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REPORTS > KEYWORD > THRESHOLD CIRCUITS:
Reports tagged with Threshold Circuits:
TR94-012 | 12th December 1994

Bounds for the Computational Power and Learning Complexity of Analog Neural Nets

It is shown that high order feedforward neural nets of constant depth with piecewise
polynomial activation functions and arbitrary real weights can be simulated for boolean
inputs and outputs by neural nets of a somewhat larger size and depth with heaviside
gates and weights ... more >>>


TR95-017 | 27th March 1995
Claudia Bertram, Thomas Hofmeister

Multiple Product Modulo Arbitrary Numbers

We consider the threshold circuit complexity of computing
the multiple product modulo m in threshold circuits.

more >>>

TR98-020 | 10th April 1998
Andris Ambainis, David Mix Barrington, Huong LeThanh

On Counting $AC^0$ Circuits with Negative Constants

Continuing the study of the relationship between $TC^0$,
$AC^0$ and arithmetic circuits, started by Agrawal et al.
(IEEE Conference on Computational Complexity'97),
we answer a few questions left open in this
paper. Our main result is that the classes Diff$AC^0$ and
Gap$AC^0$ ... more >>>


TR99-012 | 19th April 1999
Eric Allender, Andris Ambainis, David Mix Barrington, Samir Datta, Huong LeThanh

Bounded Depth Arithmetic Circuits: Counting and Closure

Comments: 1

Constant-depth arithmetic circuits have been defined and studied
in [AAD97,ABL98]; these circuits yield the function classes #AC^0
and GapAC^0. These function classes in turn provide new
characterizations of the computational power of threshold circuits,
and provide a link between the circuit classes AC^0 ... more >>>


TR00-032 | 31st May 2000

On the Computational Power of Winner-Take-All

In this paper the computational power of a new type of gate is studied:
winner-take-all gates. This work is motivated by the fact that the cost
of implementing a winner-take-all gate in analog VLSI is about the same
as that of implementing a threshold gate.

We show that ... more >>>


TR00-065 | 7th September 2000
Eric Allender, David Mix Barrington

Uniform Circuits for Division: Consequences and Problems

Comments: 2

The essential idea in the fast parallel computation of division and
related problems is that of Chinese remainder representation
(CRR) -- storing a number in the form of its residues modulo many
small primes. Integer division provides one of the few natural
examples of problems for which ... more >>>


TR01-033 | 27th April 2001
Eric Allender, David Mix Barrington, William Hesse

Uniform Circuits for Division: Consequences and Problems

Integer division has been known to lie in P-uniform TC^0 since
the mid-1980's, and recently this was improved to DLOG-uniform
TC^0. At the time that the results in this paper were proved and
submitted for conference presentation, it was unknown whether division
lay in DLOGTIME-uniform TC^0 (also known as ... more >>>


TR06-138 | 13th November 2006
Kei Uchizawa, Rodney Douglas

Energy Complexity and Entropy of Threshold Circuits

Circuits composed of threshold gates (McCulloch-Pitts neurons, or
perceptrons) are simplified models of neural circuits with the
advantage that they are theoretically more tractable than their
biological counterparts. However, when such threshold circuits are
designed to perform a specific computational task they usually
differ ... more >>>


TR08-016 | 26th February 2008
Alexander Razborov, Alexander A. Sherstov

The Sign-Rank of AC^0

The sign-rank of a matrix A=[A_{ij}] with +/-1 entries
is the least rank of a real matrix B=[B_{ij}] with A_{ij}B_{ij}>0
for all i,j. We obtain the first exponential lower bound on the
sign-rank of a function in AC^0. Namely, let
f(x,y)=\bigwedge_{i=1}^m\bigvee_{j=1}^{m^2} (x_{ij}\wedge y_{ij}).
We show that the matrix [f(x,y)]_{x,y} has ... more >>>


TR12-007 | 28th January 2012
Ruiwen Chen, Valentine Kabanets

Lower Bounds against Weakly Uniform Circuits

Revisions: 1

A family of Boolean circuits $\{C_n\}_{n\geq 0}$ is called \emph{$\gamma(n)$-weakly uniform} if
there is a polynomial-time algorithm for deciding the direct-connection language of every $C_n$,
given \emph{advice} of size $\gamma(n)$. This is a relaxation of the usual notion of uniformity, which allows one
to interpolate between complete uniformity (when $\gamma(n)=0$) ... more >>>


