Statistics

Authors and titles for July 2019

[101] arXiv:1907.02829 [pdf, other]

Title: Risk models for breast cancer and their validation

Adam R Brentnall, Jack Cuzick

Journal-ref: Statist. Sci., Volume 35, Number 1 (2020), 14-30

Subjects: Applications (stat.AP); Methodology (stat.ME)

[102] arXiv:1907.02844 [pdf, other]

Title: Geodesic Learning via Unsupervised Decision Forests

Meghana Madhyastha, Percy Li, James Browne, Veronika Strnadova-Neeley, Carey E. Priebe, Randal Burns, Joshua T. Vogelstein

Subjects: Machine Learning (stat.ML); Information Retrieval (cs.IR); Machine Learning (cs.LG); Methodology (stat.ME)

[103] arXiv:1907.02893 [pdf, other]

Title: Invariant Risk Minimization

Martin Arjovsky, Léon Bottou, Ishaan Gulrajani, David Lopez-Paz

Subjects: Machine Learning (stat.ML); Artificial Intelligence (cs.AI); Machine Learning (cs.LG)

[104] arXiv:1907.02907 [pdf, other]

Title: Hybridized Threshold Clustering for Massive Data

Jianmei Luo, ChandraVyas Annakula, Aruna Sai Kannamareddy, Jasjeet S. Sekhon, William Henry Hsu, Michael Higgins

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[105] arXiv:1907.02912 [pdf, other]

Title: On Finite Exchangeability and Conditional Independence

Kayvan Sadeghi

Comments: 25 pages, 2 figures

Subjects: Statistics Theory (math.ST); Probability (math.PR); Other Statistics (stat.OT)

[106] arXiv:1907.02936 [pdf, other]

Title: Learning in Volatile Environments with the Bayes Factor Surprise

Vasiliki Liakoni, Alireza Modirshanechi, Wulfram Gerstner, Johanni Brea

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Neurons and Cognition (q-bio.NC); Applications (stat.AP)

[107] arXiv:1907.03025 [pdf, other]

Title: Improving Lasso for model selection and prediction

Piotr Pokarowski, Wojciech Rejchel, Agnieszka Soltys, Michal Frej, Jan Mielniczuk

Subjects: Statistics Theory (math.ST); Methodology (stat.ME)

[108] arXiv:1907.03028 [pdf, other]

Title: On Inferences from Completed Data

Jamie Haddock, Denali Molitor, Deanna Needell, Sneha Sambandam, Joy Song, Simon Sun

Subjects: Statistics Theory (math.ST)

[109] arXiv:1907.03087 [pdf, other]

Title: Estimating location parameters in entangled single-sample distributions

Ankit Pensia, Varun Jog, Po-Ling Loh

Subjects: Statistics Theory (math.ST); Information Theory (cs.IT); Machine Learning (cs.LG); Machine Learning (stat.ML)

[110] arXiv:1907.03119 [pdf, other]

Title: Investigating some attributes of periodicity in DNA sequences via semi-Markov modelling

Pavlos Kolias, Alexandra Papadopoulou

Subjects: Applications (stat.AP); Other Quantitative Biology (q-bio.OT)

[111] arXiv:1907.03153 [pdf, other]

Title: The revisited knockoffs method for variable selection in L1-penalised regressions

Anne Gégout-Petit, Aurélie Gueudin-Muller, Clémence Karmann

Comments: arXiv admin note: text overlap with arXiv:1805.10097

Subjects: Methodology (stat.ME); Applications (stat.AP)

[112] arXiv:1907.03155 [pdf, other]

Title: Learning a latent pattern of heterogeneity in the innovation rates of a time series of counts

Helton Graziadei, Hedibert F. Lopes, Paulo C. Marques F

Subjects: Methodology (stat.ME)

[113] arXiv:1907.03170 [pdf, other]

Title: Convergence Analysis of a Collapsed Gibbs Sampler for Bayesian Vector Autoregressions

