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ORCID3rd 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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