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Jan
6
comment Is the logarithm of sum of multiple variables with the constraint on sum of them Concave?
@MichaelGrant yes. I edit the question title to make the question more formally. In fact in machine learning field saying Convex implies the meaning of being "Convex or Concave" BTW I am sorry if the title was not clear.
Jan
6
comment Is the logarithm of sum of multiple variables with the constraint on sum of them Concave?
the second derivative of log(1+x) is -1/((1+x)^2) which is always <0 for x>=0 and x<=1 and so it is concave. I think I missed the point on how this is not a concave function.
Jan
6
comment Is the logarithm of sum of multiple variables with the constraint on sum of them Concave?
Oh, I edit my question 25 minute ago and you answered it 22 minute ago. so you may didn't see the edit to the question:"constraint that ∑i=1:1:mαi=1∑i=1:1:mαi=1 and they are positive". I am really sorry
Jan
6
comment Is the logarithm of sum of multiple variables with the constraint on sum of them Concave?
thanks Giuseppe, But I didn't catch your idea exactly. we know that x>=0 and x<=1. so you say that log(x+1) is not convex for 0<=x<=1?
Jan
5
comment is this function an ill-shape convex function?
thanks for your reply. i edit the question to be more obvious(it has a little typo also). also yes, all things except the alphas are simple constants
Jan
4
comment is this function an ill-shape convex function?
I have deleted the old question because I think that this question(new one) makes sense better
Sep
14
comment right way of weighting sampling for a distribution?
yes, Thank you a lot.@joriki
Sep
14
comment right way of weighting sampling for a distribution?
I think there was an answer here which is deleted now. unfortunately I didn't read it.
Sep
14
comment right way of weighting sampling for a distribution?
@joriki yes, You are right I should provide the reference too. thanks.
Sep
4
comment How to calcute the inverse Laplace transform of $\hat{F}(z)=\sum_{i=0}^{\infty} \frac{A^{i}}{z^{i+1}}$
very nice answer.thank you a lot
Jul
19
comment EM algorithm with constrained equation
I edit the question and add the paper link.thanks
Jul
19
comment Dirichlet distribution when parameters $\rightarrow\infty$
Great answer.thanks
Feb
6
comment Fail to understand elementary matrices properties in matrix LU factorization.
thanks for your explanation dear Marc. Honestly I didn't completely get it yet.can you provide me an example please?
Nov
23
comment Problem with with derivative of integral
I think this question is just about derivation of an integral on a variable.
Nov
23
comment Problem with with derivative of integral
we define z=xy . z is new R.V
Nov
23
comment Problem with with derivative of integral
'f' is probability density function and 'F' is cumulative distribution function.although I think it is not helping to know about F and f in order to solve the above formulation.
Nov
25
comment has deleting node in a binary search tree Displacement feature?
deleting means that for example detele('4') removes node with key 4 from our tree.
Nov
25
comment has deleting node in a binary search tree Displacement feature?
a simple binary search tree keys in all nodes(include leaves).being balance is not required.
Oct
12
comment implicit equation for covering a $3\times{n}$ face with $2\times{1}$ mosaics with recursion solution?
thanks Brian for your complete and step by step solution.i learned it good.also i will plan to read the materials that you suggested
Oct
12
comment implicit equation for covering a $3\times{n}$ face with $2\times{1}$ mosaics with recursion solution?
i used implicit for terms like that i wrote in my post and explicit for a single term for example a0(k0)^n