Faculty

Institution

Unit

Venue

Alessandro Rinaldo

Professor

Carnegie Mellon University

Affiliations

Dietrich College of Humanities and Social Sciences

Statistics & Data Science

School of Computer Science

Machine Learning

Alessandro Rinaldo is currently serving as a Dietrich College Of Humanities And Social Sciences Professor at Carnegie Mellon University.

Honors

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Experiences

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Education

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Alessandro Rinaldo

Carnegie Mellon University

Professor

You can click a keyword to filter the displayed items

statistics applied mathematics data science computer science statistical inference statistical methodology machine learning graph theory applied statistics computational statistics estimation theory topology machine learning research computational intelligence topological data analysis artificial intelligence localization mathematical optimization random graphs high-dimensional method geometric topology machine intelligence econometrics network theory maximum likelihood estimation bibliometrics change detection localization technique algebraic statistics probabilistic graph theory log-linear models multi-armed bandits sparse representations persistence diagrams persistent homology spectral theory decision science differential privacy anomaly detection neuroinformatics graph analysis information theory optimal rates confidence sets asymptotic properties fused lasso control optimization scientific computing manifold modeling manifold learning statistical signal processing outlier detection bootstrap resampling regression analysis spectral clustering functional data nearest neighbor methods homology inference minimax rates berry-esseen bounds data security information technology blockchain computational optimization computational imaging linkage disequilibrium reachability analysis mathematical statistics riemannian manifold symbolic computation graph processing distributed artificial intelligence edge intelligence stability analysis network analytics transaction processing high-dimensional data knowledge discovery optimization-based data mining data classification granular computing data mining data modeling reinforcement learning

Notable Scholarly Works

Notable Federal Grants

Collaborators

Fan Wang, Yi Yu and Alessandro Rinaldo's Contribution to the Discussion of ‘Root and Community Inference on the Latent Growth Process of a Network’ by Crane and Xu. Journal of the Royal Statistical Society Series B (Statistical Methodology) (2024)

Fan WangYi YuAlessandro Rinaldo

network sciencestatisticsstatistical methodologybiostatisticscommunity inferencelatent growth processdata sciencestatistical science

High-Probability Sample Complexities for Policy Evaluation With Linear Function Approximation. IEEE Transactions on Information Theory (2024)

Gen LiWeichen WuYuejie ChiCong MaAlessandro RinaldoYuting Wei

computer sciencestatisticshigh-probability sample complexitiesdata sciencelinear function approximationpolicy evaluationinformation theoryinformation science

Network Online Change Point Localization. SIAM Journal on Mathematics of Data Science (2024)

Yi YuOscar H. Madrid PadillaDaren WangAlessandro Rinaldo

network sciencecomputer sciencedata scienceinformaticslocalizationpositioning systemsnavigationapplied mathematics

A Note on Online Change Point Detection. Sequential Analysis (2023)

Yi YuOscar Hernan Madrid PadillaDaren WangAlessandro Rinaldo

computer sciencestatisticshealth sciencesmachine learningcomputer visionsequential learningprogram analysisanalyticssequence analysis

Divide and Conquer Dynamic Programming: An Almost Linear Time Change Point Detection Methodology in High Dimensions. arXiv (Cornell University) (2023)

Li, WanshanWang, DarenRinaldo, Alessandro

computer sciencedynamic programminghigh dimensions

E-Detectors: A Nonparametric Framework for Sequential Change Detection. The New England Journal of Statistics in Data Science (2023)

Jaehyeok ShinAaditya RamdasAlessandro Rinaldo

statisticshealth sciencesstatistical methodologymachine learningsequential change detectiondata sciencecomputer visionnonparametric frameworkapplied statistics

Multilayer Random Dot Product Graphs: Estimation and Online Change Point Detection. arXiv (Cornell University) (2023)

Wang, FanLi, WanshanPadilla, Oscar Hernan MadridYu, YiRinaldo, Alessandro

graph theoryapplied mathematics

Detecting Abrupt Changes in Sequential Pairwise Comparison Data. arXiv (Cornell University) (2022)

Li, WanshanWang, DarenRinaldo, Alessandro

change detectiontime seriesabrupt changesdata science

Mitigating Multiple Descents: A Model-Agnostic Framework for Risk Monotonization. arXiv (Cornell University) (2022)

