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Serving ML prediction pipelines spanning multiple models and hardware accelerators is a key challenge in production machine learning.
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Nephele streaming: Stream processing under qos constraints at scale
B. Lohrmann, D. Warneke, and O. Kao · 2013
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Deep Convolutional Network Cascade for Facial Point Detection
Y. Sun, X. Wang, and X. Tang · 2013
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Deep compositional question answering with neural module networks
J. Andreas, M. Rohrbach, T. Darrell, and D. Klein · 2015
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Real-Time Pedestrian Detection with Deep Network Cascades
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Elastic stream processing with latency guarantees
B. Lohrmann, P. Janacik, and O. Kao · 2015
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Ask your neurons: A neural-based approach to answering questions about images
M. Malinowski, M. Rohrbach, and M. Fritz · 2015
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Faster R-CNN: towards real-time object detection with region proposal networks
S. Ren, K. He, R. B. Girshick, and J. Sun · 2015
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An Uncertainty-Aware Approach to Optimal Configuration of Stream Processing Systems
P. Jamshidi and G. Casale · 2016
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Morpheus: Towards automated slos for enterprise clusters
S. A. Jyothi, C. Curino, I. Menache, S. M. Narayanamurthy, A. Tumanov, J. Yaniv, R. Mavlyutov, I. n. Goiri, S. Krishnan, J. Kulkarni, and S. Rao · 2016
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Dhalion: Self-regulating stream processing in heron
A. Floratou, A. Agrawal, B. Graham, S. Rao, and K. Ramasamy · 2017
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Drs: Auto-scaling for real-time stream analytics
T. Z. J. Fu, J. Ding, R. T. B. Ma, M. Winslett, Y. Yang, and Z. Zhang · 2017
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Energy-efficient Amortized Inference with Cascaded Deep Classifiers
J. Guan, Y. Liu, Q. Liu, and J. Peng · 2017
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Amazon sagemaker: Developer guide
A. W. S. Inc · 2017
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Deciding How to Decide: Dynamic Routing in Artificial Neural Networks
M. McGill and P. Perona · 2017
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Automatic differentiation in pytorch
A. Paszke, S. Gross, S. Chintala, G. Chanan, E. Yang, Z. DeVito, Z. Lin, A. Desmaison, L. Antiga, and A. Lerer · 2017
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J. Redmon, S. Divvala, R. Girshick, and A. Farhadi · 2016
Cited alongside, same era.
End-to-End Large Scale Machine Learning with KeystoneML
E. Sparks · 2016
Cited alongside, same era.
TFX: A tensorflow-based production-scale machine learning platform
D. Baylor, E. Breck, H.-T. Cheng, N. Fiedel, C. Y. Foo, Z. Haque, S. Haykal, M. Ispir, V. Jain, L. Koc, C. Y. Koo, L. Lew, C. Mewald, A. N. Modi, N. Polyzotis, S. Ramesh, S. Roy, S. E. Whang, M. Wicke, J. Wilkiewicz, X. Zhang, and M. Zinkevich · 2017
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Towards automatic parameter tuning of stream processing systems
M. Bilal and M. Canini · 2017
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Clipper: A low-latency online prediction serving system
D. Crankshaw, X. Wang, G. Zhou, M. J. Franklin, J. E. Gonzalez, and I. Stoica · 2017
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https://flink.apache.org
Apache Flink
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https://www.openalpr.com/
Open ALPR
Cited in the paper.
Enabling workflow-aware scheduling on hpc systems
G. P. Rodrigo, E. Elmroth, P.-O. Östberg, and L. Ramakrishnan · 2017
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Live video analytics at scale with approximation and delay-tolerance
H. Zhang, G. Ananthanarayanan, P. Bodik, M. Philipose, P. Bahl, and M. J. Freedman · 2017
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Three steps is all you need: Fast, accurate, automatic scaling decisions for distributed streaming dataflows
V. Kalavri, J. Liagouris, M. Hoffmann, D. Dimitrova, M. Forshaw, and T. Roscoe · 2018
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Nexus: A gpu cluster engine for accelerating dnn-based video analysis
H. Shen, L. Chen, Y. Jin, L. Zhao, B. Kong, M. Philipose, A. Krishnamurthy, and R. Sundaram · 2019
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