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3rd EuroMLSys@EuroSys 2023: Rome, Italy
- Eiko Yoneki, Luigi Nardi:
Proceedings of the 3rd Workshop on Machine Learning and Systems, EuroMLSys 2023, Rome, Italy, 8 May 2023. ACM 2023 - Ming-Chuan Wu
, Manuel Bähr
, Nils Braun
, Katrin Honauer
:
Actionable Data Insights for Machine Learning. 1-7 - Maximilian Böther
, Foteini Strati
, Viktor Gsteiger
, Ana Klimovic
:
Towards A Platform and Benchmark Suite for Model Training on Dynamic Datasets. 8-17 - Ehsan Yousefzadeh-Asl-Miandoab
, Ties Robroek
, Pinar Tözün
:
Profiling and Monitoring Deep Learning Training Tasks. 18-25 - Guoliang He
, Zak Singh
, Eiko Yoneki
:
MCTS-GEB: Monte Carlo Tree Search is a Good E-graph Builder. 26-33 - Akash Dhasade
, Anne-Marie Kermarrec
, Rafael Pires
, Rishi Sharma
, Milos Vujasinovic
:
Decentralized Learning Made Easy with DecentralizePy. 34-41 - Dongqi Cai
, Yaozong Wu
, Haitao Yuan
, Shangguang Wang
, Felix Xiaozhu Lin
, Mengwei Xu
:
Towards Practical Few-shot Federated NLP. 42-48 - Ousmane Touat
, Sara Bouchenak
:
Towards Robust and Bias-free Federated Learning. 49-55 - Chenyang Ma
, Xinchi Qiu
, Daniel J. Beutel
, Nicholas D. Lane
:
Gradient-less Federated Gradient Boosting Tree with Learnable Learning Rates. 56-63 - Hongrui Shi
, Valentin Radu
, Po Yang
:
Distributed Training for Speech Recognition using Local Knowledge Aggregation and Knowledge Distillation in Heterogeneous Systems. 64-70 - Luke Nicholas Darlow
, Artjom Joosen
, Martin Asenov
, Qiwen Deng
, Jianfeng Wang
, Adam Barker
:
FoldFormer: sequence folding and seasonal attention for fine-grained long-term FaaS forecasting. 71-77 - Mehran Salmani
, Saeid Ghafouri
, Alireza Sanaee
, Kamran Razavi
, Max Mühlhäuser
, Joseph Doyle
, Pooyan Jamshidi
, Mohsen Sharifi
:
Reconciling High Accuracy, Cost-Efficiency, and Low Latency of Inference Serving Systems. 78-86 - Muhammad Sabih
, Mikail Yayla
, Frank Hannig
, Jürgen Teich
, Jian-Jia Chen
:
Robust and Tiny Binary Neural Networks using Gradient-based Explainability Methods. 87-93 - Theophilus A. Benson
:
Illuminating the hidden challenges of data-driven CDNs. 94-103 - Christoph Schulte
, Sven Wagner
, Armin Runge
, Dimitrios Bariamis
, Barbara Hammer
:
Best of both, Structured and Unstructured Sparsity in Neural Networks. 104-108 - Luke Nicholas Darlow
, Artjom Joosen
, Martin Asenov
, Qiwen Deng
, Jianfeng Wang
, Adam Barker
:
TSMix: time series data augmentation by mixing sources. 109-114 - Georgia Christofidi
, Konstantinos Papaioannou
, Thaleia Dimitra Doudali
:
Toward Pattern-based Model Selection for Cloud Resource Forecasting. 115-122 - Norah Alballa
, Marco Canini
:
A First Look at the Impact of Distillation Hyper-Parameters in Federated Knowledge Distillation. 123-130 - Alex Iacob
, Pedro Porto Buarque de Gusmão
, Nicholas D. Lane
:
Can Fair Federated Learning Reduce the need for Personalisation? 131-139 - Andrei Paleyes
, Neil David Lawrence
:
Causal fault localisation in dataflow systems. 140-147 - Minh Tri Le
, Julyan Arbel
:
TinyMLOps for real-time ultra-low power MCUs applied to frame-based event classification. 148-153 - Ravi Kumar Singh
, Mayank Mishra
, Rekha Singhal
:
Scalable High-Performance Architecture for Evolving Recommender System. 154-162 - Ravi Kumar Singh
, Mayank Mishra
, Rekha Singhal
:
Accelerating Model Training: Performance Antipatterns Eliminator Framework. 163-170

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