Patil, PratikKuchibhotla, Arun KumarWei, YutingRinaldo, Alessandro

machine learningmitigation techniquesmultiple descentsdata sciencedecision theoryrisk monotonizationmitigation technologymodel-agnostic framework

Denoising and Change Point Localisation in Piecewise-Constant High-Dimensional Regression Coefficients. arXiv (Cornell University) (2021)

Fan WangOscar Hernan Madrid PadillaYi YuAlessandro Rinaldo

high-dimensional statisticsmachine learningchange point localisationimage denoisingapplied mathematics

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Alessandro Rinaldo

Professor

Carnegie Mellon University

Affiliations

Dietrich College of Humanities and Social Sciences

Statistics & Data Science

School of Computer Science

Machine Learning

Alessandro Rinaldo is currently serving as a Dietrich College Of Humanities And Social Sciences Professor at Carnegie Mellon University.

Honors

Create free account to unlock more features

Experiences

Create free account to unlock more features

Education

Create free account to unlock more features

Alessandro Rinaldo

Carnegie Mellon University

Professor

You can click a keyword to filter the displayed items

Notable Scholarly Works

Notable Federal Grants

Collaborators

Fan WangYi YuAlessandro Rinaldo

network sciencestatisticsstatistical methodologybiostatisticscommunity inferencelatent growth processdata sciencestatistical science

High-Probability Sample Complexities for Policy Evaluation With Linear Function Approximation. IEEE Transactions on Information Theory (2024)

Gen LiWeichen WuYuejie ChiCong MaAlessandro RinaldoYuting Wei

computer sciencestatisticshigh-probability sample complexitiesdata sciencelinear function approximationpolicy evaluationinformation theoryinformation science

Network Online Change Point Localization. SIAM Journal on Mathematics of Data Science (2024)

Yi YuOscar H. Madrid PadillaDaren WangAlessandro Rinaldo

network sciencecomputer sciencedata scienceinformaticslocalizationpositioning systemsnavigationapplied mathematics

A Note on Online Change Point Detection. Sequential Analysis (2023)

Yi YuOscar Hernan Madrid PadillaDaren WangAlessandro Rinaldo

computer sciencestatisticshealth sciencesmachine learningcomputer visionsequential learningprogram analysisanalyticssequence analysis

Divide and Conquer Dynamic Programming: An Almost Linear Time Change Point Detection Methodology in High Dimensions. arXiv (Cornell University) (2023)

Li, WanshanWang, DarenRinaldo, Alessandro

computer sciencedynamic programminghigh dimensions

E-Detectors: A Nonparametric Framework for Sequential Change Detection. The New England Journal of Statistics in Data Science (2023)

Jaehyeok ShinAaditya RamdasAlessandro Rinaldo

statisticshealth sciencesstatistical methodologymachine learningsequential change detectiondata sciencecomputer visionnonparametric frameworkapplied statistics

Multilayer Random Dot Product Graphs: Estimation and Online Change Point Detection. arXiv (Cornell University) (2023)

Wang, FanLi, WanshanPadilla, Oscar Hernan MadridYu, YiRinaldo, Alessandro

graph theoryapplied mathematics

Detecting Abrupt Changes in Sequential Pairwise Comparison Data. arXiv (Cornell University) (2022)

Li, WanshanWang, DarenRinaldo, Alessandro

change detectiontime seriesabrupt changesdata science

Mitigating Multiple Descents: A Model-Agnostic Framework for Risk Monotonization. arXiv (Cornell University) (2022)

Patil, PratikKuchibhotla, Arun KumarWei, YutingRinaldo, Alessandro

machine learningmitigation techniquesmultiple descentsdata sciencedecision theoryrisk monotonizationmitigation technologymodel-agnostic framework

Denoising and Change Point Localisation in Piecewise-Constant High-Dimensional Regression Coefficients. arXiv (Cornell University) (2021)

Fan WangOscar Hernan Madrid PadillaYi YuAlessandro Rinaldo

high-dimensional statisticsmachine learningchange point localisationimage denoisingapplied mathematics

1
2
3
4
5
20
10 / page

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