Search Results for author: Jiannong Cao

Found 41 papers, 12 papers with code

Enhancing Motion in Text-to-Video Generation with Decomposed Encoding and Conditioning

1 code implementation31 Oct 2024 Penghui Ruan, Pichao Wang, Divya Saxena, Jiannong Cao, Yuhui Shi

This issue stems from the internal biases in text encoding, which overlooks motions, and inadequate conditioning mechanisms in T2V generation models.

Motion Synthesis Text-to-Video Generation +1

Unveiling Molecular Secrets: An LLM-Augmented Linear Model for Explainable and Calibratable Molecular Property Prediction

1 code implementation11 Oct 2024 Zhuoran Li, Xu sun, WanYu Lin, Jiannong Cao

The core of MoleX is to model complicated molecular structure-property relationships using a simple linear model, augmented by LLM knowledge and a crafted calibration strategy.

Dimensionality Reduction Drug Discovery +2

Overcoming Growth-Induced Forgetting in Task-Agnostic Continual Learning

no code implementations20 Aug 2024 Yuqing Zhao, Divya Saxena, Jiannong Cao, Xiaoyun Liu, Changlin Song

In continual learning (CL), model growth enhances adaptability over new data, improving knowledge retention for more tasks.

Continual Learning

The Diversity Bonus: Learning from Dissimilar Distributed Clients in Personalized Federated Learning

no code implementations22 Jul 2024 Xinghao Wu, Xuefeng Liu, Jianwei Niu, Guogang Zhu, Shaojie Tang, Xiaotian Li, Jiannong Cao

We note that when dealing with clients with similar data distributions, methods such as personalized weight aggregation tend to enforce their models to be close in the parameter space.

Diversity Personalized Federated Learning

Large Language Models for Cuffless Blood Pressure Measurement From Wearable Biosignals

no code implementations26 Jun 2024 Zengding Liu, Chen Chen, Jiannong Cao, Minglei Pan, Jikui Liu, Nan Li, Fen Miao, Ye Li

This paper pioneers the exploration of LLMs for cuffless BP measurement, providing a potential solution to enhance the accuracy of cuffless BP measurement.

Self-assessment, Exhibition, and Recognition: a Review of Personality in Large Language Models

no code implementations25 Jun 2024 Zhiyuan Wen, Yu Yang, Jiannong Cao, Haoming Sun, Ruosong Yang, Shuaiqi Liu

By presenting a clear taxonomy, in-depth analysis, promising future directions, and extensive resource collections, we aim to provide a better understanding and facilitate further advancements in this emerging field.

Toward Structure Fairness in Dynamic Graph Embedding: A Trend-aware Dual Debiasing Approach

1 code implementation19 Jun 2024 Yicong Li, Yu Yang, Jiannong Cao, Shuaiqi Liu, Haoran Tang, Guandong Xu

We first identify biased structural evolutions in a dynamic graph based on the evolving trend of vertex degree and then propose FairDGE, the first structurally Fair Dynamic Graph Embedding algorithm.

Dynamic graph embedding Fairness +1

SHARON: Secure and Efficient Cross-shard Transaction Processing via Shard Rotation

no code implementations INFOCOM 2024 Shan Jiang, Jiannong Cao, Cheung Leong Tung, Yuqin Wang, Shan Wang

Recently, sharding has become a popular direction to scale out blockchain systems by dividing the network into shards that process transactions in parallel.

Scheduling

FedFa: A Fully Asynchronous Training Paradigm for Federated Learning

no code implementations17 Apr 2024 Haotian Xu, Zhaorui Zhang, Sheng Di, Benben Liu, Khalid Ayed Alharthi, Jiannong Cao

We propose a full asynchronous training paradigm, called FedFa, which can guarantee model convergence and eliminate the waiting time completely for federated learning by using a few buffered results on the server for parameter updating.

Federated Learning

FedDistill: Global Model Distillation for Local Model De-Biasing in Non-IID Federated Learning

no code implementations14 Apr 2024 Changlin Song, Divya Saxena, Jiannong Cao, Yuqing Zhao

This paper introduces FedDistill, a framework enhancing the knowledge transfer from the global model to local models, focusing on the issue of imbalanced class distribution.

Federated Learning Transfer Learning

Affective-NLI: Towards Accurate and Interpretable Personality Recognition in Conversation

1 code implementation3 Apr 2024 Zhiyuan Wen, Jiannong Cao, Yu Yang, Ruosong Yang, Shuaiqi Liu

To utilize affectivity within dialog content for accurate personality recognition, we fine-tuned a pre-trained language model specifically for emotion recognition in conversations, facilitating real-time affective annotations for utterances.

