For general convex learning tasks whose optima share a low-rank or clustered structure, this paper gives sample-complexity bounds for recovering that structure, including a one-sample-per-task regime where the number of tasks must be exponential in the rank.
Multi-task feature learning
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
Meta-learning of shared linear representations beyond well-specified linear regression
For general convex learning tasks whose optima share a low-rank or clustered structure, this paper gives sample-complexity bounds for recovering that structure, including a one-sample-per-task regime where the number of tasks must be exponential in the rank.