Publications (207)
Forecasting Multivariate Time Series under Predictive Heterogeneity: A Validation-Driven Clustering Framework
Ziling Ma, Ãngel López Oriona, Hernando Ombao +1
We study adaptive pooling under predictive heterogeneity in high-dimensional multivariate time series forecasting, where global models improve statistical efficiency but may fail t…
Fuzzy clustering of circular time series based on a new dependence measure with applications to wind data
Ãngel López-Oriona, Ying Sun, Rosa M. Crujeiras
Time series clustering is an essential machine learning task with applications in many disciplines. While the majority of the methods focus on time series taking values on the real…
Spatio-temporal DeepKriging for Interpolation and Probabilistic Forecasting
Pratik Nag, Ying Sun, Brian J Reich
Gaussian processes (GP) and Kriging are widely used in traditional spatio-temporal mod-elling and prediction. These techniques typically presuppose that the data are observed from…
Escaping the KL Agreement Trap in On-Policy Distillation
Haoran Xin, Anhao Zhao, Ying Sun +3
On-policy distillation (OPD) provides dense token-level supervision by asking a teacher to score student-generated rollouts. However, when the student drifts into an unrecoverable…
FreqINR: Frequency Consistency for Implicit Neural Representation with Adaptive DCT Frequency Loss
Meiyi Wei, Liu Xie, Ying Sun +1
Recent advancements in local Implicit Neural Representation (INR) demonstrate its exceptional capability in handling images at various resolutions. However, frequency discrepancies…
HDMoE: A Hierarchical Decoupling-Fusion Mixture-of-Experts Framework for Multimodal Cancer Survival Prediction
Huayi Wang, Haochao Ying, Yuyang Xu +5
Multimodal survival prediction, a crucial yet challenging task, demands the integration of multimodal medical data (\eg Whole Slide Images (WSIs) and Genomic Profiles) to achieve a…
Distributed Stochastic Bilevel Optimization: Improved Complexity and Heterogeneity Analysis
Youcheng Niu, Jinming Xu, Ying Sun +2
This paper consider solving a class of nonconvex-strongly-convex distributed stochastic bilevel optimization (DSBO) problems with personalized inner-level objectives. Most existing…
Team I2R-VI-FF Technical Report on EPIC-KITCHENS VISOR Hand Object Segmentation Challenge 2023
Fen Fang, Yi Cheng, Ying Sun +1
In this report, we present our approach to the EPIC-KITCHENS VISOR Hand Object Segmentation Challenge, which focuses on the estimation of the relation between the hands and the obj…
Robust Estimation of Structured Covariance Matrix for Heavy-Tailed Elliptical Distributions
Ying Sun, Prabhu Babu, Daniel P. Palomar
This paper considers the problem of robustly estimating a structured covariance matrix with an elliptical underlying distribution with known mean. In applications where the covaria…
Exploring the Efficacy of Statistical and Deep Learning Methods for Large Spatial Datasets: A Case Study
Arnab Hazra, Pratik Nag, Rishikesh Yadav +1
Increasingly large and complex spatial datasets pose massive inferential challenges due to high computational and storage costs. Our study is motivated by the KAUST Competition on…
MALT: Lightweight Curvature-Aware Muon via Diagonal Preconditioning
Tongle Wu, Huanyu Dong, Ying Sun +1
Muon has recently emerged as a promising alternative to AdamW for language model pretraining by orthogonalizing momentum matrices using Newton-Schulz iterations. Although Muon miti…
High-Entropy Enhanced Negative Thermal Expansion Perfomance in Antiperovkites
Xiuliang Yuan, Bing Wang, Ying Sun +16
The negative thermal expansion (NTE) materials, which can act as thermal-expansion compensators to counteract the positive thermal expansion, have great applications merit in preci…
Large-scale Environmental Data Science with ExaGeoStatR
Sameh Abdulah, Yuxiao Li, Jian Cao +4
Parallel computing in Gaussian process calculations becomes necessary for avoiding computational and memory restrictions associated with large-scale environmental data science appl…
Unveiling the Tapestry: the Interplay of Generalization and Forgetting in Continual Learning
Zenglin Shi, Jing Jie, Ying Sun +2
In AI, generalization refers to a model's ability to perform well on out-of-distribution data related to the given task, beyond the data it was trained on. For an AI agent to excel…
SGD with Partial Hessian for Deep Neural Networks Optimization
