Search Results for author: Yue Sun

Found 29 papers, 8 papers with code

System Description on Automatic Simultaneous Translation Workshop

no code implementations NAACL (AutoSimTrans) 2022 Zecheng Li, Yue Sun, Haoze Li

This paper describes our system submitted on the third automatic simultaneous translation workshop at NAACL2022.

Sentence Translation

Incorporating Domain Differential Equations into Graph Convolutional Networks to Lower Generalization Discrepancy

no code implementations1 Apr 2024 Yue Sun, Chao Chen, Yuesheng Xu, Sihong Xie, Rick S. Blum, Parv Venkitasubramaniam

We theoretically derive conditions where GCNs incorporating such domain differential equations are robust to mismatched training and testing data compared to baseline domain agnostic models.

Domain Generalization Time Series Prediction

FourCastNeXt: Optimizing FourCastNet Training for Limited Compute

1 code implementation10 Jan 2024 Edison Guo, Maruf Ahmed, Yue Sun, Rui Yang, Harrison Cook, Tennessee Leeuwenburg, Ben Evans

FourCastNeXt is an optimization of FourCastNet - a global machine learning weather forecasting model - that performs with a comparable level of accuracy and can be trained using around 5% of the original FourCastNet computational requirements.

Model Optimization Weather Forecasting

A Parameterized Generative Adversarial Network Using Cyclic Projection for Explainable Medical Image Classification

1 code implementation24 Nov 2023 Xiangyu Xiong, Yue Sun, Xiaohong Liu, Chan-Tong Lam, Tong Tong, Hao Chen, Qinquan Gao, Wei Ke, Tao Tan

Although current data augmentation methods are successful to alleviate the data insufficiency, conventional augmentation are primarily intra-domain while advanced generative adversarial networks (GANs) generate images remaining uncertain, particularly in small-scale datasets.

Data Augmentation Generative Adversarial Network +2

Local Convolution Enhanced Global Fourier Neural Operator For Multiscale Dynamic Spaces Prediction

no code implementations21 Nov 2023 Xuanle Zhao, Yue Sun, Tielin Zhang, Bo Xu

One of the most notable methods is the Fourier Neural Operator (FNO), which is inspired by Green's function method and approximate operator kernel directly in the frequency domain.

Neurogenesis Dynamics-inspired Spiking Neural Network Training Acceleration

no code implementations24 Apr 2023 Shaoyi Huang, Haowen Fang, Kaleel Mahmood, Bowen Lei, Nuo Xu, Bin Lei, Yue Sun, Dongkuan Xu, Wujie Wen, Caiwen Ding

Experimental results show that NDSNN achieves up to 20. 52\% improvement in accuracy on Tiny-ImageNet using ResNet-19 (with a sparsity of 99\%) as compared to other SOTA methods (e. g., Lottery Ticket Hypothesis (LTH), SET-SNN, RigL-SNN).

Around the world in 60 words: A generative vocabulary test for online research

no code implementations3 Feb 2023 Pol van Rijn, Yue Sun, Harin Lee, Raja Marjieh, Ilia Sucholutsky, Francesca Lanzarini, Elisabeth André, Nori Jacoby

Six behavioral experiments (N=236) in six countries and eight languages show that (a) our test can distinguish between native speakers of closely related languages, (b) the test is reliable ($r=0. 82$), and (c) performance strongly correlates with existing tests (LexTale) and self-reports.

Cultural Vocal Bursts Intensity Prediction

Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off

no code implementations30 Nov 2022 Shaoyi Huang, Bowen Lei, Dongkuan Xu, Hongwu Peng, Yue Sun, Mimi Xie, Caiwen Ding

We further design an acquisition function and provide the theoretical guarantees for the proposed method and clarify its convergence property.

3D Reconstruction of Multiple Objects by mmWave Radar on UAV

no code implementations3 Nov 2022 Yue Sun, Zhuoming Huang, Honggang Zhang, Xiaohui Liang

The radar data is sent to a deep neural network model, which outputs the point cloud reconstruction of the multiple objects in the space.

3D Object Reconstruction Point cloud reconstruction

R2P: A Deep Learning Model from mmWave Radar to Point Cloud

no code implementations21 Jul 2022 Yue Sun, Honggang Zhang, Zhuoming Huang, Benyuan Liu

Recent research has shown the effectiveness of mmWave radar sensing for object detection in low visibility environments, which makes it an ideal technique in autonomous navigation systems.

3D Reconstruction Autonomous Navigation +4

System Identification via Nuclear Norm Regularization

1 code implementation30 Mar 2022 Yue Sun, Samet Oymak, Maryam Fazel

Hankel regularization encourages the low-rankness of the Hankel matrix, which maps to the low-orderness of the system.

Model Selection

Towards Sample-efficient Overparameterized Meta-learning

1 code implementation NeurIPS 2021 Yue Sun, Adhyyan Narang, Halil Ibrahim Gulluk, Samet Oymak, Maryam Fazel

Specifically, for (1), we first show that learning the optimal representation coincides with the problem of designing a task-aware regularization to promote inductive bias.