Emotion Recognition Language Modelling +2

Personality-affected Emotion Generation in Dialog Systems

no code implementations3 Apr 2024 Zhiyuan Wen, Jiannong Cao, Jiaxing Shen, Ruosong Yang, Shuaiqi Liu, Maosong Sun

Therefore, we propose a new task, Personality-affected Emotion Generation, to generate emotion based on the personality given to the dialog system and further investigate a solution through the personality-affected mood transition.

Digital Twin-assisted Reinforcement Learning for Resource-aware Microservice Offloading in Edge Computing

no code implementations13 Mar 2024 Xiangchun Chen, Jiannong Cao, Zhixuan Liang, Yuvraj Sahni, Mingjin Zhang

To address this challenge, we formulate an online joint microservice offloading and bandwidth allocation problem, JMOBA, to minimize the average completion time of services.

Edge-computing

Low-Resource Court Judgment Summarization for Common Law Systems

1 code implementation7 Mar 2024 Shuaiqi Liu, Jiannong Cao, Yicong Li, Ruosong Yang, Zhiyuan Wen

Current summarization datasets are insufficient to satisfy the demands of summarizing precedents across multiple jurisdictions, especially when labeled data are scarce for many jurisdictions.

Data Augmentation

Heterogeneity-aware Cross-school Electives Recommendation: a Hybrid Federated Approach

no code implementations19 Feb 2024 Chengyi Ju, Jiannong Cao, Yu Yang, Zhen-Qun Yang, Ho Man Lee

In response, we propose HFRec, a heterogeneity-aware hybrid federated recommender system designed for cross-school elective course recommendations.

Diversity Recommendation Systems

Bayes-enhanced Multi-view Attention Networks for Robust POI Recommendation

no code implementations1 Nov 2023 Jiangnan Xia, Yu Yang, Senzhang Wang, Hongzhi Yin, Jiannong Cao, Philip S. Yu

To this end, we investigate a novel problem of robust POI recommendation by considering the uncertainty factors of the user check-ins, and proposes a Bayes-enhanced Multi-view Attention Network.

Data Augmentation Representation Learning

SGOOD: Substructure-enhanced Graph-Level Out-of-Distribution Detection

1 code implementation16 Oct 2023 Zhihao Ding, Jieming Shi, Shiqi Shen, Xuequn Shang, Jiannong Cao, Zhipeng Wang, Zhi Gong

We find that substructure differences commonly exist between ID and OOD graphs, and design SGOOD with a series of techniques to encode task-agnostic substructures for effective OOD detection.

Out-of-Distribution Detection Representation Learning

Effective Illicit Account Detection on Large Cryptocurrency MultiGraphs

1 code implementation4 Sep 2023 Zhihao Ding, Jieming Shi, Qing Li, Jiannong Cao

For example, on a Bitcoin dataset with 20 million nodes and 203 million edges, DIAM attains an F1 score of 96. 55%, markedly surpassing the runner-up's score of 83. 92%.

Feature Engineering Graph Neural Network

Spatial-Temporal Data Mining for Ocean Science: Data, Methodologies, and Opportunities

no code implementations20 Jul 2023 Hanchen Yang, Wengen Li, Shuyu Wang, Hui Li, Jihong Guan, Shuigeng Zhou, Jiannong Cao

Compared with typical ST data (e. g., traffic data), ST ocean data is more complicated but with unique characteristics, e. g., diverse regionality and high sparsity.

Anomaly Detection Event Detection +1

Long Text and Multi-Table Summarization: Dataset and Method

1 code implementation8 Feb 2023 Shuaiqi Liu, Jiannong Cao, Ruosong Yang, Zhiyuan Wen

Within a report document, the salient information can be scattered in the textual and non-textual content.

Document Summarization Informativeness +1

Re-GAN: Data-Efficient GANs Training via Architectural Reconfiguration

1 code implementation CVPR 2023 Divya Saxena, Jiannong Cao, Jiahao Xu, Tarun Kulshrestha

Re-GAN stabilizes the GANs models with less data and offers an alternative to the existing GANs tickets and progressive growing methods.

Image Generation

AdaptCL: Adaptive Continual Learning for Tackling Heterogeneity in Sequential Datasets

1 code implementation22 Jul 2022 Yuqing Zhao, Divya Saxena, Jiannong Cao

Managing heterogeneous datasets that vary in complexity, size, and similarity in continual learning presents a significant challenge.

Continual Learning Transfer Learning

Time-aware Dynamic Graph Embedding for Asynchronous Structural Evolution

no code implementations1 Jul 2022 Yu Yang, Hongzhi Yin, Jiannong Cao, Tong Chen, Quoc Viet Hung Nguyen, Xiaofang Zhou, Lei Chen

Meanwhile, we treat each edge sequence as a whole and embed its ToV of the first vertex to further encode the time-sensitive information.