Karl Oskar Ekvall, Galin L. Jones

Subjects: Statistics Theory (math.ST)

[114] arXiv:1907.03178 [pdf, other]

Title: XGBoostLSS -- An extension of XGBoost to probabilistic forecasting

Alexander März

Comments: Bayesian Optimization; Distributional Modeling; Expectile Regression; GAMLSS; Probabilistic Forecast; Uncertainty Quantification; XGBoost

Subjects: Machine Learning (stat.ML); Artificial Intelligence (cs.AI); Machine Learning (cs.LG); Methodology (stat.ME)

[115] arXiv:1907.03186 [pdf, other]

Title: Bayesian Nonparametric Nonhomogeneous Poisson Process with Applications to USGS Earthquake Data

Junxian Geng, Wei Shi, Guanyu Hu

Subjects: Methodology (stat.ME); Applications (stat.AP)

[116] arXiv:1907.03190 [pdf, other]

Title: Testing Mixtures of Discrete Distributions

Maryam Aliakbarpour, Ravi Kumar, Ronitt Rubinfeld

Comments: Appeared in COLT 2019

Subjects: Statistics Theory (math.ST); Data Structures and Algorithms (cs.DS); Machine Learning (stat.ML)

[117] arXiv:1907.03206 [pdf, other]

Title: Filaments of crime: Informing policing via thresholded ridge estimation

Ben Moews, Jaime R. Argueta Jr., Antonia Gieschen

Comments: 16 pages, 4 figures, accepted for publication in Decision Support Systems

Subjects: Applications (stat.AP); Computers and Society (cs.CY); Computation (stat.CO)

[118] arXiv:1907.03385 [pdf, other]

Title: Modeling Symmetric Positive Definite Matrices with An Application to Functional Brain Connectivity

Zhenhua Lin, Dehan Kong, Qiang Sun

Comments: 17 pages

Subjects: Methodology (stat.ME)

[119] arXiv:1907.03411 [pdf, other]

Title: Unbiased estimators for random design regression

Michał Dereziński, Manfred K. Warmuth, Daniel Hsu

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[120] arXiv:1907.03555 [pdf, other]

Title: Causal mechanism of extreme river discharges in the upper Danube basin network

Linda Mhalla, Valérie Chavez-Demoulin, Debbie J. Dupuis

Subjects: Applications (stat.AP)

[121] arXiv:1907.03625 [pdf, other]

Title: Arbitrary functional Glivenko-Cantelli classes and applications to different types of dependence

Harouna Sangaré, Gane Samb Lo, Mamadou Cherif Moctar Traoré

Subjects: Statistics Theory (math.ST)

[122] arXiv:1907.03682 [pdf, other]

Title: A Versatile Estimation Procedure without Estimating the Nonignorable Missingness Mechanism

Jiwei Zhao, Yanyuan Ma

Subjects: Methodology (stat.ME)

[123] arXiv:1907.03807 [pdf, other]

Title: Aggregating Knockoffs for False Discovery Rate Control with an Application to Gut Microbiome Data

Fang Xie, Johannes Lederer

Journal-ref: Entropy 23(2021) 230

Subjects: Methodology (stat.ME); Quantitative Methods (q-bio.QM); Applications (stat.AP)

[124] arXiv:1907.03808 [pdf, other]

Title: False Discovery Rates in Biological Networks

Lu Yu, Tobias Kaufmann, Johannes Lederer

Subjects: Methodology (stat.ME); Quantitative Methods (q-bio.QM); Applications (stat.AP)

[125] arXiv:1907.03813 [pdf, other]

Title: Statistical Analysis of Nearest Neighbor Methods for Anomaly Detection

Xiaoyi Gu, Leman Akoglu, Alessandro Rinaldo

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Statistics Theory (math.ST)

[126] arXiv:1907.03814 [pdf, other]

Title: Road Maintenance Operation Start Time Optimization Based on Real-time Traffic Map Data

