about using data driven deep learning models for downstream tasks in medical image analysis, e. g., anatomy segmentation and lesion detection, disease diagnosis and prognosis, and treatment planning.

Anatomy Explainable Models +2

Preventing Over-Smoothing for Hypergraph Neural Networks

no code implementations31 Mar 2022 Guanzi Chen, Jiying Zhang, Xi Xiao, Yang Li

In recent years, hypergraph learning has attracted great attention due to its capacity in representing complex and high-order relationships.

Multi-source data processing and fusion method for power distribution internet of things based on edge intelligence

no code implementations30 Mar 2022 Quande Yuan, Yuzhen Pi, Lei Kou, Fangfang Zhang, Yang Li, Zhenming Zhang

In this paper, an edge intelligence-based PD-IoT multi-source data processing and fusion method is proposed to solve the problems of confusing storage and insufficient fusion computing performance of multi-source heterogeneous distribution data.

PersFormer: 3D Lane Detection via Perspective Transformer and the OpenLane Benchmark

2 code implementations21 Mar 2022 Li Chen, Chonghao Sima, Yang Li, Zehan Zheng, Jiajie Xu, Xiangwei Geng, Hongyang Li, Conghui He, Jianping Shi, Yu Qiao, Junchi Yan

Methods for 3D lane detection have been recently proposed to address the issue of inaccurate lane layouts in many autonomous driving scenarios (uphill/downhill, bump, etc.).

3D Lane Detection Autonomous Driving +1

Bridging Pre-trained Language Models and Hand-crafted Features for Unsupervised POS Tagging

1 code implementation Findings (ACL) 2022 Houquan Zhou, Yang Li, Zhenghua Li, Min Zhang

In recent years, large-scale pre-trained language models (PLMs) have made extraordinary progress in most NLP tasks.


Efficient Training of the Memristive Deep Belief Net Immune to Non-Idealities of the Synaptic Devices

no code implementations15 Mar 2022 Wei Wang, Barak Hoffer, Tzofnat Greenberg-Toledo, Yang Li, Minhui Zou, Eric Herbelin, Ronny Ronen, Xiaoxin Xu, Yulin Zhao, Jianguo Yang, Shahar Kvatinsky

Nevertheless, the implementation of the VMM needs complex peripheral circuits and the complexity further increases since non-idealities of memristive devices prevent precise conductance tuning (especially for the online training) and largely degrade the performance of the deep neural networks (DNNs).

A Robust Approach for the Decomposition of High-Energy-Consuming Industrial Loads with Deep Learning

no code implementations11 Mar 2022 Jia Cui, Yonghui Jin, Renzhe Yu, Martin Onyeka Okoye, Yang Li, Junyou Yang, Shunjiang Wang

The commonly used parameters in a conventional method are however inapplicable in high-energy-consuming industrial loads.

HDL: Hybrid Deep Learning for the Synthesis of Myocardial Velocity Maps in Digital Twins for Cardiac Analysis

no code implementations9 Mar 2022 Xiaodan Xing, Javier Del Ser, Yinzhe Wu, Yang Li, Jun Xia, Lei Xu, David Firmin, Peter Gatehouse, Guang Yang

A core part of digital healthcare twins is model-based data synthesis, which permits the generation of realistic medical signals without requiring to cope with the modelling complexity of anatomical and biochemical phenomena producing them in reality.

Decision Making Left Ventricle Segmentation

PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm

1 code implementation1 Mar 2022 Wentao Zhang, Yu Shen, Zheyu Lin, Yang Li, Xiaosen Li, Wen Ouyang, Yangyu Tao, Zhi Yang, Bin Cui

Through deconstructing the message passing mechanism, PasCa presents a novel Scalable Graph Neural Architecture Paradigm (SGAP), together with a general architecture design space consisting of 150k different designs.

Neural Architecture Search

Bridge the Gap between Supervised and Unsupervised Learning for Fine-Grained Classification

no code implementations1 Mar 2022 Jiabao Wang, Yang Li, Xiu-Shen Wei, Hang Li, Zhuang Miao, Rui Zhang

Unsupervised learning technology has caught up with or even surpassed supervised learning technology in general object classification (GOC) and person re-identification (re-ID).

