b'Ying Sun'

research

∙ 08/28/2023

Which Parameterization of the Matérn Covariance Function?

The Matérn family of covariance functions is currently the most popularl...

0 Kesen Wang, et al. ∙

research

∙ 08/10/2023

Exploring the Efficacy of Statistical and Deep Learning Methods for Large Spatial Datasets: A Case Study

Increasingly large and complex spatial datasets pose massive inferential...

0 Arnab Hazra, et al. ∙

research

∙ 07/25/2023

Keyword-Aware Relative Spatio-Temporal Graph Networks for Video Question Answering

The main challenge in video question answering (VideoQA) is to capture a...

0 Yi Cheng, et al. ∙

research

∙ 07/16/2023

Bivariate DeepKriging for Large-scale Spatial Interpolation of Wind Fields

High spatial resolution wind data are essential for a wide range of appl...

0 Pratik Nag, et al. ∙

research

∙ 07/13/2023

A Study on Differentiable Logic and LLMs for EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2023

In this technical report, we present our findings from a study conducted...

0 Yi Cheng, et al. ∙

research

∙ 07/03/2023

A Comprehensive Survey of Artificial Intelligence Techniques for Talent Analytics

In today's competitive and fast-evolving business environment, it is a c...

0 Chuan Qin, et al. ∙

research

∙ 06/30/2023

Training-free Object Counting with Prompts

This paper tackles the problem of object counting in images. Existing ap...

0 Zenglin Shi, et al. ∙

research

∙ 06/20/2023

Efficient Large-scale Nonstationary Spatial Covariance Function Estimation Using Convolutional Neural Networks

Spatial processes observed in various fields, such as climate and enviro...

0 Pratik Nag, et al. ∙

research

∙ 06/20/2023

Spatio-temporal DeepKriging for Interpolation and Probabilistic Forecasting

Gaussian processes (GP) and Kriging are widely used in traditional spati...

0 Pratik Nag, et al. ∙

research

∙ 06/17/2023

A semi-parametric estimation method for quantile coherence with an application to bivariate financial time series clustering

In multivariate time series analysis, the coherence measures the linear ...

0 Cristian F. Jiménez-Varón, et al. ∙

research

∙ 05/31/2023

Forecasting high-dimensional functional time series: Application to sub-national age-specific mortality

We consider modeling and forecasting high-dimensional functional time se...

0 Cristian F. Jiménez-Varón, et al. ∙

research

∙ 04/29/2023

Large-Scale Assessment of Labour Market Dynamics in China during the COVID-19 Pandemic

The outbreak of the COVID-19 pandemic has had an unprecedented impact on...

0 Ying Sun, et al. ∙

research

∙ 04/10/2023

Meta Compositional Referring Expression Segmentation

Referring expression segmentation aims to segment an object described by...

0 Li Xu, et al. ∙

research

∙ 03/18/2023

Pseudo Supervised Metrics: Evaluating Unsupervised Image to Image Translation Models In Unsupervised Cross-Domain Classification Frameworks

The ability to classify images accurately and efficiently is dependent o...

0 Firas Al-Hindawi, et al. ∙

research

∙ 01/29/2023

Team VI-I2R Technical Report on EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2022

In this report, we present the technical details of our submission to th...

0 Yi Cheng, et al. ∙

research

∙ 12/18/2022

A Generalized Framework for Critical Heat Flux Detection Using Unsupervised Image-to-Image Translation

This work proposes a framework developed to generalize Critical Heat Flu...

0 Firas Al-Hindawi, et al. ∙

research

∙ 11/28/2022

Learning to Learn: How to Continuously Teach Humans and Machines

Our education system comprises a series of curricula. For example, when ...

0 Parantak Singh, et al. ∙

research

∙ 11/21/2022

On the Robustness, Generalization, and Forgetting of Shape-Texture Debiased Continual Learning

Tremendous progress has been made in continual learning to maintain good...

0 Zenglin Shi, et al. ∙

research

∙ 07/16/2022

Monitoring Vegetation From Space at Extremely Fine Resolutions via Coarsely-Supervised Smooth U-Net

Monitoring vegetation productivity at extremely fine resolutions is valu...

1 Joshua Fan, et al. ∙

research

∙ 07/14/2022

Visuo-Tactile Manipulation Planning Using Reinforcement Learning with Affordance Representation

Robots are increasingly expected to manipulate objects in ever more unst...

0 Wenyu Liang, et al. ∙

research

∙ 07/08/2022

Tackling Data Heterogeneity: A New Unified Framework for Decentralized SGD with Sample-induced Topology

We develop a general framework unifying several gradient-based stochasti...

0 Yan Huang, et al. ∙

research

∙ 06/03/2022

Team VI-I2R Technical Report on EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2021

In this report, we present the technical details of our approach to the ...

0 Yi Cheng, et al. ∙

research

∙ 05/24/2022

TAILOR: Teaching with Active and Incremental Learning for Object Registration

When deploying a robot to a new task, one often has to train it to detec...

2 Qianli Xu, et al. ∙

research

∙ 05/21/2022

Myocardial Segmentation of Late Gadolinium Enhanced MR Images by Propagation of Contours from Cine MR Images

Automatic segmentation of myocardium in Late Gadolinium Enhanced (LGE) C...

0 Dong Wei, et al. ∙

research

∙ 05/21/2022

A Comprehensive 3-D Framework for Automatic Quantification of Late Gadolinium Enhanced Cardiac Magnetic Resonance Images

Late gadolinium enhanced (LGE) cardiac magnetic resonance (CMR) can dire...

