Causal stability selection produces effect-modifier sets with explicit non-asymptotic false-positive bounds by combining cross-fitted CATE estimation and integrated path stability selection.
Econometrica: Journal of the Econometric Society , pages=
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A Neyman-orthogonal estimator paired with Lasso nuisance estimation achieves root-T asymptotic normality for BLP demand parameters under high-dimensional controls and approximate sparsity.
In untrusted strategic settings with unreliable measurements, the quantum primitive for output-hiding function sharing permits parties to generate private unbiased coins.
Proposes a quantum primitive for output-hiding function sharing with applications to enhanced QKD security and hidden joint function encoding.
citing papers explorer
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Causal Stability Selection
Causal stability selection produces effect-modifier sets with explicit non-asymptotic false-positive bounds by combining cross-fitted CATE estimation and integrated path stability selection.
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Estimation of BLP models with high-dimensional controls
A Neyman-orthogonal estimator paired with Lasso nuisance estimation achieves root-T asymptotic normality for BLP demand parameters under high-dimensional controls and approximate sparsity.
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Quantum Primitive for Output-Hiding Function Sharing: Strategic Settings
In untrusted strategic settings with unreliable measurements, the quantum primitive for output-hiding function sharing permits parties to generate private unbiased coins.
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Quantum Primitive for Output-Hiding Function Sharing: QKD and Joint Computation Applications
Proposes a quantum primitive for output-hiding function sharing with applications to enhanced QKD security and hidden joint function encoding.