A Markov-modeled maximum likelihood estimator for multi-look holographic reconstruction achieves near-ideal performance under strong inter-look speckle correlation by outperforming methods that assume independence.
Maximum likelihood from incomplete data via the em algorithm,
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
UNVERDICTED 2representative citing papers
Reveals hidden human-like spans in machine-generated texts that raise detection complexity and proposes a stacked enhancement framework with hard-EM optimization to improve detectors across LLMs.
citing papers explorer
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Maximum Likelihood Reconstruction for Multi-Look Digital Holography with Markov-Modeled Speckle Correlation
A Markov-modeled maximum likelihood estimator for multi-look holographic reconstruction achieves near-ideal performance under strong inter-look speckle correlation by outperforming methods that assume independence.
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Hidden Human-Like Nature of Machine-Generated Texts: Theory and Detection Enhancement
Reveals hidden human-like spans in machine-generated texts that raise detection complexity and proposes a stacked enhancement framework with hard-EM optimization to improve detectors across LLMs.