Dynamic graph embedding Graph Mining

Hierarchical Reinforcement Learning with Opponent Modeling for Distributed Multi-agent Cooperation

no code implementations25 Jun 2022 Zhixuan Liang, Jiannong Cao, Shan Jiang, Divya Saxena, Huafeng Xu

To tackle the issues, we propose a hierarchical reinforcement learning approach with high-level decision-making and low-level individual control for efficient policy search.

Autonomous Vehicles Decision Making +4

From Multi-agent to Multi-robot: A Scalable Training and Evaluation Platform for Multi-robot Reinforcement Learning

no code implementations20 Jun 2022 Zhiuxan Liang, Jiannong Cao, Shan Jiang, Divya Saxena, Jinlin Chen, Huafeng Xu

Precisely, SMART consists of two components: 1) a simulation environment that provides a variety of complex interaction scenarios for training and 2) a real-world multi-robot system for realistic performance evaluation.

Multi-agent Reinforcement Learning reinforcement-learning +2

Time Series Clustering for Human Behavior Pattern Mining

no code implementations14 Oct 2021 Rohan Kabra, Divya Saxena, Dhaval Patel, Jiannong Cao

Human behavior modeling deals with learning and understanding behavior patterns inherent in humans' daily routines.

Clustering Human Dynamics +2

E-Tree Learning: A Novel Decentralized Model Learning Framework for Edge AI

no code implementations4 Aug 2020 Lei Yang, Yanyan Lu, Jiannong Cao, Jiaming Huang, Mingjin Zhang

In this paper, we propose a novel decentralized model learning approach, namely E-Tree, which makes use of a well-designed tree structure imposed on the edge devices.

Clustering Federated Learning

EPARS: Early Prediction of At-risk Students with Online and Offline Learning Behaviors

no code implementations6 Jun 2020 Yu Yang, Zhiyuan Wen, Jiannong Cao, Jiaxing Shen, Hongzhi Yin, Xiaofang Zhou

We propose a novel algorithm (EPARS) that could early predict STAR in a semester by modeling online and offline learning behaviors.

Management Network Embedding

Decode with Template: Content Preserving Sentiment Transfer

no code implementations LREC 2020 Zhiyuan Wen, Jiannong Cao, Ruosong Yang, Senzhang Wang

The two major challenges in existing works lie in (1) effectively disentangling the original sentiment from input sentences; and (2) preserving the semantic content while transferring the sentiment.

GGP: Glossary Guided Post-processing for Word Embedding Learning

no code implementations LREC 2020 Ruosong Yang, Jiannong Cao, Zhiyuan Wen

To enhance corpus based word embedding models, researchers utilize domain knowledge to learn more distinguishable representations via joint optimization and post-processing based models.

Generative Adversarial Networks (GANs Survey): Challenges, Solutions, and Future Directions

no code implementations30 Apr 2020 Divya Saxena, Jiannong Cao

In this study, we perform a comprehensive survey of the advancements in GANs design and optimization solutions proposed to handle GANs challenges.

Survey

Boros: Secure Cross-Channel Transfers via Channel Hub

no code implementations29 Nov 2019 YongJie Ye, Jingjing Zhang, Weigang Wu, Xiapu Luo, Jiannong Cao

In this paper, we design and develop a novel off-chain system to shorten the routing path for the payment network.

Cryptography and Security

D-GAN: Deep Generative Adversarial Nets for Spatio-Temporal Prediction

no code implementations19 Jul 2019 Divya Saxena, Jiannong Cao

However, it is still very challenging (1) to adequately learn the complex and non-linear ST relationships; (2) to model the high variations in the ST data volumes as it is inherently dynamic, changing over time (i. e., irregular) and highly influenced by many external factors, such as adverse weather, accidents, traffic control, PoI, etc.

Generative Adversarial Network Variational Inference

Deep Learning for Spatio-Temporal Data Mining: A Survey

no code implementations11 Jun 2019 Senzhang Wang, Jiannong Cao, Philip S. Yu

Next we classify existing literatures based on the types of ST data, the data mining tasks, and the deep learning models, followed by the applications of deep learning for STDM in different domains including transportation, climate science, human mobility, location based social network, crime analysis, and neuroscience.

Anomaly Detection Deep Learning +3

Joint Topic-Semantic-aware Social Recommendation for Online Voting

1 code implementation3 Dec 2017 Hongwei Wang, Jia Wang, Miao Zhao, Jiannong Cao, Minyi Guo

JTS-MF model calculates similarity among users and votings by combining their TEWE representation and structural information of social networks, and preserves this topic-semantic-social similarity during matrix factorization.

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