Gerald Friedland

Gerald Friedland

University of California, Berkeley

H-index: 34

North America-United States

About Gerald Friedland

Gerald Friedland, With an exceptional h-index of 34 and a recent h-index of 17 (since 2020), a distinguished researcher at University of California, Berkeley, specializes in the field of multimedia computing, scientific machine learning, speaker diarization, privacy.

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

Multimodal contrastive learning for unsupervised video representation learning

Machine Learning Operations

Capacity

Enhancing GAN-Based Vocoders with Contrastive Learning Under Data-limited Condition

The Curse of Training and the Blessing of High Dimensionality

Machine Learning and Society

Capacity of Neural Networks

The (Black Box) Machine Learning Process

Gerald Friedland Information

University

Position

Brainome Inc

Citations(all)

7316

Citations(since 2020)

2913

Cited By

5861

hIndex(all)

34

hIndex(since 2020)

17

i10Index(all)

103

i10Index(since 2020)

26

Email

University Profile Page

University of California, Berkeley

Google Scholar

View Google Scholar Profile

Gerald Friedland Skills & Research Interests

multimedia computing

scientific machine learning

speaker diarization

privacy

Top articles of Gerald Friedland

Title

Journal

Author(s)

Publication Date

Multimodal contrastive learning for unsupervised video representation learning

Electronic Imaging

Anup Hiremath

Avideh Zakhor

2023/1/16

Machine Learning Operations

Gerald Friedland

2023/8/29

Capacity

The Science of Quantitative Information Flow

Mário S Alvim

Konstantinos Chatzikokolakis

Annabelle McIver

Carroll Morgan

Catuscia Palamidessi

...

2020

Enhancing GAN-Based Vocoders with Contrastive Learning Under Data-limited Condition

arXiv preprint arXiv:2309.09088

Haoming Guo

Seth Z Zhao

Jiachen Lian

Gopala Anumanchipalli

Gerald Friedland

2023/9/16

The Curse of Training and the Blessing of High Dimensionality

Gerald Friedland

2023/8/29

Machine Learning and Society

Gerald Friedland

2023/8/29

Capacity of Neural Networks

Gerald Friedland

2023/8/29

The (Black Box) Machine Learning Process

Gerald Friedland

2023/8/29

Measuring Data Sufficiency

Gerald Friedland

2023/8/29

Meta-Math: Exploring the Limits of Modeling

Gerald Friedland

2023/8/29

The Automated Scientific Process

Gerald Friedland

2023/8/29

Neural Network Architectures

Hooman Yousefizadeh

Ali Zilouchian

2001/3/27

Explainability

Gerald Friedland

2023/8/29

Deep Layers Beware: Unraveling the Surprising Benefits of JPEG Compression for Image Classification Pre-processing

Guruprasad Nayak

Gerald Friedland

2023/12/11

Data Collection and Preparation

Gerald Friedland

2023/8/29

Repeatability and Reproducibility

Gerald Friedland

2023/8/29

The Mechanics of Generalization

Gerald Friedland

2023/8/29

Information-Driven Machine Learning: Data Science as an Engineering Discipline

Gerald Friedland

2023/12/1

Methods and systems for facilitating classification of labelled data

2022/1/27

A Systematic Review of Multimodal Approaches to Online Misinformation Detection

Haoming Guo

Tianyi Huang

Huixuan Huang

Mingyue Fan

Gerald Friedland

2022/8/2

See List of Professors in Gerald Friedland University(University of California, Berkeley)

Co-Authors

H-index: 101
Kannan Ramchandran

Kannan Ramchandran

University of California, Berkeley

H-index: 45
Li-Jia Li

Li-Jia Li

Stanford University

H-index: 44
Martha Larson

Martha Larson

Technische Universiteit Delft

H-index: 28
Hayley Hung

Hayley Hung

Technische Universiteit Delft

H-index: 27
Wolfgang Hürst

Wolfgang Hürst

Universiteit Utrecht

H-index: 20
Nikki Mirghafori

Nikki Mirghafori

University of California, Berkeley

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