7 papers
ModelLakeFishing: Efficient Retrieval over Million-Scale Model Lakes
Xiaoyang Liu, Zhengyuan Dong, Renée J. Miller
Open model lakes may contain millions of reusable models, making it costly to identify suitable models for a new dataset. We present ModelLakeFishing, a model-retrieval framework f…
Diversed Model Discovery via Structured Table Discovery
Zhengyuan Dong, Renée J. Miller
Model cards describe model behavior through a mixture of textual descriptions and structured artifacts, including performance, configuration, and dataset tables. Existing model sea…
Novel Table Search [Technical Report]
Besat Kassaie, Renée J. Miller
Avoiding redundancy in query results has been extensively studied in relational databases and information retrieval, yet its implications for data lakes remain largely unexplored.…
Diverse Unionable Tuple Search: Novelty-Driven Discovery in Data Lakes [Technical Report]
Aamod Khatiwada, Roee Shraga, Renée J. Miller
Unionable table search techniques input a query table from a user and search for data lake tables that can contribute additional rows to the query table. The definition of unionabi…
Fuzzy Integration of Data Lake Tables
Aamod Khatiwada, Roee Shraga, Renée J. Miller
Data integration is an important step in any data science pipeline where the objective is to unify the information available in different datasets for comprehensive analysis. Full…
Gen-T: Table Reclamation in Data Lakes
Grace Fan, Roee Shraga, Renée J. Miller
We introduce the problem of Table Reclamation. Given a Source Table and a large table repository, reclamation finds a set of tables that, when integrated, reproduce the source tabl…
Model Lakes
Koyena Pal, David Bau, Renée J. Miller
Given a set of deep learning models, it can be hard to find models appropriate to a task, understand the models, and characterize how models are different one from another. Current…