Ying Sun, Hongwei Yong, Lei Zhang
Due to the effectiveness of second-order algorithms in solving classical optimization problems, designing second-order optimizers to train deep neural networks (DNNs) has attracted…
Multidimensional Integral Fractional Ornstein--Uhlenbeck Process with an Application to Animal Movement
J. H. RamÃrez-González, J. H. Ramírez-González, Erick A. Chacón-Montalván +3
Fractional Ornstein--Uhlenbeck (fOU) processes model temporal dependence and memory, including long-range dependence, while retaining the classical Ornstein--Uhlenbeck process as a…
Improving Recommendation Fairness without Sensitive Attributes Using Multi-Persona LLMs
Haoran Xin, Ying Sun, Chao Wang +3
Despite the success of recommender systems in alleviating information overload, fairness issues have raised concerns in recent years, potentially leading to unequal treatment for c…
Unified Dual-Intent Translation for Joint Modeling of Search and Recommendation
Yuting Zhang, Yiqing Wu, Ruidong Han +7
Recommendation systems, which assist users in discovering their preferred items among numerous options, have served billions of users across various online platforms. Intuitively,…
Distributed Big-Data Optimization via Block-Iterative Convexification and Averaging
Ivano Notarnicola, Ying Sun, Gesualdo Scutari +1
In this paper, we study distributed big-data nonconvex optimization in multi-agent networks. We consider the (constrained) minimization of the sum of a smooth (possibly) nonconvex…
Test and Visualization of Covariance Properties for Multivariate Spatio-Temporal Random Fields
Huang Huang, Ying Sun, Marc G. Genton
The prevalence of multivariate space-time data collected from monitoring networks and satellites, or generated from numerical models, has brought much attention to multivariate spa…
ChemATP: A Training-Free Chemical Reasoning Framework for Large Language Models
Mingxu Zhang, Dazhong Shen, Qi Zhang +1
Large Language Models (LLMs) exhibit strong general reasoning but struggle in molecular science due to the lack of explicit chemical priors in standard string representations. Curr…
Bivariate DeepKriging for Large-scale Spatial Interpolation of Wind Fields
Pratik Nag, Ying Sun, Brian J Reich
High spatial resolution wind data are essential for a wide range of applications in climate, oceanographic and meteorological studies. Large-scale spatial interpolation or downscal…
LLMs as Better Recommenders with Natural Language Collaborative Signals: A Self-Assessing Retrieval Approach
Haoran Xin, Ying Sun, Chao Wang +2
Incorporating collaborative information (CI) effectively is crucial for leveraging LLMs in recommendation tasks. Existing approaches often encode CI using soft tokens or abstract i…
Team VI-I2R Technical Report on EPIC-KITCHENS-100 Unsupervised Domain Adaptation Challenge for Action Recognition 2022
Yi Cheng, Dongyun Lin, Fen Fang +3
In this report, we present the technical details of our submission to the EPIC-KITCHENS-100 Unsupervised Domain Adaptation (UDA) Challenge for Action Recognition 2022. This task ai…
Decouple, Reorganize, and Fuse: A Multimodal Framework for Cancer Survival Prediction
Huayi Wang, Haochao Ying, Yuyang Xu +5
Cancer survival analysis commonly integrates information across diverse medical modalities to make survival-time predictions. Existing methods primarily focus on extracting differe…
Keyword-Aware Relative Spatio-Temporal Graph Networks for Video Question Answering
Yi Cheng, Hehe Fan, Dongyun Lin +3
The main challenge in video question answering (VideoQA) is to capture and understand the complex spatial and temporal relations between objects based on given questions. Existing…
Parallel and Distributed Successive Convex Approximation Methods for Big-Data Optimization
Gesualdo Scutari, Ying Sun
Recent years have witnessed a surge of interest in parallel and distributed optimization methods for large-scale systems. In particular, nonconvex large-scale optimization problems…
The Impact of Ionic Anharmonicity on Superconductivity in Metal-Stuffed B-C Clathrates
Wenbo Zhao, Ying Sun, Jiaxiang Li +8
Metal-stuffed BC compounds with sodalite clathrate structure have captured increasing attention due to their predicted exceptional superconductivity above liquid nitrogen temper…
Understanding the Statistical Accuracy-Communication Trade-off in Personalized Federated Learning with Minimax Guarantees
