17 citations · 18 across the 5 of their papers we have counts for
5 papers
Tytan: Interactive Neurosymbolic Construction of Analytic Semantic Schemas from Relational Data
Donna Hooshmand, Shubham Shahi, Cameron Barrie +4
From natural-language query interfaces to automated report generation, data analysis tools need a description of the data: the real-world entities it contains, which columns functi…
Satyrn: A Platform for Analytics Augmented Generation
Marko Sterbentz, Cameron Barrie, Shubham Shahi +4
Large language models (LLMs) are capable of producing documents, and retrieval augmented generation (RAG) has shown itself to be a powerful method for improving accuracy without sa…
Lightweight Knowledge Representations for Automating Data Analysis
Marko Sterbentz, Cameron Barrie, Donna Hooshmand +7
The principal goal of data science is to derive meaningful information from data. To do this, data scientists develop a space of analytic possibilities and from it reach their info…
On Robustness to Adversarial Examples and Polynomial Optimization
Pranjal Awasthi, Abhratanu Dutta, Aravindan Vijayaraghavan
We study the design of computationally efficient algorithms with provable guarantees, that are robust to adversarial (test time) perturbations. While there has been an proliferatio…
Clustering Stable Instances of Euclidean k-means
Abhratanu Dutta, Aravindan Vijayaraghavan, Alex Wang
The Euclidean k-means problem is arguably the most widely-studied clustering problem in machine learning. While the k-means objective is NP-hard in the worst-case, practitioners ha…