Clustering Contrastive Learning +3

Active and Passive Hybrid Detection Method for Power CPS False Data Injection Attacks with Improved AKF and GRU-CNN

no code implementations14 Feb 2022 Zhaoyang Qu, Xiaoyong Bo, Tong Yu, Yaowei Liu, Yunchang Dong, Zhongfeng Kan, Lei Wang, Yang Li

Taking account of the fact that the existing knowledge-driven detection process for FDIAs has been in a passive detection state for a long time and ignores the advantages of data-driven active capture of features, an active and passive hybrid detection method for power CPS FDIAs with improved adaptive Kalman filter (AKF) and convolutional neural networks (CNN) is proposed in this paper.

Wind power ramp prediction algorithm based on wavelet deep belief network

no code implementations11 Feb 2022 Zhenhao Tang, Qingyu Meng, Shengxian Cao, Yang Li, Zhongha Mu, Xiaoya Pang

To improve the ramp prediction accuracy, a hybrid wavelet deep belief network algorithm with adaptive feature selection (WDBNAFS) is proposed.

Algorithm feature selection +1

Robust Dynamic State Estimator of Integrated Energy Systems based on Natural Gas Partial Differential Equations

no code implementations4 Feb 2022 Liang Chen, Yang Li, Manyun Huang, Xinxin Hui, Songlin Gu

A novel robust dynamic state estimation methodology for integrated natural gas and electric power systems is proposed based on Kalman filter.

Improved normal-boundary intersection algorithm: a method for energy optimization strategy in smart buildings

no code implementations25 Jan 2022 Jia Cui, Jiang Pan, Shunjiang Wang, Martin Onyeka Okoye, Junyou Yang, Yang Li, Hao Wang

With the widespread use of distributed energy sources, the advantages of smart buildings over traditional buildings are becoming increasingly obvious.


Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale

no code implementations18 Jan 2022 Yang Li, Yu Shen, Huaijun Jiang, Wentao Zhang, Jixiang Li, Ji Liu, Ce Zhang, Bin Cui

The ever-growing demand and complexity of machine learning are putting pressure on hyper-parameter tuning systems: while the evaluation cost of models continues to increase, the scalability of state-of-the-arts starts to become a crucial bottleneck.


Joint Planning of Distributed Generations and Energy Storage in Active Distribution Networks: A Bi-Level Programming Approach

no code implementations15 Jan 2022 Yang Li, Bo Feng, Bin Wang, Shuchao Sun

In this model, the upper-level aims to seek the optimal location and capacity of DGs and energy storage, while the lower-level optimizes the operation of energy storage devices.

Learning to Denoise Raw Mobile UI Layouts for Improving Datasets at Scale

no code implementations11 Jan 2022 Gang Li, Gilles Baechler, Manuel Tragut, Yang Li

The layout of a mobile screen is a critical data source for UI design research and semantic understanding of the screen.


Swin Transformer for Fast MRI

2 code implementations10 Jan 2022 Jiahao Huang, Yingying Fang, Yinzhe Wu, Huanjun Wu, Zhifan Gao, Yang Li, Javier Del Ser, Jun Xia, Guang Yang

The IM and OM were 2D convolutional layers and the FEM was composed of a cascaded of residual Swin transformer blocks (RSTBs) and 2D convolutional layers.

MRI Reconstruction

N-Omniglot, a large-scale neuromorphic dataset for spatio-temporal sparse few-shot learning

1 code implementation25 Dec 2021 Yang Li, Yiting Dong, Dongcheng Zhao, Yi Zeng

Few-shot learning (learning with a few samples) is one of the most important cognitive abilities of the human brain.

Few-Shot Learning

A review of data-driven short-term voltage stability assessment of power systems: Concept, principle, and challenges

no code implementations22 Dec 2021 Jiting Cao, Meng Zhang, Yang Li

With the rapid growth of power market reform and power demand, the power transmission capacity of a power grid is approaching its limit, and the secure and stable operation of power systems becomes increasingly important.

Learning to Model the Relationship Between Brain Structural and Functional Connectomes

1 code implementation18 Dec 2021 Yang Li, Gonzalo Mateos, Zhengwu Zhang

Recent advances in neuroimaging along with algorithmic innovations in statistical learning from network data offer a unique pathway to integrate brain structure and function, and thus facilitate revealing some of the brain's organizing principles at the system level.

Graph Representation Learning

Homography Decomposition Networks for Planar Object Tracking

2 code implementations15 Dec 2021 Xinrui Zhan, Yueran Liu, Jianke Zhu, Yang Li

Planar object tracking plays an important role in AI applications, such as robotics, visual servoing, and visual SLAM.

