AutoML is dead an LLMs have killed it? MLGym is a benchmark and framework testing this theory. Roberta Raileanu and Deepak Nathani discuss how well current LLMs are doing at solving ML tasks, what the biggest roadblocks are, and what that means for AutoML generally. Check out the paper: https://arxiv.org/pdf/2502.14499 More on Roberta: https://rraileanu.github.io/ More on Deepak: https://dnathani.net/
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AutoML is dead an LLMs have killed it? MLGym is a benchmark and framework testing this theory. Roberta Raileanu and Deepak Nathani discuss how well current LLMs are doing at solving ML tasks, what the biggest roadblocks are, and what that means for AutoML generally. Check out the paper: https://arxiv.org/pdf/2502.14499 More on Roberta: https://rraileanu.github.io/ More on Deepak: https://dnathani.net/
How to Design an AutoML System using Error Decomposition
The AutoML Podcast
28 minutes
2 years ago
How to Design an AutoML System using Error Decomposition
Today we're talking with Caitlin Owen, a post-doc at the University of Otago about her work on error decomposition. She recently published a paper titled "Towards Explainable AutoML Using Error Decomposition" about how a more granular view of the components of error can lead the construction of better AutoML systems. Read her paper here: https://link.springer.com/chapter/10.1007/978-3-031-22695-3_13 Follow her on Twitter here: @CaitAshfordOwen Connect with her on LinkedIn here: https://www...
The AutoML Podcast
AutoML is dead an LLMs have killed it? MLGym is a benchmark and framework testing this theory. Roberta Raileanu and Deepak Nathani discuss how well current LLMs are doing at solving ML tasks, what the biggest roadblocks are, and what that means for AutoML generally. Check out the paper: https://arxiv.org/pdf/2502.14499 More on Roberta: https://rraileanu.github.io/ More on Deepak: https://dnathani.net/
