Search Results for author: Jiang Zhang

Found 32 papers, 10 papers with code

PCDCNet: A Surrogate Model for Air Quality Forecasting with Physical-Chemical Dynamics and Constraints

2 code implementations26 May 2025 Shuo Wang, Yun Cheng, Qingye Meng, Olga Saukh, Jiang Zhang, Jingfang Fan, YuanTing Zhang, Xingyuan Yuan, Lothar Thiele

Air quality forecasting (AQF) is critical for public health and environmental management, yet remains challenging due to the complex interplay of emissions, meteorology, and chemical transformations.

Deep Learning

Preserving Privacy and Utility in LLM-Based Product Recommendations

no code implementations2 May 2025 Tina Khezresmaeilzadeh, Jiang Zhang, Dimitrios Andreadis, Konstantinos Psounis

To address this, we propose a hybrid privacy-preserving recommendation framework which separates sensitive from nonsensitive data and only shares the latter with the cloud to harness LLM-powered recommendations.

Collaborative Filtering Large Language Model +2

SpinML: Customized Synthetic Data Generation for Private Training of Specialized ML Models

no code implementations5 Mar 2025 Jiang Zhang, Rohan Xavier Sequeira, Konstantinos Psounis

Specialized machine learning (ML) models tailored to users needs and requests are increasingly being deployed on smart devices with cameras, to provide personalized intelligent services taking advantage of camera data.

Synthetic Data Generation

Multi-Omics Fusion with Soft Labeling for Enhanced Prediction of Distant Metastasis in Nasopharyngeal Carcinoma Patients after Radiotherapy

no code implementations12 Feb 2025 Jiabao Sheng, SaiKit Lam, Jiang Zhang, Yuanpeng Zhang, Jing Cai

In order to overcome this challenge and facilitate the integration of their joint application to specific medical objectives, this study aims to develop a fusion methodology that mitigates the disparities inherent in omics data.

Quantifying system-environment synergistic information by effective information decomposition

no code implementations28 Jan 2025 Mingzhe Yang, Linli Pan, Jiang Zhang

Currently, many theories have attempted to explain the most essential difference between living systems and general systems, such as the self-organization theory and the free energy principle, but there is a lack of a reasonable indicator that can measure to what extent a system can be regarded as a system with life characteristics, especially the lack of attention to the dynamic characteristics of life systems.

Predicting Company Growth by Econophysics informed Machine Learning

no code implementations23 Oct 2024 Ruyi Tao, Kaiwei Liu, Xu Jing, Jiang Zhang

Predicting company growth is crucial for strategic adjustment, operational decision-making, risk assessment, and loan eligibility reviews.

Decision Making Time Series +1

Differentially Private Federated Learning without Noise Addition: When is it Possible?

no code implementations6 May 2024 Jiang Zhang, Konstantinos Psounis, Salman Avestimehr

However, we further demonstrate that in practice, these conditions are almost unlikely to hold and hence additional noise added in model updates is still required in order for SA in FL to achieve DP.

Federated Learning Privacy Preserving

Efficient Toxic Content Detection by Bootstrapping and Distilling Large Language Models

no code implementations13 Dec 2023 Jiang Zhang, Qiong Wu, Yiming Xu, Cheng Cao, Zheng Du, Konstantinos Psounis

Furthermore, student LMs fine-tuned with rationales extracted via DToT outperform baselines on all datasets with up to 16. 9\% accuracy improvement, while being more than 60x smaller than conventional LLMs.

In-Context Learning

Neural Network Pruning by Gradient Descent

1 code implementation21 Nov 2023 Zhang Zhang, Ruyi Tao, Jiang Zhang

The rapid increase in the parameters of deep learning models has led to significant costs, challenging computational efficiency and model interpretability.

Computational Efficiency Deep Learning +3

Data driven modeling for self-similar dynamics

1 code implementation12 Oct 2023 Ruyi Tao, Ningning Tao, Yi-Zhuang You, Jiang Zhang

For deterministic dynamics, our framework can discern whether the dynamics are self-similar.

Finding emergence in data by maximizing effective information

no code implementations19 Aug 2023 Mingzhe Yang, Zhipeng Wang, Kaiwei Liu, Yingqi Rong, Bing Yuan, Jiang Zhang

Quantifying emergence and modeling emergent dynamics in a data-driven manner for complex dynamical systems is challenging due to the lack of direct observations at the micro-level.

How Much Privacy Does Federated Learning with Secure Aggregation Guarantee?

no code implementations3 Aug 2022 Ahmed Roushdy Elkordy, Jiang Zhang, Yahya H. Ezzeldin, Konstantinos Psounis, Salman Avestimehr

While SA ensures no additional information is leaked about the individual model update beyond the aggregated model update, there are no formal guarantees on how much privacy FL with SA can actually offer; as information about the individual dataset can still potentially leak through the aggregated model computed at the server.

Federated Learning Privacy Preserving

Completing Networks by Learning Local Connection Patterns

1 code implementation25 Apr 2022 Zhang Zhang, Ruyi Tao, Yongzai Tao, Mingze Qi, Jiang Zhang

And experiments show that our model perform better on a network with higher Reachable CC.