Object Tracking

Hierarchical Stochastic Scheduling of Multi-Community Integrated Energy Systems in Uncertain Environments via Stackelberg Game

no code implementations14 Dec 2021 Yang Li, Bin Wang, Zhen Yang, Jiazheng Li, Chen Chen

An operating entity utilizing community-integrated energy systems with a large number of small-scale distributed energy sources can easily trade with existing distribution markets.

energy management Management +1

Progressive Graph Convolution Network for EEG Emotion Recognition

no code implementations14 Dec 2021 Yijin Zhou, Fu Li, Yang Li, Youshuo Ji, Guangming Shi, Wenming Zheng, Lijian Zhang, Yuanfang Chen, Rui Cheng

Moreover, motivated by the observation of the relationship between coarse- and fine-grained emotions, we adopt a dual-head module that enables the PGCN to progressively learn more discriminative EEG features, from coarse-grained (easy) to fine-grained categories (difficult), referring to the hierarchical characteristic of emotion.

EEG Emotion Recognition Electroencephalogram (EEG)

Dynamic Exploitation Gaussian Bare-Bones Bat Algorithm for Optimal Reactive Power Dispatch to Improve the Safety and Stability of Power System

no code implementations13 Dec 2021 Zhaoyang Qu, Yunchang Dong, Sylvère Mugemanyi, Tong Yu, Xiaoyong Bo, Huashun Li, Yang Li, François Xavier Rugema, Christophe Bananeza

DeGBBBA is an advanced variant of GBBBA in which a modified Gaussian distribution is introduced so as to allow the dynamic adaptation of exploitation and exploitation in the proposed algorithm.

Continuous Control

Automated assessment of disease severity of COVID-19 using artificial intelligence with synthetic chest CT

no code implementations11 Dec 2021 Mengqiu Liu, Ying Liu, Yidong Yang, Aiping Liu, Shana Li, Changbing Qu, Xiaohui Qiu, Yang Li, Weifu Lv, Peng Zhang, Jie Wen

Correlations between imaging findings and clinical lab tests suggested the value of this system as a potential tool to assess disease severity of COVID-19.

Data Augmentation Lesion Segmentation

VUT: Versatile UI Transformer for Multi-Modal Multi-Task User Interface Modeling

no code implementations10 Dec 2021 Yang Li, Gang Li, Xin Zhou, Mostafa Dehghani, Alexey Gritsenko

Our model consists of a multimodal Transformer encoder that jointly encodes UI images and structures, and performs UI object detection when the UI structures are absent in the input.

object-detection Object Detection +2

A Deep-Learning Intelligent System Incorporating Data Augmentation for Short-Term Voltage Stability Assessment of Power Systems

no code implementations5 Dec 2021 Yang Li, Meng Zhang, Chen Chen

Facing the difficulty of expensive and trivial data collection and annotation, how to make a deep learning-based short-term voltage stability assessment (STVSA) model work well on a small training dataset is a challenging and urgent problem.

Data Augmentation

Structure-Aware Multi-Hop Graph Convolution for Graph Neural Networks

no code implementations3 Dec 2021 Yang Li, Yuichi Tanaka

In this paper, we propose two methods to improve the performance of GCs: 1) Utilizing structural information in the feature space, and 2) exploiting the multi-hop information in one GC step.

Iterative Connecting Probability Estimation for Networks

no code implementations NeurIPS 2021 Yichen Qin, Linhan Yu, Yang Li

Starting at a random initial point or an existing estimate, our method iteratively updates the pairwise vertex distances, the sets of similar vertices, and connecting probabilities to improve the precision of the estimate.

Learning to Adapt via Latent Domains for Adaptive Semantic Segmentation

no code implementations NeurIPS 2021 Yunan Liu, Shanshan Zhang, Yang Li, Jian Yang

In this setting, we embed an additional pair of “latent-latent” to reduce the domain gap between the source and different latent domains, allowing the model to adapt well on multiple target domains simultaneously.

Domain Adaptation Meta-Learning +1

Stochastic optimal scheduling of demand response-enabled microgrids with renewable generations: An analytical-heuristic approach

no code implementations24 Nov 2021 Yang Li, Kang Li, Zhen Yang, Yang Yu, Runnan Xu, Miaosen Yang

In order to solve this model, this research combines Jaya algorithm and interior point method (IPM) to develop a hybrid analysis-heuristic solution method called Jaya-IPM, where the lower- and upper- levels are respectively addressed by the IPM and the Jaya, and the scheduling scheme is obtained via iterations between the two levels.


