Yaqing Wang

Orcid: 0000-0002-1548-0727

Affiliations:
  • Google Deepmind
  • Purdue University, IN, USA (Ph.D.)


According to our database1, Yaqing Wang authored at least 49 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
FIARSE: Model-Heterogeneous Federated Learning via Importance-Aware Submodel Extraction.
CoRR, 2024

MedDiffusion: Boosting Health Risk Prediction via Diffusion-based Data Augmentation.
Proceedings of the 2024 SIAM International Conference on Data Mining, 2024

Synthesizing Multimodal Electronic Health Records via Predictive Diffusion Models.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

AdaDiff: Accelerating Diffusion Models Through Step-Wise Adaptive Computation.
Proceedings of the Computer Vision - ECCV 2024, 2024

CoRelation: Boosting Automatic ICD Coding through Contextualized Code Relation Learning.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Unity in Diversity: Collaborative Pre-training Across Multimodal Medical Sources.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
Knowledge-Enhanced Semi-Supervised Federated Learning for Aggregating Heterogeneous Lightweight Clients in IoT.
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023

Macular: A Multi-Task Adversarial Framework for Cross-Lingual Natural Language Understanding.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

LightToken: A Task and Model-agnostic Lightweight Token Embedding Framework for Pre-trained Language Models.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Hierarchical Pretraining on Multimodal Electronic Health Records.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Macedon: Minimizing Representation Coding Rate Reduction for Cross-Lingual Natural Language Understanding.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

HadSkip: Homotopic and Adaptive Layer Skipping of Pre-trained Language Models for Efficient Inference.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

SimFair: A Unified Framework for Fairness-Aware Multi-Label Classification.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
AdaMix: Mixture-of-Adapter for Parameter-efficient Tuning of Large Language Models.
CoRR, 2022

FedKC: Federated Knowledge Composition for Multilingual Natural Language Understanding.
Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

LiST: Lite Prompted Self-training Makes Parameter-efficient Few-shot Learners.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2022, 2022

Heterogeneous Information Enhanced Prerequisite Learning in Massive Open Online Courses.
Proceedings of the IEEE International Conference on Data Mining, 2022

AdaMix: Mixture-of-Adaptations for Parameter-efficient Model Tuning.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021
LiST: Lite Self-training Makes Efficient Few-shot Learners.
CoRR, 2021

FedCon: A Contrastive Framework for Federated Semi-Supervised Learning.
CoRR, 2021

MedPath: Augmenting Health Risk Prediction via Medical Knowledge Paths.
Proceedings of the WWW '21: The Web Conference 2021, 2021

Fair Classification Under Strict Unawareness.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Towards Learning Outcome Prediction via Modeling Question Explanations and Student Responses.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Multimodal Emergent Fake News Detection via Meta Neural Process Networks.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Meta Self-training for Few-shot Neural Sequence Labeling.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Knowledge-Guided Paraphrase Identification.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Learning from Language Description: Low-shot Named Entity Recognition via Decomposed Framework.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

MedRetriever: Target-Driven Interpretable Health Risk Prediction via Retrieving Unstructured Medical Text.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

A Lightweight Knowledge Graph Embedding Framework for Efficient Inference and Storage.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

FedTriNet: A Pseudo Labeling Method with Three Players for Federated Semi-supervised Learning.
Proceedings of the 2021 IEEE International Conference on Big Data (Big Data), 2021

InterHG: an Interpretable and Accurate Model for Hypothesis Generation.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2021

2020
FedSemi: An Adaptive Federated Semi-Supervised Learning Framework.
CoRR, 2020

A Benchmark Dataset for Understandable Medical Language Translation.
CoRR, 2020

Adaptive Self-training for Few-shot Neural Sequence Labeling.
CoRR, 2020

Decomposed Adversarial Learned Inference.
CoRR, 2020

Rare Disease Prediction by Generating Quality-Assured Electronic Health Records.
Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Automatic Validation of Textual Attribute Values in E-commerce Catalog by Learning with Limited Labeled Data.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020

LP-Explain: Local Pictorial Explanation for Outliers.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Efficient Knowledge Graph Validation via Cross-Graph Representation Learning.
Proceedings of the CIKM '20: The 29th ACM International Conference on Information and Knowledge Management, 2020

Weak Supervision for Fake News Detection via Reinforcement Learning.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Incorporating medical code descriptions for diagnosis prediction in healthcare.
BMC Medical Informatics Decis. Mak., 2019

A hybrid self-attention deep learning framework for multivariate sleep stage classification.
BMC Bioinform., 2019

2018
Towards Environment Independent Device Free Human Activity Recognition.
Proceedings of the 24th Annual International Conference on Mobile Computing and Networking, 2018

EANN: Event Adversarial Neural Networks for Multi-Modal Fake News Detection.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

MuVAN: A Multi-view Attention Network for Multivariate Temporal Data.
Proceedings of the IEEE International Conference on Data Mining, 2018

Multivariate Sleep Stage Classification using Hybrid Self-Attentive Deep Learning Networks.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

A General Framework for Diagnosis Prediction via Incorporating Medical Code Descriptions.
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine, 2018

Leveraging the Power of Informative Users for Local Event Detection.
Proceedings of the IEEE/ACM 2018 International Conference on Advances in Social Networks Analysis and Mining, 2018

2017
Discovering Truths from Distributed Data.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017


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