TR13-021 | 5th February 2013
Kristoffer Arnsfelt Hansen, Vladimir Podolskii

Polynomial threshold functions and Boolean threshold circuits

We study the complexity of computing Boolean functions on general
Boolean domains by polynomial threshold functions (PTFs). A typical
example of a general Boolean domain is $\{1,2\}^n$. We are mainly
interested in the length (the number of monomials) of PTFs, with
their degree and weight being of secondary interest. We ... more >>>


TR13-177 | 10th December 2013
Eric Allender, Nikhil Balaji, Samir Datta

Low-depth Uniform Threshold Circuits and the Bit-Complexity of Straight Line Programs

Revisions: 1

We present improved uniform TC$^0$ circuits for division, matrix powering, and related problems, where the improvement is in terms of ``majority depth'' (initially studied by Maciel and Therien). As a corollary, we obtain improved bounds on the complexity of certain problems involving arithmetic circuits, which are known to lie in ... more >>>


TR14-122 | 30th September 2014
Eric Allender, Anna Gal, Ian Mertz

Dual VP Classes

Revisions: 2

We consider arithmetic complexity classes that are in some sense dual to the classes VP(Fp) that were introduced by Valiant. This provides new characterizations of the complexity classes ACC^1 and TC^1, and also provides a compelling example of
a class of high-degree polynomials that can be simulated via arithmetic circuits ... more >>>


TR15-188 | 24th November 2015
Daniel Kane, Ryan Williams

Super-Linear Gate and Super-Quadratic Wire Lower Bounds for Depth-Two and Depth-Three Threshold Circuits

In order to formally understand the power of neural computing, we first need to crack the frontier of threshold circuits with two and three layers, a regime that has been surprisingly intractable to analyze. We prove the first super-linear gate lower bounds and the first super-quadratic wire lower bounds for ... more >>>


TR15-191 | 26th November 2015
Ruiwen Chen, Rahul Santhanam, Srikanth Srinivasan

Average-Case Lower Bounds and Satisfiability Algorithms for Small Threshold Circuits

We show average-case lower bounds for explicit Boolean functions against bounded-depth threshold circuits with a superlinear number of wires. We show that for each integer d > 1, there is \epsilon_d > 0 such that Parity has correlation at most 1/n^{\Omega(1)} with depth-d threshold circuits which have at most
n^{1+\epsilon_d} ... more >>>


TR16-075 | 9th May 2016
Mark Bun, Justin Thaler

Improved Bounds on the Sign-Rank of AC$^0$

Revisions: 1

The sign-rank of a matrix $A$ with entries in $\{-1, +1\}$ is the least rank of a real matrix $B$ with $A_{ij} \cdot B_{ij} > 0$ for all $i, j$. Razborov and Sherstov (2008) gave the first exponential lower bounds on the sign-rank of a function in AC$^0$, answering an ... more >>>


TR16-121 | 4th August 2016
Mark Bun, Justin Thaler

Approximate Degree and the Complexity of Depth Three Circuits

Revisions: 1

Threshold weight, margin complexity, and Majority-of-Threshold circuit size are basic complexity measures of Boolean functions that arise in learning theory, communication complexity, and circuit complexity. Each of these measures might exhibit a chasm at depth three: namely, all polynomial size Boolean circuits of depth two have polynomial complexity under the ... more >>>


TR17-083 | 5th May 2017
Arkadev Chattopadhyay, Nikhil Mande

Weights at the Bottom Matter When the Top is Heavy

Revisions: 1

Proving super-polynomial lower bounds against depth-2 threshold circuits of the form THR of THR is a well-known open problem that represents a frontier of our understanding in boolean circuit complexity. By contrast, exponential lower bounds on the size of THR of MAJ circuits were shown by Razborov and Sherstov (SIAM ... more >>>


TR19-007 | 17th January 2019
Arkadev Chattopadhyay, Meena Mahajan, Nikhil Mande, Nitin Saurabh

Lower Bounds for Linear Decision Lists

We demonstrate a lower bound technique for linear decision lists, which are decision lists where the queries are arbitrary linear threshold functions.
We use this technique to prove an explicit lower bound by showing that any linear decision list computing the function $MAJ \circ XOR$ requires size $2^{0.18 n}$. This ... more >>>




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