Meta-Auto-Decoder for Solving Parametric Partial Differential Equations

no code implementations15 Nov 2021 Xiang Huang, Zhanhong Ye, Hongsheng Liu, Beiji Shi, Zidong Wang, Kang Yang, Yang Li, Bingya Weng, Min Wang, Haotian Chu, Fan Yu, Bei Hua, Lei Chen, Bin Dong

Many important problems in science and engineering require solving the so-called parametric partial differential equations (PDEs), i. e., PDEs with different physical parameters, boundary conditions, shapes of computation domains, etc.


Spiking CapsNet: A Spiking Neural Network With A Biologically Plausible Routing Rule Between Capsules

no code implementations15 Nov 2021 Dongcheng Zhao, Yang Li, Yi Zeng, Jihang Wang, Qian Zhang

Our Spiking CapsNet fully combines the strengthens of SNN and CapsNet, and shows strong robustness to noise and affine transformation.

DSBERT:Unsupervised Dialogue Structure learning with BERT

no code implementations9 Nov 2021 Bingkun Chen, Shaobing Dai, Shenghua Zheng, Lei Liao, Yang Li

Unsupervised dialogue structure learning is an important and meaningful task in natural language processing.

Dialogue Generation

Solving Partial Differential Equations with Point Source Based on Physics-Informed Neural Networks

no code implementations2 Nov 2021 Xiang Huang, Hongsheng Liu, Beiji Shi, Zidong Wang, Kang Yang, Yang Li, Bingya Weng, Min Wang, Haotian Chu, Jing Zhou, Fan Yu, Bei Hua, Lei Chen, Bin Dong

In recent years, deep learning technology has been used to solve partial differential equations (PDEs), among which the physics-informed neural networks (PINNs) emerges to be a promising method for solving both forward and inverse PDE problems.

A critical review of data-driven transient stability assessment of power systems: principles, prospects and challenges

no code implementations1 Nov 2021 Shitu Zhang, Zhixun Zhu, Yang Li

Transient stability assessment (TSA) has always been a fundamental means for ensuring the secure and stable operation of power systems.

Automated Hyperparameter Optimization Challenge at CIKM 2021 AnalyticCup

1 code implementation31 Oct 2021 Huaijun Jiang, Yu Shen, Yang Li

In this paper, we describe our method for tackling the automated hyperparameter optimization challenge in QQ Browser 2021 AI Algorithm Competiton (ACM CIKM 2021 AnalyticCup Track 2).

Bayesian Optimization Hyperparameter Optimization

Data Driven based Dynamic Correction Prediction Model for NOx Emission of Coal Fired Boiler

no code implementations29 Oct 2021 Zhenhao Tang, Deyu Zhu, Yang Li

The real-time prediction of NOx emissions is of great significance for pollutant emission control and unit operation of coal-fired power plants.

feature selection

Path-Enhanced Multi-Relational Question Answering with Knowledge Graph Embeddings

no code implementations29 Oct 2021 Guanglin Niu, Yang Li, Chengguang Tang, Zhongkai Hu, Shibin Yang, Peng Li, Chengyu Wang, Hao Wang, Jian Sun

The multi-relational Knowledge Base Question Answering (KBQA) system performs multi-hop reasoning over the knowledge graph (KG) to achieve the answer.

Knowledge Base Question Answering Knowledge Graph Embedding +1

Deep DIC: Deep Learning-Based Digital Image Correlation for End-to-End Displacement and Strain Measurement

no code implementations26 Oct 2021 Ru Yang, Yang Li, Danielle Zeng, Ping Guo

StrainNet predicts the strain field directly from the image input without relying on the displacement prediction, which significantly improves the strain prediction accuracy.

Creating User Interface Mock-ups from High-Level Text Descriptions with Deep-Learning Models

no code implementations14 Oct 2021 Forrest Huang, Gang Li, Xin Zhou, John F. Canny, Yang Li

The design process of user interfaces (UIs) often begins with articulating high-level design goals.


Transferability Estimation for Semantic Segmentation Task

no code implementations30 Sep 2021 Yang Tan, Yang Li, Shao-Lun Huang

Recent analytical transferability metrics are mainly designed for image classification problem, and currently there is no specific investigation for the transferability estimation of semantic segmentation task, which is an essential problem in autonomous driving, medical image analysis, etc.

