Streaming Active Learning with Deep Neural Networks

• URL: http://arxiv.org/abs/2303.02535v2
• Date: Tue, 6 Jun 2023 23:34:01 GMT
• Title: Streaming Active Learning with Deep Neural Networks
• Authors: Akanksha Saran, Safoora Yousefi, Akshay Krishnamurthy, John Langford, Jordan T. Ash
• Abstract summary: We propose VeSSAL, a new algorithm for batch active learning with deep neural networks in streaming settings. VeSSAL samples groups of points to query for labels at the moment they are encountered. We expand the applicability of deep neural networks to realistic active learning scenarios.
• Score: 44.50018541065145
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Active learning is perhaps most naturally posed as an online learning problem. However, prior active learning approaches with deep neural networks assume offline access to the entire dataset ahead of time. This paper proposes VeSSAL, a new algorithm for batch active learning with deep neural networks in streaming settings, which samples groups of points to query for labels at the moment they are encountered. Our approach trades off between uncertainty and diversity of queried samples to match a desired query rate without requiring any hand-tuned hyperparameters. Altogether, we expand the applicability of deep neural networks to realistic active learning scenarios, such as applications relevant to HCI and large, fractured datasets.

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