User mathhahaha

4 votes

1 answer

65 views

The sum of $O_p$ --$ O_p \left(s^2\frac{\log d}{n}+s\sqrt{\frac{\log d}{n}} \right) $

asked Jun 27 at 1:48

4 votes

0 answers

129 views

The deviation of the sample correlation matrix from its true value

asked Oct 26 at 14:00

3 votes

1 answer

100 views

Concentration inequality about the sum of covariance matrix

asked Oct 13 at 5:04

3 votes

2 answers

83 views

Estimate a vector $\beta=\underbrace{\beta_1}_{\text{sparse}}+\underbrace{\beta_2}_{\text{dense}}$

asked Nov 6 at 2:42

3 votes

0 answers

114 views

Does the loss function necessarily converge to zero as we get more samples?

asked Aug 13 at 8:45

3 votes

0 answers

39 views

Subgradient of the matrix norm

asked Sep 8 at 4:56

2 votes

1 answer

45 views

Does $|X_n|+|Y_n|=o_p\left(1\right)$ imply $|X_n|=o_p\left(1\right)$?

asked Aug 16 at 1:52

1 vote

1 answer

48 views

Concentration inequality of the covariance matrix

asked Sep 8 at 15:37

1 vote

0 answers

33 views

Bound the spectral norm of the precision matrix using column-wise norm

asked Oct 19 at 2:44

1 vote

0 answers

21 views

Is $\mathbb{E}\left[\|\hat{\Sigma}\|_F\right]=\|{\Sigma}\|_F$?

asked Nov 3 at 8:51

0 votes

0 answers

32 views

Square of the convergence rate $\|\hat{A}-A\|_F^2$

asked Nov 4 at 8:21

0 votes

0 answers

12 views

Control the estimation error measured by induced matrix $L_1$ norm

asked Oct 23 at 12:18

0 votes

0 answers

26 views

What does consistency mean in high-dimensional settings?

asked Nov 11 at 9:37

0 votes

1 answer

27 views

Choose a good estimator in a candidate set

asked Nov 19 at 12:48

0 votes

0 answers

37 views

Is it possible to solve $\|X-A\|_2+\lambda_n\|X\|_1$?

asked Sep 9 at 13:36

0 votes

0 answers

15 views

The concentration inequality of the product of the estimators

asked Oct 10 at 3:34

0 votes

2 answers

74 views

Derivative of $\text{tr}\left(XAX\right)$ w.r.t $X$ [duplicate]

asked Aug 27 at 12:38

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17 Questions

The sum of $O_p$ --$ O_p \left(s^2\frac{\log d}{n}+s\sqrt{\frac{\log d}{n}} \right) $

The deviation of the sample correlation matrix from its true value

Concentration inequality about the sum of covariance matrix

Estimate a vector $\beta=\underbrace{\beta_1}_{\text{sparse}}+\underbrace{\beta_2}_{\text{dense}}$

Does the loss function necessarily converge to zero as we get more samples?

Subgradient of the matrix norm

Does $|X_n|+|Y_n|=o_p\left(1\right)$ imply $|X_n|=o_p\left(1\right)$?

Concentration inequality of the covariance matrix

Bound the spectral norm of the precision matrix using column-wise norm

Is $\mathbb{E}\left[\|\hat{\Sigma}\|_F\right]=\|{\Sigma}\|_F$?

Square of the convergence rate $\|\hat{A}-A\|_F^2$

Control the estimation error measured by induced matrix $L_1$ norm

What does consistency mean in high-dimensional settings?

Choose a good estimator in a candidate set

Is it possible to solve $\|X-A\|_2+\lambda_n\|X\|_1$?

The concentration inequality of the product of the estimators

Derivative of $\text{tr}\left(XAX\right)$ w.r.t $X$ [duplicate]