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4 papers · 2 filters
Causal Inference on Time Series using Structural Equation Models
Jonas Peters, Dominik Janzing, Bernhard Schölkopf
Causal inference uses observations to infer the causal structure of the data generating system. We study a class of functional models that we call Time Series Models with Independe…
A Nonparametric Conjugate Prior Distribution for the Maximizing Argument of a Noisy Function
Pedro A. Ortega, Jordi Grau-Moya, Tim Genewein +2
We propose a novel Bayesian approach to solve stochastic optimization problems that involve finding extrema of noisy, nonlinear functions. Previous work has focused on representing…
Free Energy and the Generalized Optimality Equations for Sequential Decision Making
Pedro A. Ortega, Daniel A. Braun
The free energy functional has recently been proposed as a variational principle for bounded rational decision-making, since it instantiates a natural trade-off between utility gai…
Fast projections onto mixed-norm balls with applications
Suvrit Sra
Joint sparsity offers powerful structural cues for feature selection, especially for variables that are expected to demonstrate a "grouped" behavior. Such behavior is commonly mode…