Link Prediction

Neural Information Squeezer for Causal Emergence

1 code implementation25 Jan 2022 Jiang Zhang, Kaiwei Liu

We also show how our framework can extract the dynamics on different levels and identify causal emergence from the data on several exampled systems.

Time Series Time Series Analysis

Privacy-Utility Trades in Crowdsourced Signal Map Obfuscation

no code implementations13 Jan 2022 Jiang Zhang, Lillian Clark, Matthew Clark, Konstantinos Psounis, Peter Kairouz

Cellular providers and data aggregating companies crowdsource celluar signal strength measurements from user devices to generate signal maps, which can be used to improve network performance.

Location Leakage in Federated Signal Maps

no code implementations7 Dec 2021 Evita Bakopoulou, Mengwei Yang, Jiang Zhang, Konstantinos Psounis, Athina Markopoulou

We consider the problem of predicting cellular network performance (signal maps) from measurements collected by several mobile devices.

Federated Learning

HARPO: Learning to Subvert Online Behavioral Advertising

no code implementations9 Nov 2021 Jiang Zhang, Konstantinos Psounis, Muhammad Haroon, Zubair Shafiq

Online behavioral advertising, and the associated tracking paraphernalia, poses a real privacy threat.

Reinforcement Learning (RL)

Tensor networks for unsupervised machine learning

1 code implementation24 Jun 2021 Jing Liu, Sujie Li, Jiang Zhang, Pan Zhang

Despite the great potential, however, existing tensor network models for unsupervised machine learning only work as a proof of principle, as their performance is much worse than the standard models such as restricted Boltzmann machines and neural networks.

BIG-bench Machine Learning Tensor Networks

TabularNet: A Neural Network Architecture for Understanding Semantic Structures of Tabular Data

no code implementations6 Jun 2021 Lun Du, Fei Gao, Xu Chen, Ran Jia, Junshan Wang, Jiang Zhang, Shi Han, Dongmei Zhang

To simultaneously extract spatial and relational information from tables, we propose a novel neural network architecture, TabularNet.

graph construction

Gumbel-softmax-based Optimization: A Simple General Framework for Optimization Problems on Graphs

no code implementations14 Apr 2020 Yaoxin Li, Jing Liu, Guozheng Lin, Yueyuan Hou, Muyun Mou, Jiang Zhang

In computer science, there exist a large number of optimization problems defined on graphs, that is to find a best node state configuration or a network structure such that the designed objective function is optimized under some constraints.

Combinatorial Optimization

PM2.5-GNN: A Domain Knowledge Enhanced Graph Neural Network For PM2.5 Forecasting

2 code implementations ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems 2020 Shuo Wang, Yan-ran Li, Jiang Zhang, Qingye Meng, Lingwei Meng, Fei Gao

When predicting PM2. 5 concentrations, it is necessary to consider complex information sources since the concentrations are influenced by various factors within a long period.

Graph Neural Network

Understanding the mesoscopic scaling patterns within cities

1 code implementation2 Jan 2020 Lei Dong, Zhou Huang, Jiang Zhang, Yu Liu

Understanding quantitative relationships between urban elements is crucial for a wide range of applications.

Physics and Society

Link Prediction via Graph Attention Network

no code implementations10 Oct 2019 Weiwei Gu, Fei Gao, Xiaodan Lou, Jiang Zhang

Link prediction aims to infer missing links or predicting the future ones based on currently observed partial networks, it is a fundamental problem in network science with tremendous real-world applications.

Graph Attention Information Retrieval +4

Gumbel-softmax Optimization: A Simple General Framework for Combinatorial Optimization Problems on Graphs

no code implementations16 Sep 2019 Jing Liu, Fei Gao, Jiang Zhang

Many problems in real life can be converted to combinatorial optimization problems (COPs) on graphs, that is to find a best node state configuration or a network structure such that the designed objective function is optimized under some constraints.

Combinatorial Optimization

A General Deep Learning Framework for Network Reconstruction and Dynamics Learning

1 code implementation30 Dec 2018 Zhang Zhang, Yi Zhao, Jing Liu, Shuo Wang, Ruyi Tao, Ruyue Xin, Jiang Zhang

We exhibit the universality of our framework on different kinds of time-series data: with the same structure, our model can be trained to accurately recover the network structure and predict future states on continuous, discrete, and binary dynamics, and outperforms competing network reconstruction methods.

Time Series Time Series Analysis

A Novel Learning-based Global Path Planning Algorithm for Planetary Rovers

1 code implementation23 Nov 2018 Jiang Zhang, Yuanqing Xia, Ganghui Shen

Autonomous path planning algorithms are significant to planetary exploration rovers, since relying on commands from Earth will heavily reduce their efficiency of executing exploration missions.

A Novel Deep Neural Network Architecture for Mars Visual Navigation

no code implementations25 Aug 2018 Jiang Zhang, Yuanqing Xia, Ganghui Shen

In this paper, emerging deep learning techniques are leveraged to deal with Mars visual navigation problem.

Autonomous Navigation Visual Navigation

Complex Network Classification with Convolutional Neural Network

no code implementations2 Feb 2018 Ruyue Xin, Jiang Zhang, Yitong Shao

Classifying large scale networks into several categories and distinguishing them according to their fine structures is of great importance with several applications in real life.

Classification Clustering +2

Cannot find the paper you are looking for? You can Submit a new open access paper.