Xin Yu, Zelin He, Ying Sun +2
Personalized federated learning (PFL) offers a flexible framework for aggregating information across distributed clients with heterogeneous data. This work considers a personalized…
Discrete Preference Learning for Personalized Multimodal Generation
Yuting Zhang, Ying Sun, Dazhong Shen +6
The emergence of generative models enables the creation of texts and images tailored to users' preferences. Existing personalized generative models have two critical limitations: l…
OThink-MR1: Stimulating multimodal generalized reasoning capabilities via dynamic reinforcement learning
Zhiyuan Liu, Yuting Zhang, Feng Liu +3
Multimodal Large Language Models (MLLMs) have gained significant traction for their ability to process diverse input data types and generate coherent, contextually relevant outputs…
Total Variation Depth for Functional Data
Huang Huang, Ying Sun
There has been extensive work on data depth-based methods for robust multivariate data analysis. Recent developments have moved to infinite-dimensional objects such as functional d…
Your AI-Generated Image Detector Can Secretly Achieve SOTA Accuracy, If Calibrated
Muli Yang, Gabriel James Goenawan, Henan Wang +7
Despite being trained on balanced datasets, existing AI-generated image detectors often exhibit systematic bias at test time, frequently misclassifying fake images as real. We hypo…
Hydride Units Filled B--C Clathrate: A New Pathway for High-Temperature Superconductivity at Ambient Pressure
Ying Sun, Li Zhu
The pursuit of room-temperature superconductors has recently advanced with the discovery of high-temperature superconductivity in compressed hydrides, although sustaining the super…
Epitaxial growth of bilayer Bi(110) on two-dimensional ferromagnetic Fe3GeTe2
Yilian Xi, Mengting Zhao, Haifeng Feng +6
Heterostructures of two-dimensional (2D) layered materials with selective compositions play an important role in creating novel functionalities. Effective interface coupling betwee…
Distributed Sparse Regression via Penalization
Yao Ji, Gesualdo Scutari, Ying Sun +1
We study sparse linear regression over a network of agents, modeled as an undirected graph (with no centralized node). The estimation problem is formulated as the minimization of t…
Distributed Nonconvex Optimization for Sparse Representation
Ying Sun, Gesualdo Scutari
We consider a non-convex constrained Lagrangian formulation of a fundamental bi-criteria optimization problem for variable selection in statistical learning; the two criteria are a…
FCPCA: Fuzzy clustering of high-dimensional time series based on common principal component analysis
Ziling Ma, Ãngel López-Oriona, Hernando Ombao +1
Clustering multivariate time series data is a crucial task in many domains, as it enables the identification of meaningful patterns and groups in time-evolving data. Traditional ap…
Interactive Interior Design Recommendation via Coarse-to-fine Multimodal Reinforcement Learning
He Zhang, Ying Sun, Weiyu Guo +4
Personalized interior decoration design often incurs high labor costs. Recent efforts in developing intelligent interior design systems have focused on generating textual requireme…
PHF: Privileged Hidden Flow for On-Policy Self-Distillation
Yuhan Li, Mingxu Zhang, Dazhong Shen +1
On-policy self-distillation (OPSD) trains a reasoning model on rollouts sampled from its own policy by matching a privileged teacher that also sees verified reference solutions. Ex…
Classifications of Single-input Lower Triangular Forms
Duan Zhang, Ying Sun
The purposes of this paper are to classify lower triangular forms and to determine under what conditions a nonlinear system is equivalent to a specific type of lower triangular for…
SLIM: Sparse Latent Steering for Interpretable and Property-Directed LLM-Based Molecular Editing
Mingxu Zhang, Yuhan Li, Lujundong Li +3
Large language models possess strong chemical reasoning capabilities, making them effective molecular editors. However, property-relevant information is implicitly entangled across…
Infrared evidence of a Slater metal-insulator transition in NaOsO3
Irene Lo Vecchio, Andrea Perucchi, Paola Di Pietro +6
The magnetically driven metal-insulator transition (MIT) was predicted by Slater in the fifties. Here a long-range antiferromagnetic (AF) order can open up a gap at the Brillouin e…