Zhepu Xu, Qun Yang

Comments: 14 pages, in Chinese, 12 figures, 7 tables

Subjects: Applications (stat.AP)

[127] arXiv:1907.03888 [pdf, other]

Title: Residual Entropy

Barnaby Rowe

Comments: 10 pages, 5 figures, updated to v2 with minor edits following feedback; code used to generate all figures available at this https URL

Subjects: Methodology (stat.ME); Statistics Theory (math.ST)

[128] arXiv:1907.03933 [pdf, other]

Title: Surrogate modeling of indoor down-link human exposure based on sparse polynomial chaos expansion

Zicheng Liu, Dominique Lesselier, Bruno Sudret, Joe Wiart

Subjects: Applications (stat.AP)

[129] arXiv:1907.03947 [pdf, other]

Title: Understanding Player Engagement and In-Game Purchasing Behavior with Ensemble Learning

Anna Guitart, Ana Fernández del Río, África Periáñez

Comments: Churn Prediction, Ensemble Methods, Survival Analysis, On- line Games, User Behavior

Journal-ref: Proceedings of GAME-ON'2019 AI and Simulation in Games, September 2019, breda, the Netherlands. ISBN 978-94-92859-08-2

Subjects: Machine Learning (stat.ML); Artificial Intelligence (cs.AI); Machine Learning (cs.LG)

[130] arXiv:1907.03989 [pdf, other]

Title: All Sparse PCA Models Are Wrong, But Some Are Useful. Part I: Computation of Scores, Residuals and Explained Variance

J. Camacho, A.K. Smilde, E. Saccenti, J.A. Westerhuis

Journal-ref: Chemometrics and Intelligent Laboratory Systems, 2020, 196: 1039072-

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[131] arXiv:1907.04004 [pdf, other]

Title: Incremental Intervention Effects in Studies with Dropout and Many Timepoints

Kwangho Kim, Edward H. Kennedy, Ashley I. Naimi

Comments: 52 pages

Journal-ref: Journal of Causal Inference, vol. 9, no. 1, 2021, pp. 302-344

Subjects: Methodology (stat.ME); Machine Learning (stat.ML)

[132] arXiv:1907.04027 [pdf, other]

Title: Iteratively Reweighted $\ell_1$-Penalized Robust Regression

Xiaoou Pan, Qiang Sun, Wen-Xin Zhou

Comments: 62 pages

Subjects: Statistics Theory (math.ST); Machine Learning (stat.ML)

[133] arXiv:1907.04044 [pdf, other]

Title: Optimal experimental designs for treatment contrasts in heteroscedastic models with covariates

Samuel Rosa

Comments: 21 pages, 2 figures, 7 tables

Subjects: Statistics Theory (math.ST)

[134] arXiv:1907.04050 [pdf, other]

Title: k-GANs: Ensemble of Generative Models with Semi-Discrete Optimal Transport

Luca Ambrogioni, Umut Güçlü, Marcel van Gerven

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[135] arXiv:1907.04059 [pdf, other]

Title: The Integrated Nested Laplace Approximation for fitting Dirichlet regression models

Joaquín Martínez-Minaya, Finn Lindgren, Antonio López-Quílez, Daniel Simpson, David Conesa

Journal-ref: Journal of Computational and Graphical Statistics (2023)

Subjects: Computation (stat.CO); Methodology (stat.ME)

[136] arXiv:1907.04068 [pdf, other]

Title: Conditional Independence Testing using Generative Adversarial Networks

Alexis Bellot, Mihaela van der Schaar

Comments: Updated version published at NeurIPS 2019

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[137] arXiv:1907.04078 [pdf, other]

Title: How to design a pre-specified statistical analysis approach to limit p-hacking in clinical trials: the Pre-SPEC framework

Brennan C Kahan, Gordon Forbes, Suzie Cro

Comments: 26 pages, 3 tables, 0 figures

Subjects: Methodology (stat.ME)

[138] arXiv:1907.04081 [pdf, other]

