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Found 3 papers, 2 papers with code
Learning from Similar Linear Representations: Adaptivity, Minimaxity, and Robustness
With a known intrinsic dimension, we propose two algorithms that are \textit{adaptive} to the similarity structure and \textit{robust} to outlier tasks under both MTL and TL settings.
Identifiability of Hierarchical Latent Attribute Models
The key ingredients of an HLAM include a binary structural matrix and a directed acyclic graph specifying hierarchical constraints on the configurations of latent attributes.
Learning Attribute Patterns in High-Dimensional Structured Latent Attribute Models
Structured latent attribute models (SLAMs) are a special family of discrete latent variable models widely used in social and biological sciences.
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