Transactions on Machine Learning Research
 | Transact Mach Learn Res. doesn't exist. |
| Transact Mach Learn Res doesn't exist. |
| Discipline | Machine Learning |
|---|---|
| Language | English |
| Edited by | Kyunghyun Cho, Gautam Kamath, Hugo Larochelle, Naila Murray |
| Publication details | |
Publication history | 2022-present |
| Publisher | Journal of Machine Learning Research Inc. |
| Yes | |
| Standard abbreviations | |
| Transact Mach Learn Res. | |
| Indexing | |
| ISSN | 2835-8856 |
| Links | |
Search Transactions on Machine Learning Research on Amazon.
Transactions on Machine Learning Research (TMLR) is a peer-reviewed open access scientific journal covering machine learning. It is a sister journal of the Journal on Machine Learning Research and was established in 2022. The journal was founded by Hugo Larochelle, Kyunghyun Cho, and Raia Hadsell.[1]
The advisory board includes Yoshua Bengio, Andrew McCallum, Bernhard Schölkopf and Lillian Lee (computer scientist).
History
The journal was founded with the aim of providing fast, conference-style review cycles and aims to prioritize novelty and scientific correctness over subjective significance.
The journal offers several awards, including an Outstanding Paper Certification and a Featured Paper Certification. In 2024, authors of papers awarded one of these certifications were invited to present their research in poster format at the International Conference on Learning Representations.[2]
References
- ↑ "dblp: Transactions on Machine Learning Research, Volume 2022". dblp.org. Retrieved 2024-06-30.
- ↑ Sun, Yizhou (2023-10-06). "Authors of TMLR publications with Featured and Outstanding Certifications at ICLR 2024 – ICLR Blog". Retrieved 2024-06-30.
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