Title: Kernel Hypothesis Testing with Set-valued Data

Alexis Bellot, Mihaela van der Schaar

Subjects: Methodology (stat.ME); Machine Learning (stat.ML)

[139] arXiv:1907.04147 [pdf, other]

Title: Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model

Feiyu Jiang, Dong Li, Ke Zhu

Subjects: Methodology (stat.ME); Econometrics (econ.EM)

[140] arXiv:1907.04148 [pdf, other]

Title: Multiple membership multilevel models

George Leckie

Comments: arXiv admin note: substantial text overlap with arXiv:1907.02569

Subjects: Methodology (stat.ME); Applications (stat.AP)

[141] arXiv:1907.04155 [pdf, other]

Title: GP-VAE: Deep Probabilistic Time Series Imputation

Vincent Fortuin, Dmitry Baranchuk, Gunnar Rätsch, Stephan Mandt

Comments: Accepted for publication at the 23rd International Conference on Artificial Intelligence and Statistics (AISTATS 2020)

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[142] arXiv:1907.04185 [pdf, other]

Title: Predictively Consistent Prior Effective Sample Sizes

Beat Neuenschwander, Sebastian Weber, Heinz Schmidli, Anthony O'Hagan

Comments: 19 pages, 1 figure

Subjects: Applications (stat.AP)

[143] arXiv:1907.04223 [pdf, other]

Title: Characterizing Inter-Layer Functional Mappings of Deep Learning Models

Donald Waagen, Katie Rainey, Jamie Gantert, David Gray, Megan King, M. Shane Thompson, Jonathan Barton, Will Waldron, Samantha Livingston, Don Hulsey

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG)

[144] arXiv:1907.04240 [pdf, other]

Title: Bayesian deep learning with hierarchical prior: Predictions from limited and noisy data

Xihaier Luo, Ahsan Kareem

Comments: 33 pages, 11 figures

Journal-ref: Structural Safety, 84, p.101918 (2020)

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Signal Processing (eess.SP); Computational Physics (physics.comp-ph)

[145] arXiv:1907.04242 [pdf, other]

Title: Topological Information Data Analysis

Pierre Baudot, Monica Tapia, Daniel Bennequin, Jean-Marc Goaillard

Subjects: Other Statistics (stat.OT); Information Theory (cs.IT); Neurons and Cognition (q-bio.NC)

[146] arXiv:1907.04266 [pdf, other]

Title: Identifying the Influential Inputs for Network Output Variance Using Sparse Polynomial Chaos Expansion

Zhanlin Liu, Ashis G. Banerjee, Youngjun Choe

Subjects: Methodology (stat.ME)

[147] arXiv:1907.04303 [pdf, other]

Title: A Bayesian Approach for Analyzing Data on the Stiefel Manifold

Subhadip Pal, Subhajit Sengupta, Riten Mitra, Arunava Banerjee

Subjects: Statistics Theory (math.ST)

[148] arXiv:1907.04371 [pdf, other]

Title: Ordered SGD: A New Stochastic Optimization Framework for Empirical Risk Minimization

Kenji Kawaguchi, Haihao Lu

Comments: Accepted in AISTATS 2020. Code available at: this https URL

Subjects: Machine Learning (stat.ML); Machine Learning (cs.LG); Optimization and Control (math.OC)

[149] arXiv:1907.04377 [pdf, other]

Title: Convergence Rates for Gaussian Mixtures of Experts

Nhat Ho, Chiao-Yu Yang, Michael I. Jordan

Comments: 81 pages

Subjects: Statistics Theory (math.ST); Machine Learning (cs.LG); Machine Learning (stat.ML)

[150] arXiv:1907.04481 [pdf, other]

Title: Tails of Lipschitz Triangular Flows

Priyank Jaini, Ivan Kobyzev, Yaoliang Yu, Marcus Brubaker

Comments: Published at the 37th International Conference of Machine Learning, (ICML 2020)

Subjects: Statistics Theory (math.ST); Machine Learning (cs.LG); Machine Learning (stat.ML)