Exploring the Magnitude-Shape Plot Framework for Anomaly Detection in Crowded Video Scenes
Zuzheng Wang, Fouzi Harrou, Ying Sun +1
Detecting anomalies in crowded video scenes is critical for public safety, enabling timely identification of potential threats. This study explores video anomaly detection within a…
Bone marrow sparing for cervical cancer radiotherapy on multimodality medical images
Yuening Wang, Ying Sun, Jie Yuan +4
Cervical cancer threatens the health of women seriously. Radiotherapy is one of the main therapy methods but with high risk of acute hematologic toxicity. Delineating the bone marr…
GPU-Accelerated Modified Bessel Function of the Second Kind for Gaussian Processes
Zipei Geng, Sameh Abdulah, Ying Sun +3
Modified Bessel functions of the second kind are widely used in physics, engineering, spatial statistics, and machine learning. Since contemporary scientific applications, includin…
A Survey of fMRI to Image Reconstruction
Weiyu Guo, Guoying Sun, JianXiang He +6
Functional magnetic resonance imaging (fMRI) based image reconstruction plays a pivotal role in decoding human perception, with applications in neuroscience and brain-computer inte…
Domain-knowledge Inspired Pseudo Supervision (DIPS) for Unsupervised Image-to-Image Translation Models to Support Cross-Domain Classification
Firas Al-Hindawi, Md Mahfuzur Rahman Siddiquee, Teresa Wu +2
The ability to classify images is dependent on having access to large labeled datasets and testing on data from the same domain that the model can train on. Classification becomes…
Revisiting Phase Stability and Superconductivity in Ca-H Superhydrides with Anharmonic Effects
Wenbo Zhao, Zefang Wang, Ying Sun +3
The prediction of superconductivity above 200 K in CaH revolutionized research on hydrogen-rich superconductors, and subsequent experiments have verified this prediction, while…
A Geometric Approach to Visualization of Variability in Functional Data
Weiyi Xie, Sebastian Kurtek, Karthik Bharath +1
We propose a new method for the construction and visualization of boxplot-type displays for functional data. We use a recent functional data analysis framework, based on a represen…
TAILOR: Teaching with Active and Incremental Learning for Object Registration
Qianli Xu, Nicolas Gauthier, Wenyu Liang +6
When deploying a robot to a new task, one often has to train it to detect novel objects, which is time-consuming and labor-intensive. We present TAILOR -- a method and system for o…
Convolutional Neural Networks for Automated Annotation of Cellular Cryo-Electron Tomograms
Muyuan Chen, Wei Dai, Ying Sun +5
Cellular Electron Cryotomography (CryoET) offers the ability to look inside cells and observe macromolecules frozen in action. A primary challenge for this technique is identifying…
Large-time Behavior of Magnetohydrodynamics with Temperature-Dependent Heat-Conductivity
Bin Huang, Xiaoding Shi, Ying Sun
We study the large-time behavior of strong solutions to the equations of a planar magnetohydrodynamic compressible flow with the heat conductivity proportional to a nonnegative pow…
Efficient Skill Discovery via Regret-Aware Optimization
He Zhang, Ming Zhou, Shaopeng Zhai +2
Unsupervised skill discovery aims to learn diverse and distinguishable behaviors in open-ended reinforcement learning. For existing methods, they focus on improving diversity throu…
Logic-in-Frames: Dynamic Keyframe Search via Visual Semantic-Logical Verification for Long Video Understanding
Weiyu Guo, Ziyang Chen, Shaoguang Wang +5
Understanding long video content is a complex endeavor that often relies on densely sampled frame captions or end-to-end feature selectors, yet these techniques commonly overlook t…
Revisiting Noise Resilience Strategies in Gesture Recognition: Short-Term Enhancement in Surface Electromyographic Signal Analysis
Weiyu Guo, Ziyue Qiao, Ying Sun +1
Gesture recognition based on surface electromyography (sEMG) has been gaining importance in many 3D Interactive Scenes. However, sEMG is easily influenced by various forms of noise…
A semi-parametric estimation method for quantile coherence with an application to bivariate financial time series clustering
Cristian F. Jiménez-Varón, Ying Sun, Ta-Hsin Li
In multivariate time series analysis, spectral coherence measures the linear dependency between two time series at different frequencies. However, real data applications often exhi…
