Tianqi Chen is an Assistant Professor in the Machine Learning Department and Computer Science Department at Carnegie Mellon University and the Chief Technologist of OctoML. His research focuses on the intersection of machine learning and systems.
Tianqi's PhD thesis is titled "Scalable and Intelligent Learning Systems," which he completed in 2019 at the University of Washington. We discuss his influential work on machine learning systems, starting with the development of XGBoost,an optimized distributed gradient boosting library that has had an enormous impact in the field. We also cover his contributions to deep learning frameworks like MXNet and machine learning compilation with TVM, and connect these to modern generative AI.
- Episode notes: www.wellecks.com/thesisreview/episode48.html
- Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter
- Follow Tianqi Chen on Twitter (@tqchenml)
- Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview
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Tianqi Chen is an Assistant Professor in the Machine Learning Department and Computer Science Department at Carnegie Mellon University and the Chief Technologist of OctoML. His research focuses on the intersection of machine learning and systems.
Tianqi's PhD thesis is titled "Scalable and Intelligent Learning Systems," which he completed in 2019 at the University of Washington. We discuss his influential work on machine learning systems, starting with the development of XGBoost,an optimized distributed gradient boosting library that has had an enormous impact in the field. We also cover his contributions to deep learning frameworks like MXNet and machine learning compilation with TVM, and connect these to modern generative AI.
- Episode notes: www.wellecks.com/thesisreview/episode48.html
- Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter
- Follow Tianqi Chen on Twitter (@tqchenml)
- Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview
[45] Luke Zettlemoyer - Learning to Map Sentences to Logical Form
The Thesis Review
59 minutes 35 seconds
2 years ago
[45] Luke Zettlemoyer - Learning to Map Sentences to Logical Form
Luke Zettlemoyer is a Professor at the University of Washington and Research Scientist at Meta. His work spans machine learning and NLP, including foundational work in large-scale self-supervised pretraining of language models.
Luke's PhD thesis is titled "Learning to Map Sentences to Logical Form", which he completed in 2009 at MIT. We talk about his PhD work, the path to the foundational Elmo paper, and various topics related to large language models.
- Episode notes: www.wellecks.com/thesisreview/episode45.html
- Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter
- Find out more info about the show at www.wellecks.com/thesisreview
- Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview
The Thesis Review
Tianqi Chen is an Assistant Professor in the Machine Learning Department and Computer Science Department at Carnegie Mellon University and the Chief Technologist of OctoML. His research focuses on the intersection of machine learning and systems.
Tianqi's PhD thesis is titled "Scalable and Intelligent Learning Systems," which he completed in 2019 at the University of Washington. We discuss his influential work on machine learning systems, starting with the development of XGBoost,an optimized distributed gradient boosting library that has had an enormous impact in the field. We also cover his contributions to deep learning frameworks like MXNet and machine learning compilation with TVM, and connect these to modern generative AI.
- Episode notes: www.wellecks.com/thesisreview/episode48.html
- Follow the Thesis Review (@thesisreview) and Sean Welleck (@wellecks) on Twitter
- Follow Tianqi Chen on Twitter (@tqchenml)
- Support The Thesis Review at www.patreon.com/thesisreview or www.buymeacoffee.com/thesisreview
