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32
Complexity Measures and Decision Tree Complexity: A Survey
 Theoretical Computer Science
, 2000
"... We discuss several complexity measures for Boolean functions: certificate complexity, sensitivity, block sensitivity, and the degree of a representing or approximating polynomial. We survey the relations and biggest gaps known between these measures, and show how they give bounds for the decision tr ..."
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Cited by 122 (15 self)
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We discuss several complexity measures for Boolean functions: certificate complexity, sensitivity, block sensitivity, and the degree of a representing or approximating polynomial. We survey the relations and biggest gaps known between these measures, and show how they give bounds for the decision tree complexity of Boolean functions on deterministic, randomized, and quantum computers. 1 Introduction Computational Complexity is the subfield of Theoretical Computer Science that aims to understand "how much" computation is necessary and sufficient to perform certain computational tasks. For example, given a computational problem it tries to establish tight upper and lower bounds on the length of the computation (or on other resources, like space). Unfortunately, for many, practically relevant, computational problems no tight bounds are known. An illustrative example is the well known P versus NP problem: for all NPcomplete problems the current upper and lower bounds lie exponentially ...
Complexity Limitations on Quantum Computation
 Journal of Computer and System Sciences
, 1997
"... We use the powerful tools of counting complexity and generic oracles to help understand the limitations of the complexity of quantum computation. We show several results for the probabilistic quantum class BQP.  BQP is low for PP, i.e., PP BQP = PP.  There exists a relativized world where P = ..."
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Cited by 98 (3 self)
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We use the powerful tools of counting complexity and generic oracles to help understand the limitations of the complexity of quantum computation. We show several results for the probabilistic quantum class BQP.  BQP is low for PP, i.e., PP BQP = PP.  There exists a relativized world where P = BQP and the polynomialtime hierarchy is infinite.  There exists a relativized world where BQP does not have complete sets.  There exists a relativized world where P = BQP but P 6= UP " coUP and oneway functions exist. This gives a relativized answer to an open question of Simon.
Computing Solutions Uniquely Collapses the Polynomial Hierarchy
 SIAM Journal on Computing
, 1993
"... Is there a singlevalued NP function that, when given a satisfiable formula as input, outputs a satisfying assignment? That is, can a nondeterministic function cull just one satisfying assignment from a possibly exponentially large collection of assignments? We show that if there is such a nondeterm ..."
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Cited by 40 (23 self)
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Is there a singlevalued NP function that, when given a satisfiable formula as input, outputs a satisfying assignment? That is, can a nondeterministic function cull just one satisfying assignment from a possibly exponentially large collection of assignments? We show that if there is such a nondeterministic function, then the polynomial hierarchy collapses to its second level. As the existence of such a function is known to be equivalent to the statement "every multivalued NP function has a singlevalued NP refinement," our result provides the strongest evidence yet that multivalued NP functions cannot be refined. We prove our result via theorems of independent interest. We say that a set A is NPSVselective (NPMVselective) if there is a 2ary partial function in NPSV (NPMV, respectively) that decides which of its inputs (if any) is "more likely" to belong to A; this is a nondeterministic analog of the recursiontheoretic notion of the semirecursive sets and the extant complexitythe...
The Role of Relativization in Complexity Theory
 Bulletin of the European Association for Theoretical Computer Science
, 1994
"... Several recent nonrelativizing results in the area of interactive proofs have caused many people to review the importance of relativization. In this paper we take a look at how complexity theorists use and misuse oracle results. We pay special attention to the new interactive proof systems and progr ..."
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Cited by 40 (9 self)
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Several recent nonrelativizing results in the area of interactive proofs have caused many people to review the importance of relativization. In this paper we take a look at how complexity theorists use and misuse oracle results. We pay special attention to the new interactive proof systems and program checking results and try to understand why they do not relativize. We give some new results that may help us to understand these questions better.
Threshold Computation and Cryptographic Security
 SIAM JOURNAL ON COMPUTING
, 1995
"... Threshold machines are Turing machines whose acceptance is determined by what portion of the machine's computation paths are accepting paths. Probabilistic machines are Turing machines whose acceptance is determined by the probability weight of the machine's accepting computation paths. In 1975, ..."
