Eiko Yoneki

Eiko Yoneki

University of Cambridge

H-index: 34

Europe-United Kingdom

About Eiko Yoneki

Eiko Yoneki, With an exceptional h-index of 34 and a recent h-index of 19 (since 2020), a distinguished researcher at University of Cambridge, specializes in the field of optimisation, large-scale graph processing, distributed systems.

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

SIP: Autotuning GPU Native Schedules via Stochastic Instruction Perturbation

Best of both, Structured and Unstructured Sparsity in Neural Networks

MCTS-GEB: Monte Carlo Tree Search is a Good E-graph Builder

X-RLflow: Graph Reinforcement Learning for Neural Network Subgraphs Transformation

Guided Graph Generation: Evaluation of Graph Generators in Terms of Network Statistics, and a New Algorithm

RLFlow: Optimising Neural Network Subgraph Transformation with World Models

BoGraph: structured Bayesian optimization from logs for expensive systems with many parameters

The future is big graphs: a community view on graph processing systems

Eiko Yoneki Information

University

Position

Computer Laboratory

Citations(all)

6782

Citations(since 2020)

1622

Cited By

6101

hIndex(all)

34

hIndex(since 2020)

19

i10Index(all)

61

i10Index(since 2020)

29

Email

University Profile Page

Google Scholar

Eiko Yoneki Skills & Research Interests

optimisation

large-scale graph processing

distributed systems

Top articles of Eiko Yoneki

SIP: Autotuning GPU Native Schedules via Stochastic Instruction Perturbation

arXiv preprint arXiv:2403.16863

2024/3/25

Guoliang He
Guoliang He

H-Index: 2

Eiko Yoneki
Eiko Yoneki

H-Index: 21

Best of both, Structured and Unstructured Sparsity in Neural Networks

2023/5/8

MCTS-GEB: Monte Carlo Tree Search is a Good E-graph Builder

2023/5/8

Guoliang He
Guoliang He

H-Index: 2

Eiko Yoneki
Eiko Yoneki

H-Index: 21

X-RLflow: Graph Reinforcement Learning for Neural Network Subgraphs Transformation

Proceedings of Machine Learning and Systems

2023/3/18

Guoliang He
Guoliang He

H-Index: 2

Eiko Yoneki
Eiko Yoneki

H-Index: 21

Guided Graph Generation: Evaluation of Graph Generators in Terms of Network Statistics, and a New Algorithm

arXiv preprint arXiv:2303.00635

2023/3/1

RLFlow: Optimising Neural Network Subgraph Transformation with World Models

arXiv preprint arXiv:2205.01435

2022/5/3

Sami Alabed
Sami Alabed

H-Index: 1

Eiko Yoneki
Eiko Yoneki

H-Index: 21

BoGraph: structured Bayesian optimization from logs for expensive systems with many parameters

2022/4/5

Sami Alabed
Sami Alabed

H-Index: 1

Eiko Yoneki
Eiko Yoneki

H-Index: 21

GDDR: GNN-based data-driven routing

2021/7/7

Eiko Yoneki
Eiko Yoneki

H-Index: 21

High-dimensional bayesian optimization with multi-task learning for rocksdb

2021/4/26

Sami Alabed
Sami Alabed

H-Index: 1

Eiko Yoneki
Eiko Yoneki

H-Index: 21

World-models for bitrate streaming

Applied Sciences

2020/9/24

Eiko Yoneki
Eiko Yoneki

H-Index: 21

Collaborative facilitation and collaborative inhibition in virtual environments

Future Internet

2020/7/13

Performance analysis of single board computer clusters

Future Generation Computer Systems

2020/1/1

See List of Professors in Eiko Yoneki University(University of Cambridge)

Co-Authors

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