Search Results for author: Micah J. Smith

Found 5 papers, 3 papers with code

Do We Still Need Clinical Language Models?

no code implementations16 Feb 2023 Eric Lehman, Evan Hernandez, Diwakar Mahajan, Jonas Wulff, Micah J. Smith, Zachary Ziegler, Daniel Nadler, Peter Szolovits, Alistair Johnson, Emily Alsentzer

To investigate this question, we conduct an extensive empirical analysis of 12 language models, ranging from 220M to 175B parameters, measuring their performance on 3 different clinical tasks that test their ability to parse and reason over electronic health records.

In-Context Learning

Enabling Collaborative Data Science Development with the Ballet Framework

3 code implementations14 Dec 2020 Micah J. Smith, Jürgen Cito, Kelvin Lu, Kalyan Veeramachaneni

While the open-source software development model has led to successful large-scale collaborations in building software systems, data science projects are frequently developed by individuals or small teams.

Feature Engineering

AutoML to Date and Beyond: Challenges and Opportunities

no code implementations21 Oct 2020 Shubhra Kanti Karmaker Santu, Md. Mahadi Hassan, Micah J. Smith, Lei Xu, ChengXiang Zhai, Kalyan Veeramachaneni

AutoML tools aim to make machine learning accessible for non-machine learning experts (domain experts), to improve the efficiency of machine learning, and to accelerate machine learning research.

AutoML BIG-bench Machine Learning

The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development

8 code implementations22 May 2019 Micah J. Smith, Carles Sala, James Max Kanter, Kalyan Veeramachaneni

To address these problems, we introduce the Machine Learning Bazaar, a new framework for developing machine learning and automated machine learning software systems.

AutoML Bayesian Optimization +1

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