A neural network is said to be nonoverlapping if there is at most one
edge outgoing from each node. We investigate the number of examples
that a learning algorithm needs when using nonoverlapping neural
networks as hypotheses. We derive bounds for this sample complexity
in terms of the Vapnik-Chervonenkis dimension. ...
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An \emph{arithmetic read-once formula} (ROF for short) is a
formula (a circuit whose underlying graph is a tree) in which the
operations are $\{+,\times\}$ and such that every input variable
labels at most one leaf. A \emph{preprocessed ROF} (PROF for
short) is a ROF in which we are allowed to ...
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There are only a few known general approaches for constructing explicit pseudorandom generators (PRGs). The ``iterated restrictions'' approach, pioneered by Ajtai and Wigderson [AW89], has provided PRGs with seed length $\mathrm{polylog} n$ or even $\tilde{O}(\log n)$ for several restricted models of computation. Can this approach ever achieve the optimal seed ... more >>>
We study monotone branching programs, wherein the states at each time step can be ordered so that edges with the same labels never cross each other. Equivalently, for each fixed input, the transition functions are a monotone function of the state.
We prove that constant-width monotone branching programs of ... more >>>
We study the polynomial equivalence problem for orbits of read-once arithmetic formulas (ROFs). Read-once formulas have received considerable attention in both algebraic and Boolean complexity and have served as a testbed for developing effective tools and techniques for analyzing circuits. Two $n$-variate polynomials $f, g \in \mathbb{F}[\mathbf{x}]$ are equivalent, denoted ... more >>>