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Found 4 papers, 1 papers with code
Asymptotic convergence of iterative optimization algorithms
This paper introduces a general framework for iterative optimization algorithms and establishes under general assumptions that their convergence is asymptotically geometric.
Mixture weights optimisation for Alpha-Divergence Variational Inference
This paper focuses on $\alpha$-divergence minimisation methods for Variational Inference.
Monotonic Alpha-divergence Minimisation for Variational Inference
In this paper, we introduce a novel family of iterative algorithms which carry out $\alpha$-divergence minimisation in a Variational Inference context.
A Global Stochastic Optimization Particle Filter Algorithm
We introduce a new online algorithm for expected log-likelihood maximization in situations where the objective function is multi-modal and/or has saddle points, that we term G-PFSO.
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