Superconductivity suppression of Ba0.5K0.5Fe2-2xM2xAs2 single crystals by substitution of transition-metal (M = Mn, Ru, Co, Ni, Cu, and Zn)
Jun Li, Yanfeng Guo, Shoubao Zhang +12
We investigated the doping effects of magnetic and nonmagnetic impurities on the single-crystalline p-type Ba0.5K0.5Fe2-2xM2xAs2 (M = Mn, Ru, Co, Ni, Cu and Zn) superconductors. Th…
Functional Outlier Detection and Taxonomy by Sequential Transformations
Wenlin Dai, Tomas Mrkvicka, Ying Sun +1
Functional data analysis can be seriously impaired by abnormal observations, which can be classified as either magnitude or shape outliers based on their way of deviating from the…
A stochastic space-time model for intermittent precipitation occurrences
Ying Sun, Michael L. Stein
Modeling a precipitation field is challenging due to its intermittent and highly scale-dependent nature. Motivated by the features of high-frequency precipitation data from a netwo…
Distributed Nonconvex Multiagent Optimization Over Time-Varying Networks
Ying Sun, Gesualdo Scutari, Daniel Palomar
We study nonconvex distributed optimization in multiagent networks where the communications between nodes is modeled as a time-varying sequence of arbitrary digraphs. We introduce…
Dealloying of Platinum-Aluminum Thin Films Part II. Electrode Performance
Thomas Ryll, Henning Galinski, Lukas Schlagenhauf +7
Highly porous Pt/Al thin film electrodes on yttria stabilized zirconia electrolytes were prepared by dealloying of co-sputtered Pt/Al films. The oxygen reduction capability of the…
Spatio-Temporal Trajectory Foundation Model - Recent Advances and Future Directions
Sean Bin Yang, Ying Sun, Yunyao Cheng +3
Foundation models (FMs) have emerged as a powerful paradigm, enabling a diverse range of data analytics and knowledge discovery tasks across scientific fields. Inspired by the succ…
Machine Learning Inspired Energy-Efficient Hybrid Precoding for MmWave Massive MIMO Systems
Xinyu Gao, Linglong Dai, Ying Sun +2
Hybrid precoding is a promising technique for mmWave massive MIMO systems, as it can considerably reduce the number of required radio-frequency (RF) chains without obvious performa…
Distributed Optimization Based on Gradient-tracking Revisited: Enhancing Convergence Rate via Surrogation
Ying Sun, Amir Daneshmand, Gesualdo Scutari
We study distributed multiagent optimization over (directed, time-varying) graphs. We consider the minimization of subject to convex constraints, where is the smooth stro…
Flow Matching-Based Active Learning for Radio Map Construction with Low-Altitude UAVs
Hao Sun, Shicong Liu, Xianghao Yu +1
The employment of unmanned aerial vehicles (UAVs) in the lowaltitude economy necessitates precise and real-time radio maps for reliable communication and safe navigation. However,…
RCOMPSs: A Scalable Runtime System for R Code Execution on Manycore Systems
Xiran Zhang, Javier Conejero, Sameh Abdulah +5
R has become a cornerstone of scientific and statistical computing due to its extensive package ecosystem, expressive syntax, and strong support for reproducible analysis. However,…
Risk-Aware Non-Myopic Motion Planner for Large-Scale Robotic Swarm Using CVaR Constraints
Xuru Yang, Yunze Hu, Han Gao +5
Swarm robotics has garnered significant attention due to its ability to accomplish elaborate and synchronized tasks. Existing methodologies for motion planning of swarm robotic sys…
Large-Scale Assessment of Labour Market Dynamics in China during the COVID-19 Pandemic
Ying Sun, Hengshu Zhu, Hui Xiong
The outbreak of the COVID-19 pandemic has had an unprecedented impact on China's labour market, and has largely changed the structure of labour supply and demand in different regio…
A Semi-Parametric Estimation Method for the Quantile Spectrum with an Application to Earthquake Classification Using Convolutional Neural Network
Tianbo Chen, Ying Sun, Ta-Hsin Li
In this paper, a new estimation method is introduced for the quantile spectrum, which uses a parametric form of the autoregressive (AR) spectrum coupled with nonparametric smoothin…
A Brain-inspired Embodied Intelligence for Fluid and Fast Reflexive Robotics Control
Weiyu Guo, He Zhang, Pengteng Li +7
Recent advances in embodied intelligence have leveraged massive scaling of data and model parameters to master natural-language command following and multi-task control. In contras…
Neural Networks for Tamed Milstein Approximation of SDEs with Additive Symmetric Jump Noise Driven by a Poisson Random Measure
