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08/28/2023
Which Parameterization of the Matérn Covariance Function?
The Matérn family of covariance functions is currently the most popularl...
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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...
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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...
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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...
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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...
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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...
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06/30/2023
Training-free Object Counting with Prompts
This paper tackles the problem of object counting in images. Existing ap...
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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...
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06/20/2023
Spatio-temporal DeepKriging for Interpolation and Probabilistic Forecasting
Gaussian processes (GP) and Kriging are widely used in traditional spati...
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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 ...
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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...
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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...
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04/10/2023
Meta Compositional Referring Expression Segmentation
Referring expression segmentation aims to segment an object described by...
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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...
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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...
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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...
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11/28/2022
Learning to Learn: How to Continuously Teach Humans and Machines
Our education system comprises a series of curricula. For example, when ...
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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...
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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...
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07/14/2022
Visuo-Tactile Manipulation Planning Using Reinforcement Learning with Affordance Representation
Robots are increasingly expected to manipulate objects in ever more unst...
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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...
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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 ...
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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...
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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...
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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...
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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...
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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...
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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...
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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...
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11/12/2021
Distributed Sparse Regression via Penalization
We study sparse linear regression over a network of agents, modeled as a...
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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...
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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...
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08/09/2020
Visualization of Covariance Structures for Multivariate Spatio-Temporal Random Fields
The prevalence of multivariate space-time data collected from monitoring...
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08/03/2020
High Performance Multivariate Spatial Modeling for Geostatistical Data on Manycore Systems
Modeling and inferring spatial relationships and predicting missing valu...
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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...
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07/28/2020
Clustering Brain Signals: A Robust Approach Using Functional Data Ranking
In this paper, we analyze electroencephalograms (EEG) which are recordin...
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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 ...
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02/25/2020
Distributed Algorithms for Composite Optimization: Unified Framework and Convergence Analysis
We study distributed composite optimization over networks: agents minimi...
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02/25/2020
Distributed Algorithms for Composite Optimization: Unified and Tight Convergence Analysis
We study distributed composite optimization over networks: agents minimi...
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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...
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12/03/2019
Robust and Secure Wireless Communications via Intelligent Reflecting Surfaces
In this paper, intelligent reflecting surfaces (IRSs) are employed to en...
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11/11/2019
Efficiency Assessment of Approximated Spatial Predictions for Large Datasets
Due to the well-known computational showstopper of the exact Maximum Lik...
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11/06/2019
Semiparametric Estimation of Cross-covariance Functions for Multivariate Random Fields
The prevalence of spatially referenced multivariate data has impelled re...
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11/06/2019
Estimation of Spatial Deformation for Nonstationary Processes via Variogram Alignment
In modeling spatial processes, a second-order stationarity assumption is...
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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...
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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...
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07/23/2019
ExaGeoStatR: A Package for Large-Scale Geostatistics in R
Parallel computing in Gaussian process calculation becomes a necessity f...
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05/07/2019
Convergence Rate of Distributed Optimization Algorithms Based on Gradient Tracking
We study distributed, strongly convex and nonconvex, multiagent optimiza...
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09/04/2018
Distributed Nonconvex Constrained Optimization over Time-Varying Digraphs
This paper considers nonconvex distributed constrained optimization over...
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08/22/2018