$(varphi_1, varphi_2)$-variational principle

Variational Principle

Variational principle for probabilistic learning Yet another justification More simplification of updates for mean-field family Examples Dirichlet Process Mixture On minimization of divergence measures Energy minimization justifications Variational learning with exponential family Mean parametrization and marginal polytopes Convex dualities The log-partition function and conjugate duality Belie...

Variational Principle for

We show that some measures suuering from the so-called Renormalization Group pathologies satisfy a variational principle and that the corresponding limit of the pressure, with boundary conditions in a set of measure 1, is proportional to the pressure of the Ising model.

An extended variational principle

On the Variational Principle

The variational principle states that if a differentiable functional F attains its minimum at some point zi, then F’(C) = 0; it has proved a valuable tool for studying partial differential equations. This paper shows that if a differentiable function F has a finite lower bound (although it need not attain it), then, for every E > 0, there exists some point u( where 11 F’(uJj* < l , i.e., its de...

Parametric variational principle and residuality

We prove a parametric version of a smooth convex variational principle with constraints using a Baire category approach. We examine in depth the necessity of the assumptions of our variational principle by providing counterexamples.

A Variational Principle for Permutations

We define an entropy function for scaling limits of permutations, called permutons, and prove that under appropriate circumstances, both the shape and number of large permutations with given constraints are determined by maximizing entropy over permutons with those constraints. We also describe a useful equivalent version of permutons using a recursive construction. This variational principle i...