Jose-Hermenegildo Ramirez-Gonzalez, Ying Sun
This work aims to estimate the drift and diffusion functions in stochastic differential equations (SDEs) driven by a particular class of Lévy processes with finite jump intensity,…
FashionSearchNet-v2: Learning Attribute Representations with Localization for Image Retrieval with Attribute Manipulation
Kenan E. Ak, Joo Hwee Lim, Ying Sun +2
The focus of this paper is on the problem of image retrieval with attribute manipulation. Our proposed work is able to manipulate the desired attributes of the query image while ma…
Collective Spectral Density Estimation and Clustering for Spatially-Correlated Data
Tianbo Chen, Ying Sun, Mehdi Maadooliat
In this paper, we develop a method for estimating and clustering two-dimensional spectral density functions (2D-SDFs) for spatial data from multiple subregions. We use a common set…
Chameleon: Control-Indexed Prospective Memory for Visuomotor Manipulation
Xinying Guo, Chenxi Jiang, Hyun Bin Kim +4
Robots often observe information that determines a future action long before that action is executed. In a shell game, for example, a robot first sees which cup hides the ball, wat…
Unlocking the Power of Orbital-Free Density Functional Theory to Explore the Electronic Structure Under Extreme Conditions
Cheng Ma, Qiang Xu, Zhenhao Zhang +8
Recent advances in X-ray free-electron laser diagnostics have enabled direct probing of the electronic structure under extreme pressures and temperatures, such as those encountered…
Zeta: Dual Whitening for Matrix Optimization via Coordinate-Adaptive Preconditioning
Kaiwen Chen, Shuhai Zhang, Zimo Liu +7
Large-scale neural network training increasingly relies on matrix-aware optimizers that exploit the structure of weight parameters beyond element-wise adaptation. However, existing…
Enhance the Safety in Reinforcement Learning by ADRC Lagrangian Methods
Mingxu Zhang, Huicheng Zhang, Jiaming Ji +2
Safe reinforcement learning (Safe RL) seeks to maximize rewards while satisfying safety constraints, typically addressed through Lagrangian-based methods. However, existing approac…
Boosting Earth System Model Outputs And Saving PetaBytes in their Storage Using Exascale Climate Emulators
Sameh Abdulah, Allison H. Baker, George Bosilca +9
We present the design and scalable implementation of an exascale climate emulator for addressing the escalating computational and storage requirements of high-resolution Earth Syst…
The Second Competition on Spatial Statistics for Large Datasets
Sameh Abdulah, Faten Alamri, Pratik Nag +4
In the last few decades, the size of spatial and spatio-temporal datasets in many research areas has rapidly increased with the development of data collection technologies. As a re…
6D Pose Estimation with Correlation Fusion
Yi Cheng, Hongyuan Zhu, Ying Sun +6
6D object pose estimation is widely applied in robotic tasks such as grasping and manipulation. Prior methods using RGB-only images are vulnerable to heavy occlusion and poor illum…
Achieving Linear Convergence in Distributed Asynchronous Multi-agent Optimization
Ye Tian, Ying Sun, Gesualdo Scutari
This papers studies multi-agent (convex and \emph{nonconvex}) optimization over static digraphs. We propose a general distributed \emph{asynchronous} algorithmic framework whereby…
Deep classifier kriging for probabilistic spatial prediction of air quality index
Junyu Chen, Pratik Nag, Huixia Judy-Wang +1
Accurate spatial interpolation of the air quality index (AQI), computed from concentrations of multiple air pollutants, is essential for regulatory decision-making, yet AQI fields…
Plan-on-Graph: Self-Correcting Adaptive Planning of Large Language Model on Knowledge Graphs
Liyi Chen, Panrong Tong, Zhongming Jin +3
Large Language Models (LLMs) have shown remarkable reasoning capabilities on complex tasks, but they still suffer from out-of-date knowledge, hallucinations, and opaque decision-ma…
Data-driven design of high-temperature superconductivity among ternary hydrides under pressure
Bowen Jiang, Xiaoshan Luo, Toshiaki Iitaka +6
Recently, ternary clathrate hydrides are promising candidates for high-temperature superconductor. However, it is a formidable challenge to effectively hunt high-temperature superc…
High Performance Multivariate Geospatial Statistics on Manycore Systems