Autonomous Driving Image Classification +2

Bitcoin Transaction Strategy Construction Based on Deep Reinforcement Learning

no code implementations30 Sep 2021 Fengrui Liu, Yang Li, Baitong Li, Jiaxin Li, Huiyang Xie

Then an automatically-generating transaction strategy is constructed building on PPO with LSTM as the basis to construct the policy.

reinforcement-learning Reinforcement Learning (RL)

Extracting stochastic dynamical systems with $α$-stable Lévy noise from data

no code implementations30 Sep 2021 Yang Li, Yubin Lu, Shengyuan Xu, Jinqiao Duan

Despite the wide applications of non-Gaussian fluctuations in numerous physical phenomena, the data-driven approaches to extract stochastic dynamical systems with (non-Gaussian) L\'evy noise are relatively few so far.

VUT: Versatile UI Transformer for Multimodal Multi-Task User Interface Modeling

no code implementations29 Sep 2021 Yang Li, Gang Li, Xin Zhou, Mostafa Dehghani, Alexey A. Gritsenko

Our model consists of a multimodal Transformer encoder that jointly encodes UI images and structures, and performs UI object detection when the UI structures are absent in the input.

object-detection Object Detection +2

Improving Generative Adversarial Networks via Adversarial Learning in Latent Space

no code implementations29 Sep 2021 Yang Li, Yichuan Mo, Liangliang Shi, Junchi Yan, Xiaolu Zhang, Jun Zhou

Although many efforts have been made in terms of backbone architecture design, loss function, and training techniques, few results have been obtained on how the sampling in latent space can affect the final performance, and existing works on latent space mainly focus on controllability.

Hierarchical Relation-Guided Type-Sentence Alignment for Long-Tail Relation Extraction with Distant Supervision

no code implementations Findings (NAACL) 2022 Yang Li, Guodong Long, Tao Shen, Jing Jiang

It consists of (1) a pairwise type-enriched sentence encoding module injecting both context-free and -related backgrounds to alleviate sentence-level wrong labeling, and (2) a hierarchical type-sentence alignment module enriching a sentence with the triple fact's basic attributes to support long-tail relations.

Knowledge Graphs Relation Extraction +1

Class-conditioned Domain Generalization via Wasserstein Distributional Robust Optimization

no code implementations8 Sep 2021 Jingge Wang, Yang Li, Liyan Xie, Yao Xie

Given multiple source domains, domain generalization aims at learning a universal model that performs well on any unseen but related target domain.

Domain Generalization

Non-intrusive load decomposition based on CNN-LSTM hybrid deep learning model

no code implementations2 Sep 2021 Xinxin Zhou, Jingru Feng, Yang Li

In this paper, the proposed decomposition method is compared with the existing traditional deep learning load decomposition method.

Extracting Stochastic Governing Laws by Nonlocal Kramers-Moyal Formulas

1 code implementation28 Aug 2021 Yubin Lu, Yang Li, Jinqiao Duan

In this work, we propose a data-driven approach to extract stochastic governing laws with both (Gaussian) Brownian motion and (non-Gaussian) L\'evy motion, from short bursts of simulation data.

Lightweight Self-Attentive Sequential Recommendation

no code implementations25 Aug 2021 Yang Li, Tong Chen, Peng-Fei Zhang, Hongzhi Yin

Modern deep neural networks (DNNs) have greatly facilitated the development of sequential recommender systems by achieving state-of-the-art recommendation performance on various sequential recommendation tasks.

Sequential Recommendation

Optimal Scheduling of Integrated Demand Response-Enabled Community Integrated Energy Systems in Uncertain Environments

no code implementations18 Aug 2021 Yang Li, Bin Wang, Zhen Yang, Jiazheng Li, Guoqing Li

The community integrated energy system (CIES) is an essential energy internet carrier that has recently been the focus of much attention.


A BCS-GDE Algorithm for Multi-objective Optimization of Combined Cooling, Heating and Power Model

no code implementations17 Aug 2021 Jiaze Sun, Jiahui Deng, Yang Li, Shuaiyin Ma, Nan Han

District energy systems can not only reduce energy consumption but also set energy supply dispatching schemes according to demand.

