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Initializing Services in Interactive ML Systems for Diverse Users
Neural Information Processing Systems
This paper investigates ML systems serving a group of users, with multiple models/services, each aimed at specializing to a sub-group of users.
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Adaptive Uncertainty Estimation via High-Dimensional Testing on Latent Representations
Neural Information Processing Systems
Uncertainty estimation aims to evaluate the confidence of a trained deep neural network.
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Federated Multi-Objective Learning
Neural Information Processing Systems
In recent years, multi-objective optimization (MOO) emerges as a foundational problem underpinning many multi-agent multi-task learning applications.
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