Marco Canini

About Marco Canini

Marco Canini, With an exceptional h-index of 42 and a recent h-index of 33 (since 2020), a distinguished researcher at King Abdullah University of Science and Technology, specializes in the field of Systems, Networking, Distributed Systems, Machine Learning.

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

Practical Insights into Knowledge Distillation for Pre-Trained Models

Flashback: Understanding and Mitigating Forgetting in Federated Learning

Global-QSGD: Practical Floatless Quantization for Distributed Learning with Theoretical Guarantees

A comprehensive empirical study of heterogeneity in federated learning

On Detecting Biased Predictions with Post-hoc Explanation Methods

A First Look at the Impact of Distillation Hyper-Parameters in Federated Knowledge Distillation

FilFL: Client filtering for optimized client participation in federated learning

Kimad: Adaptive Gradient Compression with Bandwidth Awareness

Marco Canini Information

University

Position

___

Citations(all)

6637

Citations(since 2020)

4010

Cited By

4100

hIndex(all)

42

hIndex(since 2020)

33

i10Index(all)

88

i10Index(since 2020)

70

Email

University Profile Page

King Abdullah University of Science and Technology

Google Scholar

View Google Scholar Profile

Marco Canini Skills & Research Interests

Systems

Networking

Distributed Systems

Machine Learning

Top articles of Marco Canini

Title

Journal

Author(s)

Publication Date

Practical Insights into Knowledge Distillation for Pre-Trained Models

arXiv preprint arXiv:2402.14922

Norah Alballa

Marco Canini

2024/2/22

Flashback: Understanding and Mitigating Forgetting in Federated Learning

arXiv preprint arXiv:2402.05558

Mohammed Aljahdali

Ahmed M Abdelmoniem

Marco Canini

Samuel Horváth

2024/2/8

Global-QSGD: Practical Floatless Quantization for Distributed Learning with Theoretical Guarantees

arXiv preprint arXiv:2305.18627

Jihao Xin

Marco Canini

Peter Richtárik

Samuel Horváth

2023/5/29

A comprehensive empirical study of heterogeneity in federated learning

IEEE Internet of Things Journal

Ahmed M Abdelmoniem

Chen-Yu Ho

Pantelis Papageorgiou

Marco Canini

2023/3/7

On Detecting Biased Predictions with Post-hoc Explanation Methods

Matteo Ruggeri

Alice Dethise

Marco Canini

2023/12/8

A First Look at the Impact of Distillation Hyper-Parameters in Federated Knowledge Distillation

Norah Alballa

Marco Canini

2023/5/8

FilFL: Client filtering for optimized client participation in federated learning

arXiv preprint arXiv:2302.06599

Fares Fourati

Salma Kharrat

Vaneet Aggarwal

Mohamed-Slim Alouini

Marco Canini

2023/2/13

Kimad: Adaptive Gradient Compression with Bandwidth Awareness

Jihao Xin

Ivan Ilin

Shunkang Zhang

Marco Canini

Peter Richtárik

2023/12/8

Refl: Resource-efficient federated learning

Ahmed M Abdelmoniem

Atal Narayan Sahu

Marco Canini

Suhaib A Fahmy

2023/5/8

Filfl: Accelerating federated learning via client filtering

Fares Fourati

Salma Kharrat

Vaneet Aggarwal

Mohamed-Slim Alouini

Marco Canini

2023/2/13

MicroView: Cloud-Native Observability with Temporal Precision

Alessandro Cornacchia

Theophilus A Benson

Muhammad Bilal

Marco Canini

2023/12/8

With great freedom comes great opportunity: Rethinking resource allocation for serverless functions

Muhammad Bilal

Marco Canini

Rodrigo Fonseca

Rodrigo Rodrigues

2023/5/8

{SAGE}: Software-based Attestation for {GPU} Execution

Andrei Ivanov

Benjamin Rothenberger

Arnaud Dethise

Marco Canini

Torsten Hoefler

...

2023

MicroView: observability with temporal precision

Alessandro Cornacchia

Theophilus Benson

Muhammad Bilal

Marco Canini

2023/10/24

In-network aggregation with transport transparency for distributed training

Shuo Liu

Qiaoling Wang

Junyi Zhang

Wenfei Wu

Qinliang Lin

...

2023/3/25

TENSOR: Lightweight BGP Non-Stop Routing

Congcong Miao

Yunming Xiao

Marco Canini

Ruiqiang Dai

Shengli Zheng

...

2023/9/10

Renaissance: A self-stabilizing distributed SDN control plane using in-band communications

Journal of Computer and System Sciences

Marco Canini

Iosif Salem

Liron Schiff

Elad M Schiller

Stefan Schmid

2022/8/1

Empirical analysis of federated learning in heterogeneous environments

Ahmed M Abdelmoniem

Chen-Yu Ho

Pantelis Papageorgiou

Marco Canini

2022/4/5

Direct nonlinear acceleration

Operational Research

Marco Canini

Peter Richtárik

2022

Unlocking the power of inline {Floating-Point} operations on programmable switches

Yifan Yuan

Omar Alama

Jiawei Fei

Jacob Nelson

Dan RK Ports

...

2022

See List of Professors in Marco Canini University(King Abdullah University of Science and Technology)

Co-Authors

H-index: 117
Jennifer Rexford

Jennifer Rexford

Princeton University

H-index: 64
Peter Richtarik

Peter Richtarik

King Abdullah University of Science and Technology

H-index: 55
Panos Kalnis

Panos Kalnis

King Abdullah University of Science and Technology

H-index: 52
Stefan Schmid

Stefan Schmid

Universität Wien

H-index: 41
Andrew W. Moore

Andrew W. Moore

University of Cambridge

H-index: 40
Fernando Pedone

Fernando Pedone

Università della Svizzera Italiana

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