166 citations · 1.4k across the 47 of their papers we have counts for
25 papers · 1 filter
Accelerating Batch Active Learning Using Continual Learning Techniques
Arnav Das, Gantavya Bhatt, Megh Bhalerao +3
A major problem with Active Learning (AL) is high training costs since models are typically retrained from scratch after every query round. We start by demonstrating that standard…
Online SuBmodular + SuPermodular (BP) Maximization with Bandit Feedback
Adhyyan Narang, Omid Sadeghi, Lillian J Ratliff +2
In the context of online interactive machine learning with combinatorial objectives, we extend purely submodular prior work to more general non-submodular objectives. This includes…
Submodularity In Machine Learning and Artificial Intelligence
Jeff Bilmes
In this manuscript, we offer a gentle review of submodularity and supermodularity and their properties. We offer a plethora of submodular definitions; a full description of a numbe…
An Effective Baseline for Robustness to Distributional Shift
Sunil Thulasidasan, Sushil Thapa, Sayera Dhaubhadel +3
Refraining from confidently predicting when faced with categories of inputs different from those seen during training is an important requirement for the safe deployment of deep le…
Submodular Mutual Information for Targeted Data Subset Selection
Suraj Kothawade, Vishal Kaushal, Ganesh Ramakrishnan +2
With the rapid growth of data, it is becoming increasingly difficult to train or improve deep learning models with the right subset of data. We show that this problem can be effect…
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…