Chunyan Miao

Generative Topic Embedding: a Continuous Representation of Documents

2016

Word embedding maps words into a lowdimensional continuous embedding space by exploiting the local word collocation patterns in a small context window. On the other hand, topic modeling maps documents onto a low-dimensional topic space, …

A coarse-to-fine feature selection method for accurate detection of cerebral small vessel disease

2016

Cerebral small vessel disease (SVD) is common in the elderly and is associated with loss of functional independence, institutionalization, and death. In this paper, we propose a coarse-to-fine feature selection method for accurate SVD detection …

Federated Learning in Mobile Edge Networks: A Comprehensive Survey

2019 · arXiv (Cornell University)

In recent years, mobile devices are equipped with increasingly advanced sensing and computing capabilities. Coupled with advancements in Deep Learning (DL), this opens up countless possibilities for meaningful applications. Traditional cloudbased Machine Learning (ML) approaches …

Dynamic Contract Design for Federated Learning in Smart Healthcare Applications

2020 · IEEE Internet of Things Journal

Currently, the data collected by the Internet of Healthcare Things, i.e., healthcare oriented Internet of Things (IoT), still rely on cloud-based centralized data aggregation and processing. To reduce the need for transmission of data to …

Reputation-aware Hedonic Coalition Formation for Efficient Serverless Hierarchical Federated Learning

2021 · IEEE Transactions on Parallel and Distributed Systems

Amid growing concerns on data privacy, Federated Learning (FL) has emerged as a promising privacy preserving distributed machine learning paradigm. Given that the FL network is expected to be implemented at scale, several studies have …

Multi-Aspect Explainable Inductive Relation Prediction by Sentence Transformer

2023 · arXiv (Cornell University)

Recent studies on knowledge graphs (KGs) show that path-based methods empowered by pre-trained language models perform well in the provision of inductive and explainable relation predictions. In this paper, we introduce the concepts of relation …

Rethinking Negative Pairs in Code Search

2023

Recently, contrastive learning has become a key component in fine-tuning code search models for software development efficiency and effectiveness. It pulls together positive code snippets while pushing negative samples away given search queries. Among contrastive …

Context Pooling: Query-specific Graph Pooling for Generic Inductive Link Prediction in Knowledge Graphs

2025

Recent investigations on the effectiveness of Graph Neural Network (GNN)-based models for link prediction in Knowledge Graphs (KGs) show that vanilla aggregation does not significantly impact the model performance. In this paper, we introduce a …