activity
20202023
most citedShare the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem

14 citations · 24 across the 4 of their papers we have counts for

collaborators

5 papers

cs.LG2023★ 2 cited

Natural Language Commanding via Program Synthesis

Apurva Gandhi, Thong Q. Nguyen, Huitian Jiao +2

We present Semantic Interpreter, a natural language-friendly AI system for productivity software such as Microsoft Office that leverages large language models (LLMs) to execute use…

cs.CL2022

SLATE: A Sequence Labeling Approach for Task Extraction from Free-form Inked Content

Apurva Gandhi, Ryan Serrao, Biyi Fang +8

We present SLATE, a sequence labeling approach for extracting tasks from free-form content such as digitally handwritten (or "inked") notes on a virtual whiteboard. Our approach al…

cs.DB2022★ 8 cited

The Tensor Data Platform: Towards an AI-centric Database System

Apurva Gandhi, Yuki Asada, Victor Fu +6

Database engines have historically absorbed many of the innovations in data processing, adding features to process graph data, XML, object oriented, and text among many others. In…

cs.DB2022★ 14 cited

Share the Tensor Tea: How Databases can Leverage the Machine Learning Ecosystem

Yuki Asada, Victor Fu, Apurva Gandhi +8

We demonstrate Tensor Query Processor (TQP): a query processor that automatically compiles relational operators into tensor programs. By leveraging tensor runtimes such as PyTorch,…

cs.CV2020

Adversarial Perturbations Fool Deepfake Detectors

Apurva Gandhi, Shomik Jain

This work uses adversarial perturbations to enhance deepfake images and fool common deepfake detectors. We created adversarial perturbations using the Fast Gradient Sign Method and…