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39
The Complexity Of Propositional Proofs
 Bulletin of Symbolic Logic
, 1995
"... This paper of Tseitin is a landmark as the first to give nontrivial lower bounds for propositional proofs; although it predates the first papers on ..."
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Cited by 107 (2 self)
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This paper of Tseitin is a landmark as the first to give nontrivial lower bounds for propositional proofs; although it predates the first papers on
PP is Closed Under Intersection
 Journal of Computer and System Sciences
, 1991
"... In his seminal paper on probabilistic Turing machines, Gill [13] asked whether the class PP is closed under intersection and union. We give a positive answer to this question. We also show that PP is closed under a variety of polynomialtime truthtable reductions. Consequences in complexity theory ..."
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Cited by 88 (9 self)
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In his seminal paper on probabilistic Turing machines, Gill [13] asked whether the class PP is closed under intersection and union. We give a positive answer to this question. We also show that PP is closed under a variety of polynomialtime truthtable reductions. Consequences in complexity theory include the definite collapse and (assuming P<F NaN> 6= PP) separation of certain query hierarchies over PP. Similar techniques allow us to combine several threshold gates into a single threshold gate. Consequences in the study of circuits include the simulation of circuits with a small number of threshold gates by circuits having only a single threshold gate at the root (perceptrons), and a lower bound on the number of threshold gates needed to compute the parity function. 1. Introduction The class PP was defined in 1972 by John Gill [13, 14] and independently by Janos Simon [26] in 1974. PP is the class of languages accepted by a polynomialtime bounded nondeterministic Turing machine t...
On the compilability and expressive power of propositional planning formalisms
, 1998
"... The recent approaches of extending the GRAPHPLAN algorithm to handle more expressive planning formalisms raise the question of what the formal meaning of “expressive power ” is. We formalize the intuition that expressive power is a measure of how concisely planning domains and plans can be expressed ..."
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Cited by 80 (10 self)
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The recent approaches of extending the GRAPHPLAN algorithm to handle more expressive planning formalisms raise the question of what the formal meaning of “expressive power ” is. We formalize the intuition that expressive power is a measure of how concisely planning domains and plans can be expressed in a particular formalism by introducing the notion of “compilation schemes ” between planning formalisms. Using this notion, we analyze the expressiveness of a large family of propositional planning formalisms, ranging from basic STRIPS to a formalism with conditional effects, partial state specifications, and propositional formulae in the preconditions. One of the results is that conditional effects cannot be compiled away if plan size should grow only linearly but can be compiled away if we allow for polynomial growth of the resulting plans. This result confirms that the recently proposed extensions to the GRAPHPLAN algorithm concerning conditional effects are optimal with respect to the “compilability ” framework. Another result is that general propositional formulae cannot be compiled into conditional effects if the plan size should be preserved linearly. This implies that allowing general propositional formulae in preconditions and effect conditions adds another level of difficulty in generating a plan.
A FirstOrder Isomorphism Theorem
 SIAM JOURNAL ON COMPUTING
, 1993
"... We show that for most complexity classes of interest, all sets complete under firstorder projections are isomorphic under firstorder isomorphisms. That is, a very restricted version of the BermanHartmanis Conjecture holds. ..."
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Cited by 24 (5 self)
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We show that for most complexity classes of interest, all sets complete under firstorder projections are isomorphic under firstorder isomorphisms. That is, a very restricted version of the BermanHartmanis Conjecture holds.
On approximate majority and probabilistic time
 in Proceedings of the 22nd IEEE Conference on Computational Complexity
, 2007
"... We prove new results on the circuit complexity of Approximate Majority, which is the problem of computing Majority of a given bit string whose fraction of 1’s is bounded away from 1/2 (by a constant). We then apply these results to obtain new relationships between probabilistic time, BPTime (t), and ..."
