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10/13/2022
Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning
Unlabeled data examples awaiting annotations contain open-set noise inev...
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06/09/2022
Adaptive Model Pooling for Online Deep Anomaly Detection from a Complex Evolving Data Stream
Online anomaly detection from a data stream is critical for the safety a...
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03/19/2022
Meta-Learning for Online Update of Recommender Systems
Online recommender systems should be always aligned with users' current ...
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12/13/2021
Data Collection and Quality Challenges in Deep Learning: A Data-Centric AI Perspective
Software 2.0 is a fundamental shift in software engineering where machin...
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12/09/2020
Accurate and Fast Federated Learning via IID and Communication-Aware Grouping
Federated learning has emerged as a new paradigm of collaborative machin...
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12/08/2020
Two-Phase Learning for Overcoming Noisy Labels
To counter the challenge associated with noise labels, the learning stra...
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12/06/2020
TornadoAggregate: Accurate and Scalable Federated Learning via the Ring-Based Architecture
Federated learning has emerged as a new paradigm of collaborative machin...
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07/16/2020
Learning from Noisy Labels with Deep Neural Networks: A Survey
Deep learning has achieved remarkable success in numerous domains with h...
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11/19/2019
Prestopping: How Does Early Stopping Help Generalization against Label Noise?
Noisy labels are very common in real-world training data, which lead to ...
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11/19/2019
Carpe Diem, Seize the Samples Uncertain "At the Moment" for Adaptive Batch Selection
The performance of deep neural networks is significantly affected by how...
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10/23/2019
MLAT: Metric Learning for kNN in Streaming Time Series
Learning a good distance measure for distance-based classification in ti...
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05/08/2018
