3,853 research outputs found
On the power of homogeneous depth 4 arithmetic circuits
We prove exponential lower bounds on the size of homogeneous depth 4
arithmetic circuits computing an explicit polynomial in . Our results hold
for the {\it Iterated Matrix Multiplication} polynomial - in particular we show
that any homogeneous depth 4 circuit computing the entry in the product
of generic matrices of dimension must have size
.
Our results strengthen previous works in two significant ways.
Our lower bounds hold for a polynomial in . Prior to our work, Kayal et
al [KLSS14] proved an exponential lower bound for homogeneous depth 4 circuits
(over fields of characteristic zero) computing a poly in . The best known
lower bounds for a depth 4 homogeneous circuit computing a poly in was the
bound of by [LSS, KLSS14].Our exponential lower bounds
also give the first exponential separation between general arithmetic circuits
and homogeneous depth 4 arithmetic circuits. In particular they imply that the
depth reduction results of Koiran [Koi12] and Tavenas [Tav13] are tight even
for reductions to general homogeneous depth 4 circuits (without the restriction
of bounded bottom fanin).
Our lower bound holds over all fields. The lower bound of [KLSS14] worked
only over fields of characteristic zero. Prior to our work, the best lower
bound for homogeneous depth 4 circuits over fields of positive characteristic
was [LSS, KLSS14]
Sums of products of polynomials in few variables : lower bounds and polynomial identity testing
We study the complexity of representing polynomials as a sum of products of
polynomials in few variables. More precisely, we study representations of the
form such that each is
an arbitrary polynomial that depends on at most variables. We prove the
following results.
1. Over fields of characteristic zero, for every constant such that , we give an explicit family of polynomials , where
is of degree in variables, such that any
representation of the above type for with requires . This strengthens a recent result of Kayal and Saha
[KS14a] which showed similar lower bounds for the model of sums of products of
linear forms in few variables. It is known that any asymptotic improvement in
the exponent of the lower bounds (even for ) would separate VP
and VNP[KS14a].
2. We obtain a deterministic subexponential time blackbox polynomial identity
testing (PIT) algorithm for circuits computed by the above model when and
the individual degree of each variable in are at most and
for any constant . We get quasipolynomial running
time when . The PIT algorithm is obtained by combining our
lower bounds with the hardness-randomness tradeoffs developed in [DSY09, KI04].
To the best of our knowledge, this is the first nontrivial PIT algorithm for
this model (even for the case ), and the first nontrivial PIT algorithm
obtained from lower bounds for small depth circuits
Determining General and Specific Purpose Transfers : An Integrated Approach
This study attempts to provide an alternative methodology to calculate the horizontal equalization transfers. This methodology follows the Australian horizontal equalization principle using a panel model methodology where both revenue and expenditure side considerations are involved. First, it applies the Canadian model in calculating the fiscal capacity equalization. Then the expenditure side equalization has been carried out for two services - education and health. Results of the exercise indicate that the transfers suggested by the panel model are more progressive than the TFC recommended transfers.horizontal equalization transfers, education, health, fiscal capacity equalization
Improved rank bounds for design matrices and a new proof of Kelly's theorem
We study the rank of complex sparse matrices in which the supports of
different columns have small intersections. The rank of these matrices, called
design matrices, was the focus of a recent work by Barak et. al. (BDWY11) in
which they were used to answer questions regarding point configurations. In
this work we derive near-optimal rank bounds for these matrices and use them to
obtain asymptotically tight bounds in many of the geometric applications. As a
consequence of our improved analysis, we also obtain a new, linear algebraic,
proof of Kelly's theorem, which is the complex analog of the Sylvester-Gallai
theorem
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