Carlos Guestrin

Carlos Guestrin

University of Washington

H-index: 85

North America-United States

About Carlos Guestrin

Carlos Guestrin, With an exceptional h-index of 85 and a recent h-index of 59 (since 2020), a distinguished researcher at University of Washington, specializes in the field of Machine Learning, Distributed Systems, Artificial Intelligence, Parallel Algorithms, Sensor Networks.

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

Post-Hoc Reversal: Are We Selecting Models Prematurely?

ACORN: Performant and Predicate-Agnostic Search Over Vector Embeddings and Structured Data

Machine learning assisted image prediction

Beyond confidence: Reliable models should also consider atypicality

Alpacafarm: A simulation framework for methods that learn from human feedback

Unifying corroborative and contributive attributions in large language models

Exploiting programmatic behavior of llms: Dual-use through standard security attacks

Learning to (learn at test time)

Carlos Guestrin Information

University

Position

Amazon Professor of Machine Learning

Citations(all)

96444

Citations(since 2020)

68833

Cited By

48488

hIndex(all)

85

hIndex(since 2020)

59

i10Index(all)

165

i10Index(since 2020)

121

Email

University Profile Page

University of Washington

Google Scholar

View Google Scholar Profile

Carlos Guestrin Skills & Research Interests

Machine Learning

Distributed Systems

Artificial Intelligence

Parallel Algorithms

Sensor Networks

Top articles of Carlos Guestrin

Title

Journal

Author(s)

Publication Date

Post-Hoc Reversal: Are We Selecting Models Prematurely?

arXiv preprint arXiv:2404.07815

Rishabh Ranjan

Saurabh Garg

Mrigank Raman

Carlos Guestrin

Zachary Chase Lipton

2024/4/11

ACORN: Performant and Predicate-Agnostic Search Over Vector Embeddings and Structured Data

arXiv preprint arXiv:2403.04871

Liana Patel

Peter Kraft

Carlos Guestrin

Matei Zaharia

2024/3/7

Machine learning assisted image prediction

2024/2/27

Beyond confidence: Reliable models should also consider atypicality

Advances in Neural Information Processing Systems

Mert Yuksekgonul

Linjun Zhang

James Y Zou

Carlos Guestrin

2024/2/13

Alpacafarm: A simulation framework for methods that learn from human feedback

Advances in Neural Information Processing Systems

Yann Dubois

Chen Xuechen Li

Rohan Taori

Tianyi Zhang

Ishaan Gulrajani

...

2024/2/13

Unifying corroborative and contributive attributions in large language models

arXiv preprint arXiv:2311.12233

Theodora Worledge

Judy Hanwen Shen

Nicole Meister

Caleb Winston

Carlos Guestrin

2023/11/20

Exploiting programmatic behavior of llms: Dual-use through standard security attacks

arXiv preprint arXiv:2302.05733

Daniel Kang

Xuechen Li

Ion Stoica

Carlos Guestrin

Matei Zaharia

...

2023/2/11

Learning to (learn at test time)

arXiv preprint arXiv:2310.13807

Yu Sun

Xinhao Li

Karan Dalal

Chloe Hsu

Sanmi Koyejo

...

2023/10/20

Adding glycemic and physical activity metrics to a multimodal algorithm-enabled decision-support tool for type 1 diabetes care: keys to implementation and opportunities

Frontiers in Endocrinology

Dessi P Zaharieva

Ransalu Senanayake

Conner Brown

Brendan Watkins

Glenn Loving

...

2023/1/12

On-the-fly calibration for improved on-device eye tracking

2023/10/17

Disparities in hemoglobin A1c levels in the first year after diagnosis among youths with type 1 diabetes offered continuous glucose monitoring

JAMA Network Open

Ananta Addala

Victoria Ding

Dessi P Zaharieva

Franziska K Bishop

Alyce S Adams

...

2023/4/3

Beyond confidence: Reliable models should also quantify atypicality

Mert Yuksekgonul

Linjun Zhang

James Zou

Carlos Guestrin

2023/3/4

A Platform for the Personalized Management of Diabetes and Cardiovascular Disease at Population Scale With Data From Multiple Sensors

Circulation

Ransalu Senanayake

Johannes O Ferstad

Isha Thapa

Flavia Giammarino

Megana Vasu

...

2022/11/8

User-interface for developing applications that apply machine learning

2021/2/23

Learning neural network subspaces

Mitchell Wortsman

Maxwell C Horton

Carlos Guestrin

Ali Farhadi

Mohammad Rastegari

2021/7/1

Variance-Based Learning Rate Control For Training Machine-Learning Models

2021/3/25

Mobility trends provide a leading indicator of changes in SARS-CoV-2 transmission

MedRxiv

Andrew C Miller

Nicholas J Foti

Joseph A Lewnard

Nicholas P Jewell

Carlos Guestrin

...

2020/5/11

Beyond accuracy: Behavioral testing of NLP models with CheckList

arXiv preprint arXiv:2005.04118

Marco Tulio Ribeiro

Tongshuang Wu

Carlos Guestrin

Sameer Singh

2020/5/8

AdaScale SGD: A user-friendly algorithm for distributed training

Tyler Johnson

Pulkit Agrawal

Haijie Gu

Carlos Guestrin

2020/11/21

The rise and fall of network stars: Analyzing 2.5 million graphs to reveal how high-degree vertices emerge over time

Information Processing & Management

Michael Fire

Carlos Guestrin

2020/3/1

See List of Professors in Carlos Guestrin University(University of Washington)

Co-Authors

H-index: 151
Christos Faloutsos

Christos Faloutsos

Carnegie Mellon University

H-index: 147
Jure Leskovec

Jure Leskovec

Stanford University

H-index: 122
Jon Kleinberg

Jon Kleinberg

Cornell University

H-index: 112
Samuel Madden

Samuel Madden

Massachusetts Institute of Technology

H-index: 102
Joseph Hellerstein

Joseph Hellerstein

University of California, Berkeley

H-index: 83
Arvind Krishnamurthy

Arvind Krishnamurthy

University of Washington

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