Pages that link to "Item:Q5124430"

The following pages link to Mutual Information and Optimality of Approximate Message-Passing in Random Linear Estimation (Q5124430):

Displaying 20 items.

• An estimate of mutual information that permits closed-form optimisation (Q742718) (← links)
• The distribution of the Lasso: uniform control over sparse balls and adaptive parameter tuning (Q2054498) (← links)
• The all-or-nothing phenomenon in sparse linear regression (Q2078961) (← links)
• Fundamental barriers to high-dimensional regression with convex penalties (Q2119224) (← links)
• Strong replica symmetry in high-dimensional optimal Bayesian inference (Q2159230) (← links)
• Phase transition in random tensors with multiple independent spikes (Q2240871) (← links)
• The adaptive interpolation method: a simple scheme to prove replica formulas in Bayesian inference (Q2312689) (← links)
• Phase transition in the spiked random tensor with Rademacher prior (Q2328058) (← links)
• Fundamental limits of weak recovery with applications to phase retrieval (Q2420637) (← links)
• Some relations between mutual information and estimation error in Wiener space (Q2456053) (← links)
• Remarks on the interpolation method (Q2658887) (← links)
• Approximate Solutions of Lagrange Multipliers for Information-Theoretic Random Field Models (Q2945169) (← links)
• On the Information Loss of the Max-Log Approximation in BICM Systems (Q2976748) (← links)
• A Bregman Matrix and the Gradient of Mutual Information for Vector Poisson and Gaussian Channels (Q2986374) (← links)
• Gradient of mutual information in linear vector Gaussian channels (Q3547462) (← links)
• Mutual Information, Relative Entropy and Estimation Error in Semi-Martingale Channels (Q4682943) (← links)
• Information theoretic limits of learning a sparse rule (Q5078669) (← links)
• Individually Conditional Individual Mutual Information Bound on Generalization Error (Q5088470) (← links)
• (Q5381124) (← links)
• The TAP free energy for high-dimensional linear regression (Q6109921) (← links)