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Content
January 2025, Volume 4, Issue 1
- 1-19 Rethinking Cost-Sensitive Classification in Deep Learning via Adversarial Data Augmentation
by Qiyuan Chen & Raed Al Kontar & Maher Nouiehed & X. Jessie Yang & Corey Lester - 20-32 Spatio-Temporal Time Series Forecasting Using an Iterative Kernel-Based Regression
by Ben Hen & Neta Rabin - 33-50 Low-Rank Robust Subspace Tensor Clustering for Metro Passenger Flow Modeling
by Nurretin Dorukhan Sergin & Jiuyun Hu & Ziyue Li & Chen Zhang & Fugee Tsung & Hao Yan - 51-66 Hierarchical Multilabel Classification for Fine-Level Event Extraction from Aviation Accident Reports
by Xinyu Zhao & Hao Yan & Yongming Liu - 67-84 Fair Collaborative Learning (FairCL): A Method to Improve Fairness amid Personalization
by Feng Lin & Chaoyue Zhao & Xiaoning Qian & Kendra Vehik & Shuai Huang - 85-99 A Reduced Modeling Approach for Making Predictions with Incomplete Data Having Blockwise Missing Patterns
by Karthik Srinivasan & Faiz Currim & Sudha Ram
October 2024, Volume 3, Issue 2
- 105-123 Registration-Free Localization of Defects in Three-Dimensional Parts from Mesh Metrology Data Using Functional Maps
by Xueqi Zhao & Enrique del Castillo - 124-144 An Optimization-Based Order-and-Cut Approach for Fair Clustering of Data Sets
by Su Li & Hrayer Aprahamian & Maher Nouiehed & Hadi El-Amine - 145-161 Thompson Sampling-Based Partially Observable Online Change Detection for Exponential Families
by Jie Guo & Hao Yan & Chen Zhang - 162-178 A Statistical Model for Multisource Remote-Sensing Data Streams of Wildfire Aerosol Optical Depth
by Guanzhou Wei & Venkat Krishnan & Yu Xie & Manajit Sengupta & Yingchen Zhang & Haitao Liao & Xiao Liu - 179-202 Conjecturing-Based Discovery of Patterns in Data
by J. Paul Brooks & David J. Edwards & Craig E. Larson & Nico Van Cleemput - 203-218 Multivariate Functional Clustering with Variable Selection and Application to Sensor Data from Engineering Systems
by Zhongnan Jin & Jie Min & Yili Hong & Pang Du & Qingyu Yang
April 2024, Volume 3, Issue 1
- 1-5 Chronicles of a New Journal: Reflections by the Inaugural Editor-in-Chief
by Galit Shmueli - 6-27 The Interplay Between Individual Mobility, Health Risk, and Economic Choice: A Holistic Model for COVID-19 Policy Intervention
by Zihao Yang & Ramayya Krishnan & Beibei Li - 28-48 Sparse Density Trees and Lists: An Interpretable Alternative to High-Dimensional Histograms
by Siong Thye Goh & Lesia Semenova & Cynthia Rudin - 49-67 Cost Patterns of Multiple Chronic Conditions: A Novel Modeling Approach Using a Condition Hierarchy
by Lida Anna Apergi & Margrét Vilborg Bjarnadóttir & John S. Baras & Bruce L. Golden - 68-83 Adaptive Exploration and Optimization of Materials Crystal Structures
by Arvind Krishna & Huan Tran & Chaofan Huang & Rampi Ramprasad & V. Roshan Joseph - 84-104 A Supervised Tensor Dimension Reduction-Based Prognostic Model for Applications with Incomplete Imaging Data
by Chengyu Zhou & Xiaolei Fang
October 2023, Volume 2, Issue 2
- 99-115 A Nonparametric Subspace Analysis Approach with Application to Anomaly Detection Ensembles
by Irad Ben-Gal & Marcelo Bacher & Morris Amara & Erez Shmueli - 116-137 Multiblock Parameter Calibration in Computer Models
by Cheoljoon Jeong & Ziang Xu & Albert S. Berahas & Eunshin Byon & Kristen Cetin - 138-160 Modeling Financial Products and Their Supply Chains
by Margrét Vilborg Bjarnadóttir & Louiqa Raschid - 161-182 Diversity Subsampling: Custom Subsamples from Large Data Sets
by Boyang Shang & Daniel W. Apley & Sanjay Mehrotra - 183-196 Interpretable Hierarchical Deep Learning Model for Noninvasive Alzheimer’s Disease Diagnosis
by Maryam Zokaeinikoo & Pooyan Kazemian & Prasenjit Mitra - 197-217 Credit Risk Modeling with Graph Machine Learning
by Sanjiv Das & Xin Huang & Soji Adeshina & Patrick Yang & Leonardo Bachega
April 2023, Volume 2, Issue 1
- 1-9 How Can IJDS Authors, Reviewers, and Editors Use (and Misuse) Generative AI?
