Search Results for author: Fenglong Ma

Found 23 papers, 5 papers with code

Predicting Ulnar Collateral Ligament Injury in Rookie Major League Baseball Pitchers

no code implementations30 Jun 2022 Sean A. Rendar, Fenglong Ma

In the growing world of machine learning and data analytics, scholars are finding new and innovative ways to solve real-world problems.

MedAttacker: Exploring Black-Box Adversarial Attacks on Risk Prediction Models in Healthcare

no code implementations11 Dec 2021 Muchao Ye, Junyu Luo, Guanjie Zheng, Cao Xiao, Ting Wang, Fenglong Ma

Deep neural networks (DNNs) have been broadly adopted in health risk prediction to provide healthcare diagnoses and treatments.

Adversarial Attack

FedTriNet: A Pseudo Labeling Method with Three Players for Federated Semi-supervised Learning

no code implementations12 Sep 2021 Liwei Che, Zewei Long, Jiaqi Wang, Yaqing Wang, Houping Xiao, Fenglong Ma

In particular, we propose to use three networks and a dynamic quality control mechanism to generate high-quality pseudo labels for unlabeled data, which are added to the training set.

Federated Learning

FedCon: A Contrastive Framework for Federated Semi-Supervised Learning

no code implementations9 Sep 2021 Zewei Long, Jiaqi Wang, Yaqing Wang, Houping Xiao, Fenglong Ma

Most existing FedSSL methods focus on the classical scenario, i. e, the labeled and unlabeled data are stored at the client side.

Multimodal Emergent Fake News Detection via Meta Neural Process Networks

no code implementations22 Jun 2021 Yaqing Wang, Fenglong Ma, Haoyu Wang, Kishlay Jha, Jing Gao

The experimental results show our proposed MetaFEND model can detect fake news on never-seen events effectively and outperform the state-of-the-art methods.

Fake News Detection Hard Attention +1

ConCAD: Contrastive Learning-based Cross Attention for Sleep Apnea Detection

no code implementations7 May 2021 Guanjie Huang, Fenglong Ma

With recent advancements in deep learning methods, automatically learning deep features from the original data is becoming an effective and widespread approach.

Contrastive Learning Sleep apnea detection

SafeDrug: Dual Molecular Graph Encoders for Safe Drug Recommendations

1 code implementation5 May 2021 Chaoqi Yang, Cao Xiao, Fenglong Ma, Lucas Glass, Jimeng Sun

On a benchmark dataset, our SafeDrug is relatively shown to reduce DDI by 19. 43% and improves 2. 88% on Jaccard similarity between recommended and actually prescribed drug combinations over previous approaches.

Fairness-aware Outlier Ensemble

no code implementations17 Mar 2021 Haoyu Liu, Fenglong Ma, Shibo He, Jiming Chen, Jing Gao

Meanwhile, we propose a post-processing framework to tune the original ensemble results through a stacking process so that we can achieve a trade off between fairness and detection performance.

Fairness Fraud Detection +1

i-Algebra: Towards Interactive Interpretability of Deep Neural Networks

no code implementations22 Jan 2021 Xinyang Zhang, Ren Pang, Shouling Ji, Fenglong Ma, Ting Wang

Providing explanations for deep neural networks (DNNs) is essential for their use in domains wherein the interpretability of decisions is a critical prerequisite.

FedSiam: Towards Adaptive Federated Semi-Supervised Learning

no code implementations6 Dec 2020 Zewei Long, Liwei Che, Yaqing Wang, Muchao Ye, Junyu Luo, Jinze Wu, Houping Xiao, Fenglong Ma

In this paper, we focus on designing a general framework FedSiam to tackle different scenarios of federated semi-supervised learning, including four settings in the labels-at-client scenario and two setting in the labels-at-server scenario.

Federated Learning

A Benchmark Dataset for Understandable Medical Language Translation

no code implementations4 Dec 2020 Junyu Luo, Zifei Zheng, Hanzhong Ye, Muchao Ye, Yaqing Wang, Quanzeng You, Cao Xiao, Fenglong Ma

In this paper, we introduce MedLane -- a new human-annotated Medical Language translation dataset, to align professional medical sentences with layperson-understandable expressions.

Benchmark Machine Translation +2

UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data

no code implementations22 Oct 2020 Chacha Chen, Junjie Liang, Fenglong Ma, Lucas M. Glass, Jimeng Sun, Cao Xiao

However, existing uncertainty estimation approaches often failed in handling high-dimensional data, which are present in multi-sourced data.

Variational Inference

Efficient Knowledge Graph Validation via Cross-Graph Representation Learning

no code implementations16 Aug 2020 Yaqing Wang, Fenglong Ma, Jing Gao

To tackle this challenging task, we propose a cross-graph representation learning framework, i. e., CrossVal, which can leverage an external KG to validate the facts in the target KG efficiently.

Graph Representation Learning Knowledge Graphs

Weak Supervision for Fake News Detection via Reinforcement Learning

1 code implementation28 Dec 2019 Yaqing Wang, Weifeng Yang, Fenglong Ma, Jin Xu, Bin Zhong, Qiang Deng, Jing Gao

In order to tackle this challenge, we propose a reinforced weakly-supervised fake news detection framework, i. e., WeFEND, which can leverage users' reports as weak supervision to enlarge the amount of training data for fake news detection.

Fake News Detection reinforcement-learning

Multi-Grained Named Entity Recognition

1 code implementation ACL 2019 Congying Xia, Chenwei Zhang, Tao Yang, Yaliang Li, Nan Du, Xian Wu, Wei Fan, Fenglong Ma, Philip Yu

This paper presents a novel framework, MGNER, for Multi-Grained Named Entity Recognition where multiple entities or entity mentions in a sentence could be non-overlapping or totally nested.

Multi-Grained Named Entity Recognition named-entity-recognition +3

Long-Term Memory Networks for Question Answering

no code implementations6 Jul 2017 Fenglong Ma, Radha Chitta, Saurabh Kataria, Jing Zhou, Palghat Ramesh, Tong Sun, Jing Gao

Question answering is an important and difficult task in the natural language processing domain, because many basic natural language processing tasks can be cast into a question answering task.

Natural Language Processing Question Answering

Dipole: Diagnosis Prediction in Healthcare via Attention-based Bidirectional Recurrent Neural Networks

no code implementations19 Jun 2017 Fenglong Ma, Radha Chitta, Jing Zhou, Quanzeng You, Tong Sun, Jing Gao

Existing work solves this problem by employing recurrent neural networks (RNNs) to model EHR data and utilizing simple attention mechanism to interpret the results.

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