283 citations · 2.1k across the 112 of their papers we have counts for
5 papers · 1 filter
Solving Constrained CASH Problems with ADMM
Parikshit Ram, Sijia Liu, Deepak Vijaykeerthi +5
The CASH problem has been widely studied in the context of automated configurations of machine learning (ML) pipelines and various solvers and toolkits are available. However, CASH…
DeepBrain: Towards Personalized EEG Interaction through Attentional and Embedded LSTM Learning
Di Wu, Huayan Wan, Siping Liu +3
The "mind-controlling" capability has always been in mankind's fantasy. With the recent advancements of electroencephalograph (EEG) techniques, brain-computer interface (BCI) resea…
Trust in AutoML: Exploring Information Needs for Establishing Trust in Automated Machine Learning Systems
Jaimie Drozdal, Justin Weisz, Dakuo Wang +6
We explore trust in a relatively new area of data science: Automated Machine Learning (AutoML). In AutoML, AI methods are used to generate and optimize machine learning models by a…
AutoAIViz: Opening the Blackbox of Automated Artificial Intelligence with Conditional Parallel Coordinates
Daniel Karl I. Weidele, Justin D. Weisz, Eno Oduor +4
Artificial Intelligence (AI) can now automate the algorithm selection, feature engineering, and hyperparameter tuning steps in a machine learning workflow. Commonly known as AutoML…
How do Data Science Workers Collaborate? Roles, Workflows, and Tools
Amy X. Zhang, Michael Muller, Dakuo Wang
Today, the prominence of data science within organizations has given rise to teams of data science workers collaborating on extracting insights from data, as opposed to individual…