- In
mathematical statistics, the
Kullback–Leibler (KL)
divergence (also
called relative entropy and I-divergence),
denoted D KL ( P ∥ Q ) {\displaystyle...
-
Solomon Kullback (April 3, 1907 –
August 5, 1994) was an
American cryptanalyst and mathematician, who was one of the
first three employees hired by William...
- In
information theory and statistics,
Kullback's inequality is a
lower bound on the
Kullback–Leibler
divergence expressed in
terms of the
large deviations...
- that the
Kullback–Leibler
divergence is non-negative.
Another inequality concerning the
Kullback–Leibler
divergence is
known as
Kullback's inequality...
- I(X;Y)=I(Y;X)=H(X)+H(Y)-H(X,Y).\,}
Mutual information can be
expressed as the
average Kullback–Leibler
divergence (information gain)
between the
posterior probability...
- The
other most
important divergence is
relative entropy (also
called Kullback–Leibler divergence),
which is
central to
information theory.
There are...
- |1-\alpha =e^{1-\lambda x}\}=e^{1-\lambda x}\end{aligned}}} The
directed Kullback–Leibler
divergence in nats of e λ {\displaystyle e^{\lambda }} ("approximating"...
-
dimensionality of the
vector space, and the
result has
units of nats. The
Kullback–Leibler
divergence from N 1 ( μ 1 , Σ 1 ) {\displaystyle {\mathcal {N}}_{1}({\boldsymbol...
-
expected value of ln(xk)
equal to ln(λk) − γ {\displaystyle \gamma } . The
Kullback–Leibler
divergence between two
Weibulll distributions is
given by D KL...
- Y)}\|P_{X}\otimes P_{Y})}
where D K L {\displaystyle D_{\mathrm {KL} }} is the
Kullback–Leibler divergence, and P X ⊗ P Y {\displaystyle P_{X}\otimes P_{Y}} is...
