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