by Galit Shmueli & Bianca Maria Colosimo & David Martens & Rema Padman & Maytal Saar-Tsechansky & Olivia R. Liu Sheng & W. Nick Street & Kwok-Leung Tsui - 10-23 GIFAIR-FL: A Framework for Group and Individual Fairness in Federated Learning
by Xubo Yue & Maher Nouiehed & Raed Al Kontar - 45-59 Sequential Adversarial Anomaly Detection for One-Class Event Data
by Shixiang Zhu & Henry Shaowu Yuchi & Minghe Zhang & Yao Xie - 60-80 Compressed Smooth Sparse Decomposition
by Shancong Mou & Jianjun Shi - 81-98 Covariate Dependent Sparse Functional Data Analysis
by Minhee Kim & Todd Allen & Kaibo Liu
October 2022, Volume 1, Issue 2
- 115-137 Weakly Supervised Multi-output Regression via Correlated Gaussian Processes
by Seokhyun Chung & Raed Al Kontar & Zhenke Wu - 138-155 Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem
by Mochen Yang & Edward McFowland & Gordon Burtch & Gediminas Adomavicius - 156-171 A Robust Approach to Quantifying Uncertainty in Matching Problems of Causal Inference
by Marco Morucci & Md. Noor-E-Alam & Cynthia Rudin - 172-187 Visualization in Operations Management Research
by Rahul Basole & Elliot Bendoly & Aravind Chandrasekaran & Kevin Linderman - 188-191 Commentary on “Visualization in Operations Management Research”: Incorporating Statistical Thinking into Visualization Practices for Decision Making in Operational Management
by Emi Tanaka & Jessica Wai Yin Leung & Dianne Cook - 192-193 Commentary on “Visualization in Operations Management Research”
by Ben Shneiderman - 194-195 Commentary on “Visualization in Operations Management Research”
by Ran Jin
April 2022, Volume 1, Issue 1
- 1-3 Congratulations, It’s Our Inaugural Issue!
by Galit Shmueli - 4-16 Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters
by Carlos Fernández-Loría & Foster Provost - 17-18 Commentary on “Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters”: On Loss Functions and Bias–Variance Tradeoffs in Causal Estimation and Decisions
by Dean Eckles - 19-20 Commentary on “Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters”
by Uri Shalit - 21-22 Commentary on “Causal Decision Making and Causal Effect Estimation Are Not the Same… and Why It Matters”
by Edward McFowland - 23-26 Rejoinder to “Causal Decision Making and Causal Effect Estimation Are Not the Same…and Why It Matters”
by Carlos Fernández-Loría & Foster Provost - 27-49 Adapting Reinforcement Learning Treatment Policies Using Limited Data to Personalize Critical Care
by Matt Baucum & Anahita Khojandi & Rama Vasudevan & Robert Davis - 50-62 STR: Seasonal-Trend Decomposition Using Regression
by Alexander Dokumentov & Rob J. Hyndman - 63-80 Constructing Prediction Intervals Using the Likelihood Ratio Statistic
by Qinglong Tian & Daniel J. Nordman & William Q. Meeker - 81-95 HeBERT and HebEMO: A Hebrew BERT Model and a Tool for Polarity Analysis and Emotion Recognition
by Avihay Chriqui & Inbal Yahav - 96-113 The Future of Forecasting Competitions: Design Attributes and Principles
by Spyros Makridakis & Chris Fry & Fotios Petropoulos & Evangelos Spiliotis