Hanbaek Lyu

Hanbaek Lyu

University of California, Los Angeles

H-index: 10

North America-United States

About Hanbaek Lyu

Hanbaek Lyu, With an exceptional h-index of 10 and a recent h-index of 9 (since 2020), a distinguished researcher at University of California, Los Angeles, specializes in the field of Probability, combinatorics, complex systems, optimization, machine learning.

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

On the Complexity of First-Order Methods in Stochastic Bilevel Optimization

Stochastic optimization with arbitrary recurrent data sampling

Four-parameter coalescing ballistic annihilation

Learning low-rank latent mesoscale structures in networks

New directions in algebraic statistics: Three challenges from 2023

Exponentially Convergent Algorithms for Supervised Matrix Factorization

Interpretable Online Network Dictionary Learning for Inferring Long-Range Chromatin Interactions

Complexity of block coordinate descent with proximal regularization and applications to Wasserstein CP-dictionary learning

Hanbaek Lyu Information

University

Position

___

Citations(all)

290

Citations(since 2020)

261

Cited By

123

hIndex(all)

10

hIndex(since 2020)

9

i10Index(all)

13

i10Index(since 2020)

9

Email

University Profile Page

University of California, Los Angeles

Google Scholar

View Google Scholar Profile

Hanbaek Lyu Skills & Research Interests

Probability

combinatorics

complex systems

optimization

machine learning

Top articles of Hanbaek Lyu

Title

Journal

Author(s)

Publication Date

On the Complexity of First-Order Methods in Stochastic Bilevel Optimization

arXiv preprint arXiv:2402.07101

Jeongyeol Kwon

Dohyun Kwon

Hanbaek Lyu

2024/2/11

Stochastic optimization with arbitrary recurrent data sampling

arXiv preprint arXiv:2401.07694

William G Powell

Hanbaek Lyu

2024/1/15

Four-parameter coalescing ballistic annihilation

arXiv preprint arXiv:2401.06852

Kimberly Affeld

Christian Dean

Matthew Junge

Hanbaek Lyu

Connor Panish

...

2024/1/12

Learning low-rank latent mesoscale structures in networks

Nature Communications

Hanbaek Lyu

Yacoub H Kureh

Joshua Vendrow

Mason A Porter

2024/1/3

New directions in algebraic statistics: Three challenges from 2023

arXiv preprint arXiv:2402.13961

Yulia Alexandr

Miles Bakenhus

Mark Curiel

Sameer K Deshpande

Elizabeth Gross

...

2024/2/21

Exponentially Convergent Algorithms for Supervised Matrix Factorization

Advances in Neural Information Processing Systems

Joowon Lee

Hanbaek Lyu

Weixin Yao

2024/2/13

Interpretable Online Network Dictionary Learning for Inferring Long-Range Chromatin Interactions

arXiv preprint arXiv:2312.10519

Vishal Rana

Jianhao Peng

Chao Pan

Hanbaek Lyu

Albert Cheng

...

2023/12/16

Complexity of block coordinate descent with proximal regularization and applications to Wasserstein CP-dictionary learning

Dohyun Kwon

Hanbaek Lyu

2023/7/3

A latent linear model for nonlinear coupled oscillators on graphs

arXiv preprint arXiv:2311.14910

Agam Goyal

Zhaoxing Wu

Richard P Yim

Binhao Chen

Zihong Xu

...

2023/11/25

Diffusion-limited annihilating-coalescing systems

arXiv preprint arXiv:2305.19333

Sungwon Ahn

Matthew Junge

Hanbaek Lyu

Lily Reeves

Jacob Richey

...

2023/5/30

Supervised low-rank semi-nonnegative matrix factorization with frequency regularization for forecasting spatio-temporal data

arXiv preprint arXiv:2311.08636

Keunsu Kim

Hanbaek Lyu

Jinsu Kim

Jae-Hun Jung

2023/11/15

Three-velocity coalescing ballistic annihilation

Electronic Journal of Probability

Luis Benitez

Matthew Junge

Hanbaek Lyu

Maximus Redman

Lily Reeves

2023

Particle density in diffusion-limited annihilating systems

The Annals of Probability

Tobias Johnson

Matthew Junge

Hanbaek Lyu

David Sivakoff

2023/11

Sampling random graph homomorphisms and applications to network data analysis

Journal of Machine Learning Research

Hanbaek Lyu

Facundo Memoli

David Sivakoff

2023/1

Block majorization-minimization with diminishing radius for constrained nonconvex optimization

arXiv preprint arXiv:2012.03503

Hanbaek Lyu

Yuchen Li

2023/8/25

Convergence and complexity of block majorization-minimization for constrained block-Riemannian optimization

arXiv preprint arXiv:2312.10330

Yuchen Li

Laura Balzano

Deanna Needell

Hanbaek Lyu

2023/12/16

Convergence of first-order methods for constrained nonconvex optimization with dependent data

Ahmet Alacaoglu

Hanbaek Lyu

2023/6/15

Learning to predict synchronization of coupled oscillators on randomly generated graphs

Scientific reports

Hardeep Bassi

Richard P Yim

Joshua Vendrow

Rohith Koduluka

Cherlin Zhu

...

2022/9/5

Inferring single-molecule chromatin interactions via online convex network dictionary learning

bioRxiv

Jianhao Peng

Chao Pan

Hanbaek Lyu

Minji Kim

Albert Cheng

...

2022/8/1

Supervised Dictionary Learning with Auxiliary Covariates

arXiv preprint arXiv:2206.06774

Joowon Lee

Hanbaek Lyu

Weixin Yao

2022/6/14

See List of Professors in Hanbaek Lyu University(University of California, Los Angeles)

Co-Authors

H-index: 35
Igor Pak

Igor Pak

University of California, Los Angeles

H-index: 31
Laura Balzano

Laura Balzano

University of Michigan-Dearborn

H-index: 24
Lionel Levine

Lionel Levine

Cornell University

H-index: 22
Janko Gravner

Janko Gravner

University of California, Davis

H-index: 14
Arnab Sen

Arnab Sen

University of Minnesota-Twin Cities

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