Fetching the paper…
Reading the bibliography…
In this paper, we introduce Katib: a scalable, cloud-native, and production-ready hyperparameter tuning system that is agnostic of the underlying machine learning framework.
Gang scheduling performance benefits for fine-grain synchronization
Feitelson, D. G., and Rudolph, L · 1992
Earlier work this paper cites.
Algorithms for hyper-parameter optimization
Bergstra, J., Bardenet, R., Bengio, Y., and Kégl, B · 2011
Earlier work this paper cites.
Random search for hyper-parameter optimization
Bergstra, J., and Bengio, Y · 2012
Earlier work this paper cites.
Practical bayesian optimization of machine learning algorithms
Snoek, J., Larochelle, H., and Adams, R. P · 2012
Earlier work this paper cites.
Communication efficient distributed machine learning with the parameter server
Li, M., Andersen, D. G., Smola, A. J., and Yu, K · 2014
Earlier work this paper cites.
Hyperopt: a python library for model selection and hyperparameter optimization
Bergstra, J., Komer, B., Eliasmith, C., Yamins, D., and Cox, D. D · 2015
Earlier work this paper cites.
Mxnet: A flexible and efficient machine learning library for heterogeneous distributed systems
Chen, T., Li, M., Li, Y., Lin, M., Wang, N., Wang, M., Xiao, T., Xu, B., Zhang, C., and Zhang, Z · 2015
Earlier work this paper cites.
Tensorflow: A system for large-scale machine learning
Abadi, M., Barham, P., Chen, J., Chen, Z., Davis, A., Dean, J., Devin, M., Ghemawat, S., Irving, G., Isard, M., et al · 2016
Earlier work this paper cites.
Chaos engineering
Basiri, A., Behnam, N., De Rooij, R., Hochstein, L., Kosewski, L., Reynolds, J., and Rosenthal, C · 2016
Earlier work this paper cites.
Xgboost: A scalable tree boosting system
Chen, T., and Guestrin, C · 2016
Earlier work this paper cites.
Deep Learning
Goodfellow, I., Bengio, Y., and Courville, A · 2016
Earlier work this paper cites.
Modeldb: a system for machine learning model management
Vartak, M., Subramanyam, H., Lee, W.-E., Viswanathan, S., Husnoo, S., Madden, S., and Zaharia, M · 2016
Cited alongside, same era.
Google vizier: A service for black-box optimization
Golovin, D., Solnik, B., Moitra, S., Kochanski, G., Karro, J., and Sculley, D · 2017
Cited alongside, same era.
Hyperband: A novel bandit-based approach to hyperparameter optimization
Li, L., Jamieson, K., DeSalvo, G., Rostamizadeh, A., and Talwalkar, A · 2017
Cited alongside, same era.
Tune: A research platform for distributed model selection and training
Liaw, R., Liang, E., Nishihara, R., Moritz, P., Gonzalez, J. E., and Stoica, I · 2018
Cited alongside, same era.
DARTS: differentiable architecture search
Liu, H., Simonyan, K., and Yang, Y · 2018
Cited alongside, same era.
https://github.com/microsoft/nni
An open source AutoML toolkit for neural architecture search, model compression and hyper-parameter tuning, 2020 · 2020
Closest in time.
https://intl.caicloud.io/products/clever
Caicloud clever: Artificial intelligence cloud platform, 2020 · 2020
Closest in time.
https://github.com/kubeflow/kubeflow
Kubeflow: The Machine Learning Toolkit for Kubernetes, 2020 · 2020
Closest in time.
https://kubernetes.io/
Kubernetes: Production-Grade Container Orchestration, 2020 · 2020
Closest in time.
https://www.mysql.com/
MySQL: The world’s most popular open source database, 2020 · 2020
Closest in time.
https://swagger.io/docs/specification/about/
Openapi: an api description format for rest apis, 2020 · 2020
Closest in time.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Sergeev, A., and Balso, M. D · 2018
Cited alongside, same era.
Accelerating the machine learning lifecycle with mlflow
Zaharia, M., Chen, A., Davidson, A., Ghodsi, A., Hong, S. A., Konwinski, A., Murching, S., Nykodym, T., Ogilvie, P., Parkhe, M., Xie, F., and Zumar, C · 2018
Cited alongside, same era.
Optuna: A next-generation hyperparameter optimization framework
Akiba, T., Sano, S., Yanase, T., Ohta, T., and Koyama, M · 2019
Cited alongside, same era.
Pytorch: An imperative style, high-performance deep learning library
Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., et al · 2019
Cited alongside, same era.
Katib: A distributed general automl platform on kubernetes
Zhou, J., Velichkevich, A., Prosvirov, K., Garg, A., Oshima, Y., and Dutta, D · 2019
Cited alongside, same era.
https://github.com/pingcap/chaos-mesh
A Chaos Engineering Platform for Kubernetes, 2020 · 2020
Cited alongside, same era.
Automatic Car Damage Assessment System: Reading and Understanding Videos as Professional Insurance Inspectors
Zhang, W., Cheng, Y., Guo, X., et al
Cited in the paper.
2020
Closest in time.
https://github.com/microsoft/pai
Resource scheduling and cluster management for AI, 2020 · 2020
Closest in time.
Ant Financial’s Hypergrowth Strategy Using Kubernetes, 2020
Financial, A · 2020
Closest in time.
https://github.com/kubeflow/katib
Katib in Kubeflow, 2020 · 2020
Closest in time.
MPI Operator in Kubeflow, 2020
Ou, R., Tang, Y., et al · 2020
Closest in time.