0 Dong Wei, et al. ∙

research

∙ 05/21/2022

Three-Dimensional Segmentation of the Left Ventricle in Late Gadolinium Enhanced MR Images of Chronic Infarction Combining Long- and Short-Axis Information

Automatic segmentation of the left ventricle (LV) in late gadolinium enh...

0 Dong Wei, et al. ∙

research

∙ 02/24/2022

Modeling and Predicting Spatio-temporal Dynamics of PM_2.5 Concentrations Through Time-evolving Covariance Models

Fine particulate matter (PM_2.5) has become a great concern worldwide du...

0 Ghulam A. Qadir, et al. ∙

research

∙ 01/21/2022

High-Dimensional Inference over Networks: Linear Convergence and Statistical Guarantees

We study sparse linear regression over a network of agents, modeled as a...

0 Ying Sun, et al. ∙

research

∙ 11/28/2021

FashionSearchNet-v2: Learning Attribute Representations with Localization for Image Retrieval with Attribute Manipulation

The focus of this paper is on the problem of image retrieval with attrib...

0 Kenan E. Ak, et al. ∙

research

∙ 11/12/2021

Distributed Sparse Regression via Penalization

We study sparse linear regression over a network of agents, modeled as a...

0 Yao Ji, et al. ∙

research

∙ 05/11/2021

Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks

Recently, embedding techniques have achieved impressive success in recom...

0 Yongchun Zhu, et al. ∙

research

∙ 01/04/2021

Using BART for Multiobjective Optimization of Noisy Multiple Objectives

Techniques to reduce the energy burden of an Industry 4.0 ecosystem ofte...

0 Akira Horiguchi, et al. ∙

research

∙ 08/09/2020

Visualization of Covariance Structures for Multivariate Spatio-Temporal Random Fields

The prevalence of multivariate space-time data collected from monitoring...

0 Huang Huang, et al. ∙

research

∙ 08/03/2020

High Performance Multivariate Spatial Modeling for Geostatistical Data on Manycore Systems

Modeling and inferring spatial relationships and predicting missing valu...

0 Mary Lai O. Salvaña, et al. ∙

research

∙ 07/28/2020

Collective Spectral Density Estimation and Clustering for Spatially-Correlated Data

In this paper, we develop a method for estimating and clustering two-dim...

0 Tianbo Chen, et al. ∙

research

∙ 07/28/2020

Clustering Brain Signals: A Robust Approach Using Functional Data Ranking

In this paper, we analyze electroencephalograms (EEG) which are recordin...

0 Tianbo Chen, et al. ∙

research

∙ 07/23/2020

DeepKriging: Spatially Dependent Deep Neural Networks for Spatial Prediction

In spatial statistics, a common objective is to predict the values of a ...

0 Yuxiao Li, et al. ∙

research

∙ 02/25/2020

Distributed Algorithms for Composite Optimization: Unified Framework and Convergence Analysis

We study distributed composite optimization over networks: agents minimi...

0 Jinming Xu, et al. ∙

research

∙ 02/25/2020

Distributed Algorithms for Composite Optimization: Unified and Tight Convergence Analysis

We study distributed composite optimization over networks: agents minimi...

0 Jinming Xu, et al. ∙

research

∙ 12/26/2019

Multi-Site High-Frequency Stochastic Precipitation Generator Using Censored Skew-Symmetric Distributions

Due to improved measuring instruments, an accurate stochastic weather ge...

0 Yuxiao Li, et al. ∙

research

∙ 12/03/2019

Robust and Secure Wireless Communications via Intelligent Reflecting Surfaces

In this paper, intelligent reflecting surfaces (IRSs) are employed to en...

0 Xianghao Yu, et al. ∙

research

∙ 11/11/2019

Efficiency Assessment of Approximated Spatial Predictions for Large Datasets

Due to the well-known computational showstopper of the exact Maximum Lik...

0 Yiping Hong, et al. ∙

research

∙ 11/06/2019

Semiparametric Estimation of Cross-covariance Functions for Multivariate Random Fields

The prevalence of spatially referenced multivariate data has impelled re...

0 Ghulam A. Qadir, et al. ∙

research

∙ 11/06/2019

Estimation of Spatial Deformation for Nonstationary Processes via Variogram Alignment

In modeling spatial processes, a second-order stationarity assumption is...

0 Ghulam A. Qadir, et al. ∙

research

∙ 10/23/2019

Accelerated Primal-Dual Algorithms for Distributed Smooth Convex Optimization over Networks

This paper proposes a novel family of primal-dual-based distributed algo...

0 Jinming Xu, et al. ∙

research

∙ 10/16/2019

A Semi-Parametric Estimation Method for the Quantile Spectrum with an Application to Earthquake Classification Using Convolutional Neural Network

In this paper, a new estimation method is introduced for the quantile sp...

0 Tianbo Chen, et al. ∙

research

∙ 07/23/2019

ExaGeoStatR: A Package for Large-Scale Geostatistics in R

Parallel computing in Gaussian process calculation becomes a necessity f...

0 Sameh Abdulah, et al. ∙

research

∙ 05/07/2019

Convergence Rate of Distributed Optimization Algorithms Based on Gradient Tracking

We study distributed, strongly convex and nonconvex, multiagent optimiza...

0 Ying Sun, et al. ∙

research

∙ 09/04/2018

Distributed Nonconvex Constrained Optimization over Time-Varying Digraphs

This paper considers nonconvex distributed constrained optimization over...

0 Gesualdo Scutari, et al. ∙

research

∙ 08/22/2018

Distributed Big-Data Optimization via Block-wise Gradient Tracking

We study distributed big-data nonconvex optimization in multi-agent netw...

0 Ivano Notarnicola, et al. ∙

Ying Sun

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