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Cited by 18 (6 self)
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We prove new results on the circuit complexity of Approximate Majority, which is the problem of computing Majority of a given bit string whose fraction of 1’s is bounded away from 1/2 (by a constant). We then apply these results to obtain new relationships between probabilistic time, BPTime (t), and alternating time, Σ O(1)Time (t). Our main results are the following: 1. We prove that 2 n0.1�size depth3 circuits for Approximate Majority on n bits have bottom fanin Ω(log n). As a corollary we obtain that BPTime (t) �⊆ Σ2Time � o(t 2) � with respect to some oracle. This complements the result that BPTime (t) ⊆ Σ2Time � t 2 · poly log t � with respect to every oracle (Sipser and Gács, STOC ’83; Lautemann, IPL ’83). 2. We prove that Approximate Majority is computable by uniform polynomialsize circuits of depth 3. Prior to our work, the only known polynomialsize depth3 circuits for Approximate Majority were nonuniform (Ajtai, Ann. Pure Appl. Logic ’83). We also prove that BPTime (t) ⊆ Σ3Time (t · poly log t). This complements our results in (1). 3. We prove new lower bounds for solving QSAT 3 ∈ Σ3Time (n · poly log n) on probabilistic computational models. In particular, we prove that solving QSAT 3 requires time n 1+Ω(1) on Turing machines with a randomaccess input tape and a sequentialaccess work tape that is initialized with random bits. No lower bound was previously known on this model (for a function computable in linear space). ∗ Author supported by NSF grant CCR0324906. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author and do not necessarily reflect the views of the
Some Problems Involving RazborovSmolensky Polynomials
, 1991
"... Several recent results in circuit complexity theory have used a representation of Boolean functions by polynomials over finite fields. Our current inability to extend these results to superficially similar situations may be related to properties of these polynomials which do not extend to polyno ..."
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Cited by 11 (2 self)
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Several recent results in circuit complexity theory have used a representation of Boolean functions by polynomials over finite fields. Our current inability to extend these results to superficially similar situations may be related to properties of these polynomials which do not extend to polynomials over general finite rings or finite abelian groups. Here we pose a number of conjectures on the behavior of such polynomials over rings and groups, and present some partial results toward proving them. 1. Introduction 1.1. Polynomials and Circuit Complexity The representation of Boolean functions as polynomials over the finite field Z 2 = f0; 1g dates back to early work in switching theory [?]. A formal language L can be identified with the family of functions f i : Z i 2 ! Z 2 , where f i (x 1 ; : : : ; x i ) = 1 iff x 1 : : : x i 2 L. Each of these functions can be written as a polynomial in the variables x 1 ; : : : ; x n . We can consider algebraic formulas or circuits with...
Protecting Circuits from Leakage: the ComputationallyBounded and Noisy Cases
, 2010
"... Abstract. Physical computational devices leak sidechannel information that may, and often does, reveal secret internal states. We present a general transformation that compiles any circuit into a new, functionally equivalent circuit which is resilient against welldefined classes of leakage. Our co ..."
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Abstract. Physical computational devices leak sidechannel information that may, and often does, reveal secret internal states. We present a general transformation that compiles any circuit into a new, functionally equivalent circuit which is resilient against welldefined classes of leakage. Our construction requires a small, stateless and computationindependent leakproof component that draws random elements from a fixed distribution. In essence, we reduce the problem of shielding arbitrarily complex circuits to the problem of shielding a single, simple component. Our approach is based on modeling the adversary as a powerful observer that inspects the device via a limited measurement apparatus. We allow the apparatus to access all the bits of the computation (except those inside the leakproof component) and the amount of leaked information to grow unbounded over time. However, we assume that the apparatus is limited either in its computational ability (namely, it lacks the ability to decode certain linear encodings and outputs a limited number of bits per iteration), or its precision (each observed bit is flipped with some probability). While our results apply in general to such leakage classes, in particular, we obtain security against: – Constant depth circuits leakage, where the measurement apparatus can be implemented by an AC 0 circuit (namely, a constant depth circuit composed of NOT gates and unbounded fanin AND and OR gates), or an ACC 0 [p] circuit (which is the same as AC 0, except that it also uses MODp gates) which outputs a limited number of bits. – Noisy leakage, where the measurement apparatus reveals all the bits of the state of the circuit, perturbed by independent binomial noise. Namely, each bit of the computation is perturbed with probability p, and remains unchanged with probability 1 − p. 1
On the complexity of hardness amplification
 In Proceedings of the 20th Annual IEEE Conference on Computational Complexity
, 2005
"... We study the task of transforming a hard function f, with which any small circuit disagrees on (1 − δ)/2 fraction of the input, into a harder function f ′ , with which any small circuit disagrees on (1 − δ k)/2 fraction of the input, for δ ∈ (0, 1) and k ∈ N. We show that this process can not be car ..."
