71 citations · 168 across the 39 of their papers we have counts for
4 papers · 1 filter
GLISTER: Generalization based Data Subset Selection for Efficient and Robust Learning
Krishnateja Killamsetty, Durga Sivasubramanian, Ganesh Ramakrishnan +1
Large scale machine learning and deep models are extremely data-hungry. Unfortunately, obtaining large amounts of labeled data is expensive, and training state-of-the-art models (w…
A Unified Framework for Generic, Query-Focused, Privacy Preserving and Update Summarization using Submodular Information Measures
Vishal Kaushal, Suraj Kothawade, Ganesh Ramakrishnan +3
We study submodular information measures as a rich framework for generic, query-focused, privacy sensitive, and update summarization tasks. While past work generally treats these p…
Realistic Video Summarization through VISIOCITY: A New Benchmark and Evaluation Framework
Vishal Kaushal, Suraj Kothawade, Rishabh Iyer +1
Automatic video summarization is still an unsolved problem due to several challenges. We take steps towards making automatic video summarization more realistic by addressing them.…
Semi-Supervised Data Programming with Subset Selection
Ayush Maheshwari, Oishik Chatterjee, KrishnaTeja Killamsetty +2
The paradigm of data programming, which uses weak supervision in the form of rules/labelling functions, and semi-supervised learning, which augments small amounts of labelled data…