# Questions tagged [bayesian-probability]

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### Derive equation for regularized logistic regression with batch updates

I am trying to understand this paper by Chapelle and Li "An Empirical Evaluation of Thompson Sampling" (2011). In particular, I am failing to derive the equations in algorithm 3 (page 6). ...
35 views

### Concentration of posterior probability around a tiny fraction of the prior volume

In the context of approximating the evidence $Z$ in a Bayesian inference setting $$Z = \int d\theta \mathcal L (\theta)\pi (\theta)$$ with $\mathcal L$ the likelihood, $\pi$ the prior, John Skilling'...
1 vote
80 views

### Bayesian inverse problems on non-separable Banach spaces

I am now studying Bayesian inverse problems. In the note of Dashti and Stuart https://arxiv.org/abs/1302.6989, they mentioned that "... when considering a non-separable Banach space $B$, it is ...
1 vote
70 views

### Conditional Gaussians in infinite dimensions

I asked this over on cross validated, but thought it might also get an answer here: The law of the conditional Gaussian distribution (the mean and covariance) are frequently mentioned to extend to the ...
39 views

### Bayesian hierarchical model inference - real problem

it might be really confusing question. I am working on my thesis and I am stuck at a problem. It's a problem in image segmentation and finding parameters of border lines of continuous region in an ...
200 views

### Do these distributions have a name already?

In playing with some math finance stuff I ran into the following distribution and I was curious if someone had a name for it or has studied it or worked with it already. To start, let $\Delta^n$ be ...
245 views

1 vote
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1 vote
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### The expectation of binary logistics regression with respect to Gaussian distribution

I am trying to compute the expectation of $g(s,x)=s \ln \sigma(x)+(1-s)\ln(1-\sigma(x))$ with respect to the normal distribution $\mathcal{N}(x;m,v)$, where we have $\sigma(x)=\frac{1}{1+e^{-x}}$. If ...
1 vote
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### Learning a Gaussian from noisy observations

Is it possible to learn a distribution over the parameters ($K=\Sigma^{-1}$ and $\mu$) of a Gaussian from noisy measurements of $X$? (Starting with some appropriate prior over the parameters) I know ...
365 views

1 vote