36 citations · 174 across the 14 of their papers we have counts for
14 papers
Intent-aware Recommendation via Disentangled Graph Contrastive Learning
Yuling Wang, Xiao Wang, Xiangzhou Huang +5
Graph neural network (GNN) based recommender systems have become one of the mainstream trends due to the powerful learning ability from user behavior data. Understanding the user i…
IOB: Integrating Optimization Transfer and Behavior Transfer for Multi-Policy Reuse
Siyuan Li, Hao Li, Jin Zhang +3
Humans have the ability to reuse previously learned policies to solve new tasks quickly, and reinforcement learning (RL) agents can do the same by transferring knowledge from sourc…
Social network modeling and applications, a tutorial
Lisette Espín-Noboa, Tiago Peixoto, Fariba Karimi
Social networks have been widely studied over the last century from multiple disciplines to understand societal issues such as inequality in employment rates, managerial performanc…
Urania: Visualizing Data Analysis Pipelines for Natural Language-Based Data Exploration
Yi Guo, Nan Cao, Xiaoyu Qi +5
Exploratory Data Analysis (EDA) is an essential yet tedious process for examining a new dataset. To facilitate it, natural language interfaces (NLIs) can help people intuitively ex…
Personalized and privacy-preserving federated heterogeneous medical image analysis with PPPML-HMI
Juexiao Zhou, Longxi Zhou, Di Wang +5
Heterogeneous data is endemic due to the use of diverse models and settings of devices by hospitals in the field of medical imaging. However, there are few open-source frameworks f…
Audit to Forget: A Unified Method to Revoke Patients' Private Data in Intelligent Healthcare
Juexiao Zhou, Haoyang Li, Xingyu Liao +5
Revoking personal private data is one of the basic human rights, which has already been sheltered by several privacy-preserving laws in many countries. However, with the developmen…
Curriculum Graph Machine Learning: A Survey
Haoyang Li, Xin Wang, Wenwu Zhu
Graph machine learning has been extensively studied in both academia and industry. However, in the literature, most existing graph machine learning models are designed to conduct t…
DLME: Deep Local-flatness Manifold Embedding
Zelin Zang, Siyuan Li, Di Wu +5
Manifold learning (ML) aims to seek low-dimensional embedding from high-dimensional data. The problem is challenging on real-world datasets, especially with under-sampling data, an…
Architecture-Agnostic Masked Image Modeling -- From ViT back to CNN
Siyuan Li, Di Wu, Fang Wu +2
Masked image modeling, an emerging self-supervised pre-training method, has shown impressive success across numerous downstream vision tasks with Vision transformers. Its underlyin…
Out-Of-Distribution Generalization on Graphs: A Survey
Haoyang Li, Xin Wang, Ziwei Zhang +1
Graph machine learning has been extensively studied in both academia and industry. Although booming with a vast number of emerging methods and techniques, most of the literature is…
Intelligent Electromagnetic Sensing with Learnable Data Acquisition and Processing
Hao-Yang Li, Han-Ting Zhao, Meng-Lin Wei +4
Electromagnetic (EM) sensing is a wide-spread contactless examination technique in science, engineering and military. However, conventional sensing systems are mostly lack of intel…
Controllable Enhancements of Wi-Fi Signals at Desired Locations Without Extra Energy Using Programmable Metasurface
Ya Shuang, Hanting Zhao, Menglin Wei +2
We present for the first time an experimental demonstration on the energy allocation of commodity Wi-Fi signals in a programmable and inexpensive way. To that end, we design an ele…
Intelligent Metasurface Imager and Recognizer
Lianlin Li, Ya Shuang, Qian Ma +7
It is ever-increasingly demanded to remotely monitor people in daily life using radio-frequency probing signals. However, conventional systems can hardly be deployed in real-world…
Billion-scale Network Embedding with Iterative Random Projection
Ziwei Zhang, Peng Cui, Haoyang Li +2
Network embedding, which learns low-dimensional vector representation for nodes in the network, has attracted considerable research attention recently. However, the existing method…