Few-Shot Learning Inductive Bias

DeepPoint: A Deep Learning Model for 3D Reconstruction in Point Clouds via mmWave Radar

no code implementations19 Sep 2021 Yue Sun, Honggang Zhang, Zhuoming Huang, Benyuan Liu

Built on our recent proposed 3DRIMR (3D Reconstruction and Imaging via mmWave Radar), we introduce in this paper DeepPoint, a deep learning model that generates 3D objects in point cloud format that significantly outperforms the original 3DRIMR design.

3D Reconstruction Autonomous Navigation +4

Quantum Machine Learning for Finance

no code implementations9 Sep 2021 Marco Pistoia, Syed Farhan Ahmad, Akshay Ajagekar, Alexander Buts, Shouvanik Chakrabarti, Dylan Herman, Shaohan Hu, Andrew Jena, Pierre Minssen, Pradeep Niroula, Arthur Rattew, Yue Sun, Romina Yalovetzky

In fact, finance is estimated to be the first industry sector to benefit from Quantum Computing not only in the medium and long terms, but even in the short term.

BIG-bench Machine Learning Quantum Machine Learning

3DRIMR: 3D Reconstruction and Imaging via mmWave Radar based on Deep Learning

no code implementations5 Aug 2021 Yue Sun, Zhuoming Huang, Honggang Zhang, Zhi Cao, Deqiang Xu

In this paper we propose 3D Reconstruction and Imaging via mmWave Radar (3DRIMR), a deep learning based architecture that reconstructs 3D shape of an object in dense detailed point cloud format, based on sparse raw mmWave radar intensity data.

3D Reconstruction

Sample Efficient Subspace-based Representations for Nonlinear Meta-Learning

no code implementations14 Feb 2021 Halil Ibrahim Gulluk, Yue Sun, Samet Oymak, Maryam Fazel

We prove that subspace-based representations can be learned in a sample-efficient manner and provably benefit future tasks in terms of sample complexity.

Binary Classification General Classification +2

A Hierarchical User Intention-Habit Extract Network for Credit Loan Overdue Risk Detection

no code implementations18 Aug 2020 Hao Guo, Xintao Ren, Rongrong Wang, Zhun Cai, Kai Shuang, Yue Sun

In this paper, we propose a model named HUIHEN (Hierarchical User Intention-Habit Extract Network) that leverages the users' behavior information in mobile banking APP.

Multi-Site Infant Brain Segmentation Algorithms: The iSeg-2019 Challenge

no code implementations4 Jul 2020 Yue Sun, Kun Gao, Zhengwang Wu, Zhihao Lei, Ying WEI, Jun Ma, Xiaoping Yang, Xue Feng, Li Zhao, Trung Le Phan, Jitae Shin, Tao Zhong, Yu Zhang, Lequan Yu, Caizi Li, Ramesh Basnet, M. Omair Ahmad, M. N. S. Swamy, Wenao Ma, Qi Dou, Toan Duc Bui, Camilo Bermudez Noguera, Bennett Landman, Ian H. Gotlib, Kathryn L. Humphreys, Sarah Shultz, Longchuan Li, Sijie Niu, Weili Lin, Valerie Jewells, Gang Li, Dinggang Shen, Li Wang

Deep learning-based methods have achieved state-of-the-art performance; however, one of major limitations is that the learning-based methods may suffer from the multi-site issue, that is, the models trained on a dataset from one site may not be applicable to the datasets acquired from other sites with different imaging protocols/scanners.

Brain Segmentation

Escaping from saddle points on Riemannian manifolds

no code implementations NeurIPS 2019 Yue Sun, Nicolas Flammarion, Maryam Fazel

We consider minimizing a nonconvex, smooth function $f$ on a Riemannian manifold $\mathcal{M}$.

Transform-Based Multilinear Dynamical System for Tensor Time Series Analysis

no code implementations18 Nov 2018 Weijun Lu, Xiao-Yang Liu, Qingwei Wu, Yue Sun, Anwar Walid

We propose a novel multilinear dynamical system (MLDS) in a transform domain, named $\mathcal{L}$-MLDS, to model tensor time series.

Time Series Time Series Analysis

Optimize transfer learning for lung diseases in bronchoscopy using a new concept: sequential fine-tuning

no code implementations10 Feb 2018 Tao Tan, Zhang Li, Haixia Liu, Ping Liu, Wenfang Tang, Hui Li, Yue Sun, Yusheng Yan, Keyu Li, Tao Xu, Shanshan Wan, Ke Lou, Jun Xu, Huiming Ying, Quchang Ouyang, Yuling Tang, Zheyu Hu, Qiang Li

To help doctors to be more selective on biopsies and provide a second opinion on diagnosis, in this work, we propose a computer-aided diagnosis (CAD) system for lung diseases including cancers and tuberculosis (TB).

Transfer Learning

Denoising of 3D magnetic resonance images with multi-channel residual learning of convolutional neural network

1 code implementation23 Dec 2017 Dongsheng Jiang, Weiqiang Dou, Luc Vosters, Xiayu Xu, Yue Sun, Tao Tan

Without noise level parameter, our general noise-applicable model is also better than the other compared methods in two datasets.


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