Mary Lai O. Salvaña, Sameh Abdulah, Huang Huang +4
Modeling and inferring spatial relationships and predicting missing values of environmental data are some of the main tasks of geospatial statisticians. These routine tasks are acc…
Distributed Algorithms for Composite Optimization: Unified Framework and Convergence Analysis
Jinming Xu, Ye Tian, Ying Sun +1
We study distributed composite optimization over networks: agents minimize a sum of smooth (strongly) convex functions, the agents' sum-utility, plus a nonsmooth (extended-valued)…
Loud-loss: A Perceptually Motivated Loss Function for Speech Enhancement Based on Equal-Loudness Contours
Zixuan Li, Xueliang Zhang, Changjiang Zhao +5
The mean squared error (MSE) is a ubiquitous loss function for speech enhancement, but its problem is that the error cannot reflect the auditory perception quality. This is because…
Monitoring Vegetation From Space at Extremely Fine Resolutions via Coarsely-Supervised Smooth U-Net
Joshua Fan, Di Chen, Jiaming Wen +2
Monitoring vegetation productivity at extremely fine resolutions is valuable for real-world agricultural applications, such as detecting crop stress and providing early warning of…
A Comprehensive Survey on Self-Interpretable Neural Networks
Yang Ji, Ying Sun, Yuting Zhang +7
Neural networks have achieved remarkable success across various fields. However, the lack of interpretability limits their practical use, particularly in critical decision-making s…
Attribution of extreme rainfall in Southeast China during May 2015
Claire Burke, Peter Stott, Ying Sun +1
Anthropogenic climate change increased the probability that a short-duration, intense rainfall event would occur in parts of southeast China. This type of event occurred in May 201…
Source-Lifted Flow Matching for Intervenable Multimodal Imitation
He Zhang, Ying Sun, Pengteng Li +6
Flow-matching policies are promising for imitation learning because they model complex multimodal action distributions. However, their stochasticity is largely passive: repeated sa…
Modeling nonstationary spatial processes with normalizing flows
Pratik Nag, Andrew Zammit-Mangion, Ying Sun
Nonstationary spatial processes can often be represented as stationary processes on a warped spatial domain. Selecting an appropriate spatial warping function for a given applicati…
A Multi-Site Stochastic Weather Generator for High-Frequency Precipitation Using Censored Skew-Symmetric Distribution
Yuxiao Li, Ying Sun
Stochastic weather generators (SWGs) are digital twins of complex weather processes and widely used in agriculture and urban design. Due to improved measuring instruments, an accur…
Amortized Neural Clustering of Time Series based on Statistical Features
Ãngel López-Oriona, Ying Sun
This paper introduces an algorithm-agnostic approach to feature-based time series clustering via amortized neural inference. By training neural networks to approximate the optimal…
LLMs Can Simulate Standardized Patients via Agent Coevolution
Zhuoyun Du, Lujie Zheng, Renjun Hu +7
Training medical personnel using standardized patients (SPs) remains a complex challenge, requiring extensive domain expertise and role-specific practice. Previous research on Larg…
Semiparametric Estimation of Cross-covariance Functions for Multivariate Random Fields
Ghulam A. Qadir, Ying Sun
The prevalence of spatially referenced multivariate data has impelled researchers to develop a procedure for the joint modeling of multiple spatial processes. This ordinarily invol…
MCLMR: A Model-Agnostic Causal Learning Framework for Multi-Behavior Recommendation
Ranxu Zhang, Junjie Meng, Ying Sun +5
Multi-Behavior Recommendation (MBR) leverages multiple user interaction types (e.g., views, clicks, purchases) to enrich preference modeling and alleviate data sparsity issues in t…
Enhancing LLM-based Recommendation with Preference Hint Discovery from Knowledge Graph
Yuting Zhang, Ziliang Pei, Chao Wang +2
LLMs have garnered substantial attention in recommendation systems. Yet they fall short of traditional recommenders when capturing complex preference patterns. Recent works have tr…
Decentralized Inference for Spatial Data Using Low-Rank Models
Jianwei Shi, Sameh Abdulah, Ying Sun +1
Advancements in information technology have enabled the creation of massive spatial datasets, driving the need for scalable and efficient computational methodologies. While offerin…