Neural Architecture Search with Reinforcement Learning
The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.
this paper
works it cites
works citing it
node size = global citations · hover for the full title
Citation edge evidence
- Deep Reinforcement Learning: A Brief Survey→Neural Architecture Search with Reinforcement LearningLegacy edge — source detail unavailable
- Transformer-XL: Attentive Language Models beyond a Fixed-Length Context→Neural Architecture Search with Reinforcement LearningLegacy edge — source detail unavailable
- AutoML: A survey of the state-of-the-art→Neural Architecture Search with Reinforcement LearningLegacy edge — source detail unavailable
- Pre-trained models for natural language processing: A survey→Neural Architecture Search with Reinforcement LearningLegacy edge — source detail unavailable
- Automated Machine Learning→Neural Architecture Search with Reinforcement LearningLegacy edge — source detail unavailable
- Neural Architecture Search with Reinforcement Learning→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Neural Architecture Search with Reinforcement Learning→Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…Legacy edge — source detail unavailable
- Neural Architecture Search with Reinforcement Learning→Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Fou…Legacy edge — source detail unavailable
- Neural Architecture Search with Reinforcement Learning→Simple statistical gradient-following algorithms for connectionist reinforcement learningLegacy edge — source detail unavailable
- Neural Architecture Search with Reinforcement Learning→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
- Neural Architecture Search with Reinforcement Learning→Human-level concept learning through probabilistic program inductionLegacy edge — source detail unavailable
- Neural Architecture Search with Reinforcement Learning→Recurrent Neural Network RegularizationLegacy edge — source detail unavailable
- Neural Architecture Search with Reinforcement Learning→Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions f…Legacy edge — source detail unavailable
- Human-level concept learning through probabilistic program induction→Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Fou…Legacy edge — source detail unavailable
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Sh…→On the importance of initialization and momentum in deep learningLegacy edge — source detail unavailable
- AutoML: A survey of the state-of-the-art→Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions f…Legacy edge — source detail unavailable
- AutoML: A survey of the state-of-the-art→Simple statistical gradient-following algorithms for connectionist reinforcement learningLegacy edge — source detail unavailable
- AutoML: A survey of the state-of-the-art→Transformer-XL: Attentive Language Models beyond a Fixed-Length ContextLegacy edge — source detail unavailable
- AutoML: A survey of the state-of-the-art→[No title in the source record — DROPS (Schloss Dagstuhl – Leibniz Center for Informatics…Legacy edge — source detail unavailable
- Pre-trained models for natural language processing: A survey→Transformer-XL: Attentive Language Models beyond a Fixed-Length ContextLegacy edge — source detail unavailable
- Deep Reinforcement Learning: A Brief Survey→Simple statistical gradient-following algorithms for connectionist reinforcement learningLegacy edge — source detail unavailable
- Automated Machine Learning→Making a Science of Model Search: Hyperparameter Optimization in Hundreds of Dimensions f…Legacy edge — source detail unavailable
What this paper cites, inside the corpus
What cites it, inside the corpus
| Paper | Year | Cited |
|---|---|---|
| Deep Reinforcement Learning: A Brief Survey | 2017 | 4,434 |
| Transformer-XL: Attentive Language Models beyond a Fixed-Length Context | 2019 | 3,202 |
| AutoML: A survey of the state-of-the-art | 2020 | 1,705 |
| Pre-trained models for natural language processing: A survey | 2020 | 1,521 |
| Automated Machine Learning | 2019 | 1,451 |
Links
Download BibTeX · Download RIS · DOI · Open access copy · OpenAlex record
Topics
| Machine Learning and Data Classification | Computer Science |
| Anomaly Detection Techniques and Applications | Computer Science |
| Neural Networks and Applications | Computer Science |
Is this record sound?
complete
Nothing in this record contradicts itself and no field we check is missing.
- supports2 author record(s) attached.
- supports45 reference(s) recorded.
- neutralThe DOI carries no year to check against.
- supportsA title is present.
Provenance
sha256 bba2969b3567609a…