Robust Fuzzy Multi-view Learning under View Conflict
Trusted multi-view classification aims to deliver reliable fusion for accurate predictions and has recently attracted substantial attention in both academia and industry. However, existing TMVC methods typically assume strict alignment across different views during both training and testing phases, which is often impractical in real-world scenarios. This limitation motivates us to revisit TMVC and extend it to a more challenging setting: how to mitigate the impact of view conflict (VC) during bo
Record details
Published: 23 May 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Finance, VC & PE
Retrieved: 14 July 2026
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ethics.ai (23 May 2026), “Robust Fuzzy Multi-view Learning under View Conflict,” evidence record 3826, https://ethics.ai/record/3826 (originally published by arXiv).
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