DeepAI AI Chat
Log In Sign Up

Bayesian Batch Active Learning as Sparse Subset Approximation

08/06/2019
by   Robert Pinsler, et al.
University of Cambridge
1

Leveraging the wealth of unlabeled data produced in recent years provides great potential for improving supervised models. When the cost of acquiring labels is high, probabilistic active learning methods can be used to greedily select the most informative data points to be labeled. However, for many large-scale problems standard greedy procedures become computationally infeasible and suffer from negligible model change. In this paper, we introduce a novel Bayesian batch active learning approach that mitigates these issues. Our approach is motivated by approximating the complete data posterior of the model parameters. While naive batch construction methods result in correlated queries, our algorithm produces diverse batches that enable efficient active learning at scale. We derive interpretable closed-form solutions akin to existing active learning procedures for linear models, and generalize to arbitrary models using random projections. We demonstrate the benefits of our approach on several large-scale regression and classification tasks.

READ FULL TEXT

page 1

page 2

page 3

page 4

04/16/2021

Data Shapley Valuation for Efficient Batch Active Learning

Annotating the right set of data amongst all available data points is a ...
11/01/2022

Batch Active Learning from the Perspective of Sparse Approximation

Active learning enables efficient model training by leveraging interacti...
02/17/2023

Black-Box Batch Active Learning for Regression

Batch active learning is a popular approach for efficiently training mac...
02/08/2022

A Lagrangian Duality Approach to Active Learning

We consider the batch active learning problem, where only a subset of th...
02/18/2020

Information Condensing Active Learning

We introduce Information Condensing Active Learning (ICAL), a batch mode...
11/27/2020

Active Learning in CNNs via Expected Improvement Maximization

Deep learning models such as Convolutional Neural Networks (CNNs) have d...
01/02/2023

Using Active Learning Methods to Strategically Select Essays for Automated Scoring

Research on automated essay scoring has become increasing important beca...