- for an m × n matrix) is
sometimes referred to as the
sparsity of the matrix. Conceptually,
sparsity corresponds to
systems with few
pairwise interactions...
-
restricted isometry property) and the
level of
sparsity in the solution, k {\displaystyle k} , the
sp**** representation problem can be
shown to have a...
-
Sp**** is a
computer software tool
designed to find
possible coding faults in the
Linux kernel.
Unlike other such tools, this
static analysis tool was...
-
Structured sparsity regularization is a
class of methods, and an area of
research in
statistical learning theory, that
extend and
generalize sparsity regularization...
-
Sp**** grids are
numerical techniques to represent,
integrate or
interpolate high
dimensional functions. They were
originally developed by the Russian...
- the k-
sp**** autoencoder.
Instead of
forcing sparsity, we add a
sparsity regularization loss, then
optimize for min θ , ϕ L ( θ , ϕ ) + λ L
sp**** ( θ ...
- the
statistical analysis of the
results from
factorial experiments, the
sparsity-of-effects
principle states that a
system is
usually dominated by main...
-
provide an
improvement in
sparsity and
flexibility of the representation. One of the most
important applications of
sp**** dictionary learning is in the...
-
under which recovery is possible. The
first one is
sparsity,
which requires the
signal to be
sp**** in some domain. The
second one is incoherence, which...
- as the 80/20 rule, the law of the
vital few and the
principle of
factor sparsity)
states that for many outcomes,
roughly 80% of
consequences come from 20%...
