Daniel Hsu

Daniel Hsu

Columbia University in the City of New York

H-index: 51

North America-United States

About Daniel Hsu

Daniel Hsu, With an exceptional h-index of 51 and a recent h-index of 43 (since 2020), a distinguished researcher at Columbia University in the City of New York, specializes in the field of Algorithmic statistics, machine learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Multi-group Learning for Hierarchical Groups

Statistical-computational trade-offs in tensor pca and related problems via communication complexity

Polynomial time auditing of statistical subgroup fairness for Gaussian data

Algorithmic Learning Theory 2024: Preface

Transformers, parallel computation, and logarithmic depth

Representational strengths and limitations of transformers

On the sample complexity of estimation in logistic regression

Group conditional validity via multi-group learning

Daniel Hsu Information

University

Position

___

Citations(all)

14923

Citations(since 2020)

9665

Cited By

9147

hIndex(all)

51

hIndex(since 2020)

43

i10Index(all)

95

i10Index(since 2020)

88

Email

University Profile Page

Columbia University in the City of New York

Google Scholar

View Google Scholar Profile

Daniel Hsu Skills & Research Interests

Algorithmic statistics

machine learning

Top articles of Daniel Hsu

Title

Journal

Author(s)

Publication Date

Multi-group Learning for Hierarchical Groups

arXiv preprint arXiv:2402.00258

Samuel Deng

Daniel Hsu

2024/2/1

Statistical-computational trade-offs in tensor pca and related problems via communication complexity

The Annals of Statistics

Rishabh Dudeja

Daniel Hsu

2024/2

Polynomial time auditing of statistical subgroup fairness for Gaussian data

arXiv preprint arXiv:2401.16439

Daniel Hsu

Jizhou Huang

Brendan Juba

2024/1/27

Algorithmic Learning Theory 2024: Preface

Claire Vernade

Daniel Hsu

2024/3/15

Transformers, parallel computation, and logarithmic depth

arXiv preprint arXiv:2402.09268

Clayton Sanford

Daniel Hsu

Matus Telgarsky

2024/2/14

Representational strengths and limitations of transformers

Advances in Neural Information Processing Systems

Clayton Sanford

Daniel J Hsu

Matus Telgarsky

2024/2/13

On the sample complexity of estimation in logistic regression

arXiv preprint arXiv:2307.04191

Daniel Hsu

Arya Mazumdar

2023/7/9

Group conditional validity via multi-group learning

arXiv preprint arXiv:2303.03995

Samuel Deng

Navid Ardeshir

Daniel Hsu

2023/3/7

Efficient estimation of the central mean subspace via smoothed gradient outer products

arXiv preprint arXiv:2312.15469

Gan Yuan

Mingyue Xu

Samory Kpotufe

Daniel Hsu

2023/12/24

Intrinsic dimensionality and generalization properties of the R-norm inductive bias

Navid Ardeshir

Daniel J Hsu

Clayton H Sanford

2023/7/12

Learning tensor representations for meta-learning

Samuel Deng

Yilin Guo

Daniel Hsu

Debmalya Mandal

2022/5/3

Masked prediction tasks: a parameter identifiability view

arXiv preprint arXiv:2202.09305

Bingbin Liu

Daniel Hsu

Pradeep Ravikumar

Andrej Risteski

2022/2/18

Unbiased estimators for random design regression

Journal of Machine Learning Research

Michał Dereziński

Manfred K Warmuth

Daniel Hsu

2022

Masked prediction: A parameter identifiability view

Advances in Neural Information Processing Systems

Bingbin Liu

Daniel J Hsu

Pradeep Ravikumar

Andrej Risteski

2022/12/6

Near-optimal statistical query lower bounds for agnostically learning intersections of halfspaces with gaussian marginals

Daniel J Hsu

Clayton H Sanford

Rocco Servedio

Emmanouil Vasileios Vlatakis-Gkaragkounis

2022/6/28

Simple and near-optimal algorithms for hidden stratification and multi-group learning

Christopher J Tosh

Daniel Hsu

2022/6/28

Contrastive learning, multi-view redundancy, and linear models

Christopher Tosh

Akshay Krishnamurthy

Daniel Hsu

2021/3/1

On the approximation power of two-layer networks of random relus

Daniel Hsu

Clayton H Sanford

Rocco Servedio

Emmanouil Vasileios Vlatakis-Gkaragkounis

2021/7/21

Dimension lower bounds for linear approaches to function approximation

Daniel Hsu’s homepage

Daniel Hsu

2021

Quantifying the effects of COVID-19 on restaurant reviews

Ivy Cao

Zizhou Liu

Giannis Karamanolakis

Daniel Hsu

Luis Gravano

2021/6

See List of Professors in Daniel Hsu University(Columbia University in the City of New York)

Co-Authors

H-index: 90
Sham M Kakade

Sham M Kakade

University of Washington

H-index: 74
Anima Anandkumar

Anima Anandkumar

California Institute of Technology

H-index: 57
Luis Gravano

Luis Gravano

Columbia University in the City of New York

H-index: 51
Mikhail (Misha)  Belkin

Mikhail (Misha) Belkin

University of California, San Diego

H-index: 46
Sanjoy Dasgupta

Sanjoy Dasgupta

University of California, San Diego

H-index: 45
Kamalika Chaudhuri

Kamalika Chaudhuri

University of California, San Diego

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