Kannan Ramchandran

About Kannan Ramchandran

Kannan Ramchandran, With an exceptional h-index of 101 and a recent h-index of 48 (since 2020), a distinguished researcher at University of California, Berkeley, specializes in the field of Signal Processing, Communications, Information Theory, Computer Vision, Networking.

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

Toward a Theory of Tokenization in LLMs

Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing

Learning a 1-layer conditional generative model in total variation

Learning to Understand: Identifying Interactions via the Mobius Transform

Competing Bandits in Non-Stationary Matching Markets

Online Pricing for Multi-User Multi-Item Markets

MRI reconstruction with side information using diffusion models

Dynamic Assortment Selection and Pricing with Learning

Kannan Ramchandran Information

University

Position

Professor of Electrical Engineering and Computer Science

Citations(all)

44169

Citations(since 2020)

11153

Cited By

37606

hIndex(all)

101

hIndex(since 2020)

48

i10Index(all)

389

i10Index(since 2020)

162

Email

University Profile Page

Google Scholar

Kannan Ramchandran Skills & Research Interests

Signal Processing

Communications

Information Theory

Computer Vision

Networking

Top articles of Kannan Ramchandran

Toward a Theory of Tokenization in LLMs

arXiv preprint arXiv:2404.08335

2024/4/12

Greedy Pruning with Group Lasso Provably Generalizes for Matrix Sensing

Advances in Neural Information Processing Systems

2024/2/13

Learning a 1-layer conditional generative model in total variation

Advances in Neural Information Processing Systems

2024/2/13

Justin Kang
Justin Kang

H-Index: 0

Ananya Uppal
Ananya Uppal

H-Index: 2

Kannan Ramchandran
Kannan Ramchandran

H-Index: 53

Learning to Understand: Identifying Interactions via the Mobius Transform

arXiv preprint arXiv:2402.02631

2024/2/4

Competing Bandits in Non-Stationary Matching Markets

IEEE Transactions on Information Theory

2024/1/10

Online Pricing for Multi-User Multi-Item Markets

Advances in Neural Information Processing Systems

2023/12/15

MRI reconstruction with side information using diffusion models

2023/10/29

Kannan Ramchandran
Kannan Ramchandran

H-Index: 53

Dynamic Assortment Selection and Pricing with Learning

2023/10/13

Kannan Ramchandran
Kannan Ramchandran

H-Index: 53

Thomas Courtade
Thomas Courtade

H-Index: 21

Pairwise proximal policy optimization: Harnessing relative feedback for llm alignment

arXiv preprint arXiv:2310.00212

2023/9/30

Efficient Clustering Frameworks for Federated Learning Systems

2023/8/11

The Fair Value of Data Under Heterogeneous Privacy Constraints in Federated Learning

Transactions on Machine Learning Research

2024/2/8

Test accuracy vs. generalization gap: Model selection in nlp without accessing training or testing data

2023/8/6

Model Selection for Generic Contextual Bandits

IEEE Transactions on Information Theory

2023/7/24

Avishek Ghosh
Avishek Ghosh

H-Index: 7

Kannan Ramchandran
Kannan Ramchandran

H-Index: 53

Efficiently computing sparse Fourier transforms of q-ary functions

2023/6

Amirali Aghazadeh
Amirali Aghazadeh

H-Index: 5

Kannan Ramchandran
Kannan Ramchandran

H-Index: 53

Layerwise Training of Deep Neural Networks

2023/5/12

Interactive Learning with Pricing for Optimal and Stable Allocations in Markets

2023/4/11

Soham Phade
Soham Phade

H-Index: 2

Kannan Ramchandran
Kannan Ramchandran

H-Index: 53

Conditional Score-Based Reconstructions for Multi-contrast MRI

arXiv preprint arXiv:2303.14795

2023/3/26

Kannan Ramchandran
Kannan Ramchandran

H-Index: 53

Minimum-Rate Spectrum-Blind Sampling Based on Sparse-Graph Codes

IEEE Transactions on Signal Processing

2023/2/22

Statistical Complexity and Optimal Algorithms for Non-linear Ridge Bandits

arXiv preprint arXiv:2302.06025

2023/2/12

The Square Root Agreement Rule for Incentivizing Truthful Feedback on Online Platforms

Management Science

2023/1

See List of Professors in Kannan Ramchandran University(University of California, Berkeley)

Co-Authors

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