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Cited by 7 (1 self)
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We study the task of transforming a hard function f, with which any small circuit disagrees on (1 − δ)/2 fraction of the input, into a harder function f ′ , with which any small circuit disagrees on (1 − δ k)/2 fraction of the input, for δ ∈ (0, 1) and k ∈ N. We show that this process can not be carried out in a blackbox way by a circuit of depth d and size 2 o(k1/d) or by a nondeterministic circuit of size o(k / log k) (and arbitrary depth). In particular, for k = 2 Ω(n) , such hardness amplification can not be done in ATIME(O(1), 2 o(n)). Therefore, hardness amplification in general requires a high complexity. Furthermore, we show that even without any restriction on the complexity of the amplification procedure, such a blackbox hardness amplification must be inherently nonuniform in the following sense. Given as an oracle any algorithm which agrees with f ′ on (1 − δ k)/2 fraction of the input, we still need an additional advice of length Ω(k log(1/δ)) in order to compute f correctly on (1−δ)/2 fraction of the input. Therefore, to guarantee the hardness, even against uniform machines, of the function f ′ , one has to start with a function f which is hard against nonuniform circuits. Finally, we derive similar lower bounds for any blackbox construction of pseudorandom generators from hard functions.
A Lower Bound for Perceptrons and an Oracle Separation of the PP PH Hierarchy
 Journal of Computer and System Sciences
, 1997
"... We show that there are functions computable by linear size boolean circuits of depth k that require superpolynomial size perceptrons of depth k \Gamma 1, for k ! logn=(6loglogn). This result implies the existence of an oracle A such that S p;A k 6` PP S p;A k\Gamma2 and in particular this ..."
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We show that there are functions computable by linear size boolean circuits of depth k that require superpolynomial size perceptrons of depth k \Gamma 1, for k ! logn=(6loglogn). This result implies the existence of an oracle A such that S p;A k 6` PP S p;A k\Gamma2 and in particular this oracle separates the levels in the PP PH hierarchy. Using the same ideas, we show a lower bound for another function, which makes it possible to strengthen the oracle separation to D p;A k 6` PP S p;A k\Gamma2 . 1 Introduction There is a strong connection between lower bounds for boolean circuits (consisting of AND, OR, and NOT gates) and relativization results about the polynomial time hierarchy. This fact was first established by Furst, Saxe, and Sipser [5]. Sipser [13] later defined a family of functions that are computable by linear size circuits of depth k, and showed that they require superpolynomial size boolean circuits of depth k \Gamma 1. Yao [14] and Hstad [8, 9] impr...
On the Power of SmallDepth Computation
, 2009
"... In this work we discuss selected topics on smalldepth computation, presenting a few unpublished proofs along the way. The four chapters contain: 1. A unified treatment of the challenge of exhibiting explicit functions that have small correlation with lowdegree polynomials over {0, 1}. 2. An unpubl ..."
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Cited by 5 (4 self)
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In this work we discuss selected topics on smalldepth computation, presenting a few unpublished proofs along the way. The four chapters contain: 1. A unified treatment of the challenge of exhibiting explicit functions that have small correlation with lowdegree polynomials over {0, 1}. 2. An unpublished proof that small boundeddepth circuits (AC 0) have exponentially small correlation with the parity function. The proof is due to Klivans and Vadhan; it builds upon and simplifies previous ones. 3. Valiant’s simulation of logdepth linearsize circuits of fanin 2 by subexponential size circuits of depth 3 and unbounded fanin. To our knowledge, a proof of this result has never appeared in full.