OK, the mention of sampling had me worried! That clears it up, thanks.
And thanks for the paper reference!



On Wed, Mar 25, 2015 at 3:53 PM, Andreas Mueller <t3k...@gmail.com> wrote:
> Even higher up, it compares variation, collapsed and truncated.
> So the variational does not need any sampling (which makes sense).
>
> Btw, this paper has a couple of references for more detailed equations:
> http://www.aaai.org/Papers/IJCAI/2007/IJCAI07-449.pdf
>
>
> On 03/25/2015 03:20 PM, Kyle Kastner wrote:
>> There was mention of TDP (blocked Gibbs higher up in the paper) vs
>> collapsed Gibbs sampling - both mentioned burn-in and lag. I was under
>> the impression you would have to be using one of these two to do the
>> computation, see page 137 of the paper just below the pictures, second
>> paragraph
>> http://www.cs.berkeley.edu/~jordan/papers/blei-jordan-ba.pdf
>>
>> I could be mistaken though, this paper is pretty gnarly!
>>
>> As far as handling missing values, that is an API concern that has not
>> been fleshed out yet. So I would not concentrate on it at this time,
>> other algorithms like low rank matrix completion would need to figure
>> this out before having the potential to be added. AKA what Andy said
>> (so fast at email!)
>>
>> On Wed, Mar 25, 2015 at 3:00 PM, Wei Xue <xuewe...@gmail.com> wrote:
>>> Ha, I just get confused about the sampling in DPGMM :).
>>>
>>>
>>> Wei Xue
>>>
>>> On Wed, Mar 25, 2015 at 2:57 PM, Andreas Mueller <t3k...@gmail.com> wrote:
>>>>
>>>>
>>>> On 03/24/2015 09:44 PM, Kyle Kastner wrote:
>>>>> Will users be allowed to set/tweak the burn-in and lag for the sampler
>>>>> in the DPGMM?
>>>>>
>>>> This is variational!
>>>>
>>>>
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