Search Results for author: Yu Duan

Found 8 papers, 3 papers with code

A Kronecker product accelerated efficient sparse Gaussian Process (E-SGP) for flow emulation

no code implementations13 Dec 2023 Yu Duan, Matthew Eaton, Michael Bluck

In this paper, we introduce an efficient sparse Gaussian process (E-SGP) for the surrogate modelling of fluid mechanics.

Computational Efficiency

Hebbian and Gradient-based Plasticity Enables Robust Memory and Rapid Learning in RNNs

1 code implementation7 Feb 2023 Yu Duan, Zhongfan Jia, Qian Li, Yi Zhong, Kaisheng Ma

Comparing different plasticity rules under the same framework shows that Hebbian plasticity is well-suited for several memory and associative learning tasks; however, it is outperformed by gradient-based plasticity on few-shot regression tasks which require the model to infer the underlying mapping.

Few-Shot Learning

Collaborative Intelligence Orchestration: Inconsistency-Based Fusion of Semi-Supervised Learning and Active Learning

no code implementations7 Jun 2022 Jiannan Guo, Yangyang Kang, Yu Duan, Xiaozhong Liu, Siliang Tang, Wenqiao Zhang, Kun Kuang, Changlong Sun, Fei Wu

Motivated by the industry practice of labeling data, we propose an innovative Inconsistency-based virtual aDvErsarial Active Learning (IDEAL) algorithm to further investigate SSL-AL's potential superiority and achieve mutual enhancement of AL and SSL, i. e., SSL propagates label information to unlabeled samples and provides smoothed embeddings for AL, while AL excludes samples with inconsistent predictions and considerable uncertainty for SSL.

Active Learning

Fixed Inducing Points Online Bayesian Calibration for Computer Models with an Application to a Scale-Resolving CFD Simulation

no code implementations15 Sep 2020 Yu Duan, Matthew Eaton, Michael Bluck

This paper proposes a novel fixed inducing points online Bayesian calibration (FIPO-BC) algorithm to efficiently learn the model parameters using a benchmark database.

Computational Efficiency

Camouflaged Chinese Spam Content Detection with Semi-supervised Generative Active Learning

no code implementations ACL 2020 Zhuoren Jiang, Zhe Gao, Yu Duan, Yangyang Kang, Changlong Sun, Qiong Zhang, Xiaozhong Liu

We propose a Semi-supervIsed GeNerative Active Learning (SIGNAL) model to address the imbalance, efficiency, and text camouflage problems of Chinese text spam detection task.

Active Learning Chinese Spam Detection +2

Pre-train and Plug-in: Flexible Conditional Text Generation with Variational Auto-Encoders

1 code implementation ACL 2020 Yu Duan, Canwen Xu, Jiaxin Pei, Jialong Han, Chenliang Li

Conditional Text Generation has drawn much attention as a topic of Natural Language Generation (NLG) which provides the possibility for humans to control the properties of generated contents.

Conditional Text Generation

Enhancing Topic Modeling for Short Texts with Auxiliary Word Embeddings

no code implementations22 Dec 2018 Chenliang Li, Yu Duan, Haoran Wang, Zhiqian Zhang, Aixin Sun, Zongyang Ma

Recent studies show that the Dirichlet Multinomial Mixture (DMM) model is effective for topic inference over short texts by assuming that each piece of short text is generated by a single topic.

text-classification Topic Models +1

A Deep Relevance Model for Zero-Shot Document Filtering

1 code implementation ACL 2018 Chenliang Li, Wei Zhou, Feng Ji, Yu Duan, Haiqing Chen

In the era of big data, focused analysis for diverse topics with a short response time becomes an urgent demand.

Sentiment Analysis Text Classification +1

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