The 4th Workshop on Machine Learning and Systems (EuroMLSys)

co-located with EuroSys '24

April 22nd 2024, Athens, Greece


The recent wave of research focusing on machine intelligence (machine learning and artificial intelligence) and its applications has been fuelled by both hardware improvements and deep learning frameworks that simplify the design and training of neural models. Advances in AI also accelerate research towards Reinforcement Learning (RL), where dynamic control mechanisms are designed to tackle complex tasks. Further, machine learning based optimisation, such as Bayesian Optimisation, is gaining traction in the computer systems community where optimisation needs to scale with complex and large parameter spaces; areas of interest range from hyperparameter tuning to system configuration tuning,

The EuroMLSys workshop will provide a platform for discussing emerging trends in building frameworks, programming models, optimisation algorithms, and software engineering to support AI/ML applications. At the same time, using ML for building such frameworks or optimisation tools will be discussed. EuroMLSys aims to bridge the gap between AI research and practice, through a technical program of fresh ideas on software infrastructure, tools, design principles, and theory/algorithms, from a systems perspective. We will also explore potential applications that will take advantages of ML.

News

  • Submission deadline has been extended!

Key dates

  • Paper submission deadline:February 20, 2024 (23:59 AoE) February 26, 2024 (23:59 AoE)
  • Acceptance notification: March 18, 2024 March 22, 2024
  • Final paper due: March 26, 2024 March 29, 2024
  • Workshop: April 22, 2024 (full-day workshop)

Past Editions

Call for Papers

A growing area of interest in machine intelligence is at the intersection of AI/ML and systems design. At the same time, applications of ML are growing in complexity and so is the volume of data they produce/consume. For computer systems to scale, new learning approaches and advanced optimisation techniques are needed. We also need to understand better the current AI/ML frameworks, in terms of their functionality, limitations, and target applications. This will clarify potential desired functions and future architectures. Novel machine learning methods to optimise and accelerate software and hardware systems must also be developed.

EuroMLSys is an interdisciplinary workshop that brings together researchers in computer architecture, systems and machine learning, along with practitioners who are active in these emerging areas.

Topics of interest include, but are not limited to, the following:

  • Scheduling algorithms for data processing clusters
  • Custom hardware for machine learning
  • Programming languages for machine learning
  • Benchmarking systems (for machine learning algorithms)
  • Synthetic input data generation for training
  • Systems for training and serving machine learning models at scale
  • Graph neural networks
  • Neural network compression and pruning in systems
  • Systems for incremental learning algorithms
  • Large scale distributed learning algorithms in practice
  • Database systems for large scale learning
  • Model understanding tools (debugging, visualisation, etc.)
  • Systems for model-free and model-based Reinforcement Learning
  • Optimisation in end-to-end deep learning
  • System optimisation using Bayesian Optimisation
  • Acceleration of model building (e.g., imitation learning in RL)
  • Use of probabilistic models in ML/AI application
  • Learning models for inferring network attacks, device/service fingerprinting, congestion, etc.
  • Techniques to collect and analyze network data in a privacy-preserving manner
  • Learning models to capture network events and control actions
  • Machine learning in networking (e.g., use of Deep RL in networking)
  • Analysis of distributed ML algorithms
  • Semantics for distributed ML languages
  • Probabilistic modelling for distributed ML algorithms
  • Synchronisation and state control of distributed ML algorithms

Accepted papers will be published in the ACM Digital Library (you can opt out from this).

Submission

Papers must be submitted electronically as PDF files, formatted for 8.5x11-inch paper. The length of the paper must be no more than 6 pages in the ACM double-column format (10-pt font). References are out of the 6 pages limit. Submitted papers must use the official ACM Master article template

Submissions will be single-blind.

Submit your paper at: https://euromlsys24.hotcrp.com/paper/new

Sponsors


Committees

Workshop and TPC Chairs

Technical Program Committee

  • Ahmed Sayed, Queen Mary University of London
  • Alex Iacob, University of Cambridge
  • Alexandros Koliousis, Northeastern University London and Institute for Experiential AI
  • Amir Payberah, KTH
  • Amitabha Roy, Google
  • Andrei Paleyes, University of Cambridge
  • Chi Zhang, Brandeis University
  • Christina Giannoula, University of Toronto
  • Christos Bouganis, Imperial College London
  • Daniel Goodman, Oracle
  • Daniel Mendoza, Stanford University
  • Davide Sanvito, NEC Laboratories Europe
  • Dawei Li, Amazon
  • Deepak George Thomas, Iowa State University
  • Dimitris Chatzopoulos, University College Dublin
  • Fiodar Kazhamiaka,Stanford University
  • Guilherme H. Apostolo, Vrije Universiteit Amsterdam
  • Guoliang He, University of Cambridge
  • Guy Leroy, MSR Cambridge
  • Hamed Haddadi, Imperial College London
  • Holger Pirk, Imperial College London
  • Jenny Huang, NVIDIA
  • Jon Crowcroft, University of Cambridge
  • Jose Cano, University of Glasgow
  • Laurent Bindschaedler, MPI-SWS
  • Liang Zhang, Oracle
  • Luigi Nardi, Lund University
  • Luo Mai, University of Edinburgh
  • Mark Zhao, Stanford University
  • Mengying Zhou, Fudan University
  • Nasrullah Sheikh, IBM Research Almaden
  • Νikhil Sarda, Google
  • Nikolas Ioannou, Google
  • Paul Patras, University of Edinburgh
  • Peter Triantafillou, University of Warwick
  • Pouya Hamadanian, MIT
  • Pratik Fegade, Google
  • Sam Ainsworth, University of Edinburgh
  • Sami Alabed, Deepmind
  • Taiyi Wang, University of Cambridge
  • Thaleia Dimitra Doudali, IMDEA
  • Valentin Radu, University of Sheffield
  • Veljko Pejovic, University of Ljubljana
  • Wayne Luke ,Imperial College London
  • Xupeng Miao, Peking University
  • Youhe Jiang, University of Cambridge
  • Zak Singh, University of Cambridge
  • Zheng Wang, University of Leeds
  • Zhihao Jia, CMU

Web Chair

  • Alexis Duque, Net AI

Contact

For any question(s) related to EuroMLSys 2023, please contact the TPC Chairs Eiko Yoneki and Aaron Zhao.

Follow us on Twitter: @euromlsys

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