Decision Making

Optimal Scheduling of Isolated Microgrids Using Automated Reinforcement Learning-based Multi-period Forecasting

no code implementations15 Aug 2021 Yang Li, Ruinong Wang, Zhen Yang

In order to reduce the negative impact of the uncertainty of load and renewable energies outputs on microgrid operation, an optimal scheduling model is proposed for isolated microgrids by using automated reinforcement learning-based multi-period forecasting of renewable power generations and loads.

reinforcement-learning Reinforcement Learning (RL) +1

Large-Scale Modeling of Mobile User Click Behaviors Using Deep Learning

no code implementations11 Aug 2021 Xin Zhou, Yang Li

Modeling tap or click sequences of users on a mobile device can improve our understandings of interaction behavior and offers opportunities for UI optimization by recommending next element the user might want to click on.

HelpViz: Automatic Generation of Contextual Visual MobileTutorials from Text-Based Instructions

no code implementations7 Aug 2021 Mingyuan Zhong, Gang Li, Peggy Chi, Yang Li

We present HelpViz, a tool for generating contextual visual mobile tutorials from text-based instructions that are abundant on the web.

Screen2Words: Automatic Mobile UI Summarization with Multimodal Learning

1 code implementation7 Aug 2021 Bryan Wang, Gang Li, Xin Zhou, Zhourong Chen, Tovi Grossman, Yang Li

Mobile User Interface Summarization generates succinct language descriptions of mobile screens for conveying important contents and functionalities of the screen, which can be useful for many language-based application scenarios.

Dynamic Prediction Model for NOx Emission of SCR System Based on Hybrid Data-driven Algorithms

no code implementations3 Aug 2021 Zhenhao Tang, Shikui Wang, Shengxian Cao, Yang Li, Tao Shen

Aiming at the problem that delay time is difficult to determine and prediction accuracy is low in building prediction model of SCR system, a dynamic modeling scheme based on a hybrid of multiple data-driven algorithms was proposed.

feature selection FLUE +1

Frequency support Scheme based on parametrized power curve for de-loaded Wind Turbine under various wind speed

no code implementations2 Aug 2021 Cheng Zhong, Yueming Lv, Huayi Li, Jikai Chen, Yang Li

However, for the existing frequency regulation scheme of wind turbines, the control gains in the auxiliary frequency controller are difficult to set because of the compromise of the frequency regulation performance and the stable operation of wind turbines, especially when the wind speed remains variable.

Grain: Improving Data Efficiency of Graph Neural Networks via Diversified Influence Maximization

1 code implementation31 Jul 2021 Wentao Zhang, Zhi Yang, Yexin Wang, Yu Shen, Yang Li, Liang Wang, Bin Cui

Data selection methods, such as active learning and core-set selection, are useful tools for improving the data efficiency of deep learning models on large-scale datasets.

Active Learning Knowledge Graphs

ROD: Reception-aware Online Distillation for Sparse Graphs

1 code implementation25 Jul 2021 Wentao Zhang, Yuezihan Jiang, Yang Li, Zeang Sheng, Yu Shen, Xupeng Miao, Liang Wang, Zhi Yang, Bin Cui

Unfortunately, many real-world networks are sparse in terms of both edges and labels, leading to sub-optimal performance of GNNs.

Clustering Graph Learning +5

Extracting Governing Laws from Sample Path Data of Non-Gaussian Stochastic Dynamical Systems

no code implementations21 Jul 2021 Yang Li, Jinqiao Duan

Advances in data science are leading to new progresses in the analysis and understanding of complex dynamics for systems with experimental and observational data.

VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition

3 code implementations19 Jul 2021 Yang Li, Yu Shen, Wentao Zhang, Jiawei Jiang, Bolin Ding, Yaliang Li, Jingren Zhou, Zhi Yang, Wentao Wu, Ce Zhang, Bin Cui

End-to-end AutoML has attracted intensive interests from both academia and industry, which automatically searches for ML pipelines in a space induced by feature engineering, algorithm/model selection, and hyper-parameter tuning.

AutoML Feature Engineering +1

Coordinating Flexible Demand Response and Renewable Uncertainties for Scheduling of Community Integrated Energy Systems with an Electric Vehicle Charging Station: A Bi-level Approach

no code implementations16 Jul 2021 Yang Li, Meng Han, Zhen Yang, Guoqing Li

A community integrated energy system (CIES) with an electric vehicle charging station (EVCS) provides a new way for tackling growing concerns of energy efficiency and environmental pollution, it is a critical task to coordinate flexible demand response and multiple renewable uncertainties.