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arXiv Machine Learning By Huang Weiquan

Resolving Multi-Modal Regression by Difference-Quotient-Based Clustering:Fast Coarse Conditional-Label Assignment

Read the original on arXiv Machine Learning →

The paper introduces Difference‑Quotient Clustering (DQC) to address mean‑collapse in multimodal regression. DQC partitions data by minimizing intra‑cluster output‑vs‑input discrepancy, assigning each sample to the cluster with the lowest maximum contradiction ratio. The resulting cluster labels train a logits generator and conditional network, achieving lower minimum squared error on synthetic benchmarks compared to random labeling and mean‑collapse baselines.

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