93 citations · 308 across the 25 of their papers we have counts for
25 papers
UniSA: Unified Generative Framework for Sentiment Analysis
Zaijing Li, Ting-En Lin, Yuchuan Wu +4
Sentiment analysis is a crucial task that aims to understand people's emotional states and predict emotional categories based on multimodal information. It consists of several subt…
Improve in-situ life prediction and classification performance by capturing both the present state and evolution rate of battery aging
Mingyuan Zhao, Yongzhi Zhang
This study develops a methodology by capturing both the battery aging state and degradation rate for improved life prediction performance. The aging state is indicated by six physi…
When Edge Meets FaaS: Opportunities and Challenges
Runyu Jin, Qirui Yang, Ming Zhao
The proliferation of edge devices and the rapid growth of IoT data have called forth the edge computing paradigm. Function-as-a-service (FaaS) is a promising computing paradigm to…
AdaCache: A Disaggregated Cache System with Adaptive Block Size for Cloud Block Storage
Qirui Yang, Runyu Jin, Ni Fan +3
NVMe SSD caching has demonstrated impressive capabilities in solving cloud block storage's I/O bottleneck and enhancing application performance in public, private, and hybrid cloud…
Attention Disturbance and Dual-Path Constraint Network for Occluded Person Re-identification
Jiaer Xia, Lei Tan, Pingyang Dai +3
Occluded person re-identification (Re-ID) aims to address the potential occlusion problem when matching occluded or holistic pedestrians from different camera views. Many methods u…
Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Neural Networks
Sitao Luan, Mingde Zhao, Chenqing Hua +2
The core operation of current Graph Neural Networks (GNNs) is the aggregation enabled by the graph Laplacian or message passing, which filters the neighborhood information of nodes…
Differentiated Federated Reinforcement Learning Based Traffic Offloading on Space-Air-Ground Integrated Networks
Yeguang Qin, Yilin Yang, Fengxiao Tang +3
The Space-Air-Ground Integrated Network (SAGIN) plays a pivotal role as a comprehensive foundational network communication infrastructure, presenting opportunities for highly effic…
Exploring the non-stationarity of coastal sea level probability distributions
Fabrizio Falasca, Andrew Brettin, Laure Zanna +3
Studies agree on a significant global mean sea level rise in the 20th century and its recent 21st century acceleration in the satellite record. At regional scale, the evolution of…
Revisiting Heterophily For Graph Neural Networks
Sitao Luan, Chenqing Hua, Qincheng Lu +5
Graph Neural Networks (GNNs) extend basic Neural Networks (NNs) by using graph structures based on the relational inductive bias (homophily assumption). While GNNs have been common…
Human Instance Segmentation and Tracking via Data Association and Single-stage Detector
Lu Cheng, Mingbo Zhao
Human video instance segmentation plays an important role in computer understanding of human activities and is widely used in video processing, video surveillance, and human modeli…
Temporal Abstractions-Augmented Temporally Contrastive Learning: An Alternative to the Laplacian in RL
Akram Erraqabi, Marlos C. Machado, Mingde Zhao +4
In reinforcement learning, the graph Laplacian has proved to be a valuable tool in the task-agnostic setting, with applications ranging from skill discovery to reward shaping. Rece…
Classifying In-Place Gestures with End-to-End Point Cloud Learning
Lizhi Zhao, Xuequan Lu, Min Zhao +1
Walking in place for moving through virtual environments has attracted noticeable attention recently. Recent attempts focused on training a classifier to recognize certain patterns…
On the Evaluation of Vision-and-Language Navigation Instructions
Ming Zhao, Peter Anderson, Vihan Jain +4
Vision-and-Language Navigation wayfinding agents can be enhanced by exploiting automatically generated navigation instructions. However, existing instruction generators have not be…
A Hierarchical Multi-Modal Encoder for Moment Localization in Video Corpus
Bowen Zhang, Hexiang Hu, Joonseok Lee +5
Identifying a short segment in a long video that semantically matches a text query is a challenging task that has important application potentials in language-based video search, b…
EdgeBench: A Workflow-based Benchmark for Edge Computing
Qirui Yang, Runyu Jin, Nabil Gandhi +3
Edge computing has been developed to utilize multiple tiers of resources for privacy, cost and Quality of Service (QoS) reasons. Edge workloads have the characteristics of data-dri…
Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Networks
Sitao Luan, Mingde Zhao, Chenqing Hua +2
The core operation of current Graph Neural Networks (GNNs) is the aggregation enabled by the graph Laplacian or message passing, which filters the neighborhood node information. Th…
Training Matters: Unlocking Potentials of Deeper Graph Convolutional Neural Networks
Sitao Luan, Mingde Zhao, Xiao-Wen Chang +1
The performance limit of Graph Convolutional Networks (GCNs) and the fact that we cannot stack more of them to increase the performance, which we usually do for other deep learning…
META-Learning Eligibility Traces for More Sample Efficient Temporal Difference Learning
Mingde Zhao
Temporal-Difference (TD) learning is a standard and very successful reinforcement learning approach, at the core of both algorithms that learn the value of a given policy, as well…
Semi-Federated Learning
Zhikun Chen, Daofeng Li, Ming Zhao +2
Federated learning (FL) enables massive distributed Information and Communication Technology (ICT) devices to learn a global consensus model without any participants revealing thei…
Exploring Overall Contextual Information for Image Captioning in Human-Like Cognitive Style
Hongwei Ge, Zehang Yan, Kai Zhang +2
Image captioning is a research hotspot where encoder-decoder models combining convolutional neural network (CNN) and long short-term memory (LSTM) achieve promising results. Despit…
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
Sitao Luan, Mingde Zhao, Xiao-Wen Chang +1
Recently, neural network based approaches have achieved significant improvement for solving large, complex, graph-structured problems. However, their bottlenecks still need to be a…
A Reference Vector based Many-Objective Evolutionary Algorithm with Feasibility-aware Adaptation
Mingde Zhao, Hongwei Ge, Kai Zhang +1
The infeasible parts of the objective space in difficult many-objective optimization problems cause trouble for evolutionary algorithms. This paper proposes a reference vector base…
META-Learning State-based Eligibility Traces for More Sample-Efficient Policy Evaluation
Mingde Zhao, Sitao Luan, Ian Porada +2
Temporal-Difference (TD) learning is a standard and very successful reinforcement learning approach, at the core of both algorithms that learn the value of a given policy, as well…
Generalizable Meta-Heuristic based on Temporal Estimation of Rewards for Large Scale Blackbox Optimization
Mingde Zhao, Hongwei Ge, Yi Lian +1
The generalization abilities of heuristic optimizers may deteriorate with the increment of the search space dimensionality. To achieve generalized performance across Large Scale Bl…