# A melhor ferramenta para a sua pesquisa, trabalho e TCC!

## Bayesian optimization for materials design

## A Bayesian Network View on Acoustic Model-Based Techniques for Robust Speech Recognition

## Being Bayesian about Network Structure

## Accuracy of Latent-Variable Estimation in Bayesian Semi-Supervised Learning

## Inference-less Density Estimation using Copula Bayesian Networks

## Fast Learning of Relational Dependency Networks

## Local Structure Discovery in Bayesian Networks

## Optimally-Weighted Herding is Bayesian Quadrature

## Scalable Bayesian Inference via Particle Mirror Descent

## Revisiting k-means: New Algorithms via Bayesian Nonparametrics

## Infinite Shift-invariant Grouped Multi-task Learning for Gaussian Processes

## Bayesian Nonparametric Hidden Semi-Markov Models

## A PAC-Bayesian bound for Lifelong Learning

## Compound Poisson Processes, Latent Shrinkage Priors and Bayesian Nonconvex Penalization

## Constrained Bayesian Inference for Low Rank Multitask Learning

## Phase transitions in optimal unsupervised learning

## Hamiltonian ABC

## Unstable Consumer Learning Models: Structural Estimation and Experimental Examination

This dissertation explores how consumers learn from repeated experiences with a product offering. It develops a new Bayesian consumer learning model, the unstable learning model. This model expands on existing models that explore learning when quality is stable, by considering when quality is changing. Further, the dissertation examines situations in which consumers may act as if quality is changing when it is stable or vice versa. This examination proceeds in two essays.

The first essay uses two experiments to examine how consumers learn when product quality is stable or changing. By collecting repeated measures of expectation data and experiences, more information enables estimation to discriminate between stable and unstable learning. The key conclusions are that (1) most consumers act as if quality is unstable, even when it is stable, and (2) consumers respond to the environment they face, adjusting their learning in the correct direction. These conclusions have important implications for the formation and value of brand equity.

Based on the conclusions of this first essay, the second essay develops a choice model of consumer learning when consumers believe quality is changing, even though it is not. A Monte Carlo experiment tests the efficacy of this model versus the standard model. The key conclusion is that both models perform similarly well when the model assumptions match the way consumers actually learn...