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Cited by 37 (7 self)
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Threshold machines are Turing machines whose acceptance is determined by what portion of the machine's computation paths are accepting paths. Probabilistic machines are Turing machines whose acceptance is determined by the probability weight of the machine's accepting computation paths. In 1975, Simon proved that for unboundederror polynomialtime machines these two notions yield the same class, PP. Perhaps because Simon's result seemed to collapse the threshold and probabilistic modes of computation, the relationship between threshold and probabilistic computing for the case of bounded error has remained unexplored. In this paper, we compare the boundederror probabilistic class BPP with the analogous threshold class, BPP path , and, more generally, we study the structural properties of BPP path . We prove that BPP path contains both NP BPP and P NP[log] , and that BPP path is contained in P \Sigma p 2 [log] , BPP NP , and PP. We conclude that, unless the polynomial hierarchy collapses, boundederror threshold computation is strictly more powerful than boundederror probabilistic computation. We also consider the natural notion of secure access to a database: an adversary who watches the queries should gain no information about the input other than perhaps its length. We show, for both BPP and BPP path , that if there is any database for which this formalization of security differs from the security given by oblivious database access, then P 6= PSPACE. It follows that if any set lacking small circuits can be securely accepted, then P 6= PSPACE.
The Isomorphism Conjecture Holds Relative to an Oracle
, 1996
"... We introduce symmetric perfect generic sets. These sets vary from the usual generic sets by allowing limited infinite encoding into the oracle. We then show that the BermanHartmanis isomorphism conjecture [BH77] holds relative to any spgeneric oracle, i.e., for any symmetric perfect generic set A, ..."
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Cited by 26 (11 self)
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We introduce symmetric perfect generic sets. These sets vary from the usual generic sets by allowing limited infinite encoding into the oracle. We then show that the BermanHartmanis isomorphism conjecture [BH77] holds relative to any spgeneric oracle, i.e., for any symmetric perfect generic set A, all NP^Acomplete sets are polynomialtime isomorphic relative to A. Prior to this work there were no known oracles relative to which the isomorphism conjecture held. As part of our proof that the isomorphism conjecture holds relative to symmetric perfect generic sets we also show that P A = FewP A for any symmetric perfect generic A.
Separability and Oneway Functions
, 2000
"... We settle all relativized questions of the relationships between the following ve propositions: P = NP P = UP P = NP \ coNP All disjoint pairs of NP sets are Pseparable. ..."
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Cited by 25 (13 self)
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We settle all relativized questions of the relationships between the following ve propositions: P = NP P = UP P = NP \ coNP All disjoint pairs of NP sets are Pseparable.
One Complexity Theorist's View of Quantum Computing
 THEORETICAL COMPUTER SCIENCE
, 2000
"... The complexity of quantum computation remains poorly understood. While physicists attempt to find ways to create quantum computers, we still do not have much evidence one way or the other as to how useful these machines will be. The tools of computational complexity theory should come to bear on ..."
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Cited by 22 (0 self)
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The complexity of quantum computation remains poorly understood. While physicists attempt to find ways to create quantum computers, we still do not have much evidence one way or the other as to how useful these machines will be. The tools of computational complexity theory should come to bear on these important questions. Quantum Computing
Quantum versus Classical Learnability
 IN: SIXTEENTH CONFERENCE ON COMPUTATIONAL COMPLEXITY (CCC
, 2000
"... This paper studies fundamental questions in computational learning theory from a quantum computation perspective. We consider quantum versions of two wellstudied classical learning models: Angluin's model of exact learning from membership queries and Valiant's Probably Approximately Correct (PAC) m ..."
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Cited by 13 (1 self)
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This paper studies fundamental questions in computational learning theory from a quantum computation perspective. We consider quantum versions of two wellstudied classical learning models: Angluin's model of exact learning from membership queries and Valiant's Probably Approximately Correct (PAC) model of learning from random examples. We give positive and negative results for quantum versus classical learnability. For each of the two learning models described above, we show that any concept class is informationtheoretically learnable from polynomially many quantum examples if and only if it is informationtheoretically learnable from polynomially many classical examples. In contrast to this informationtheoretic equivalence betwen quantum and classical learnability, though, we observe that a separation does exist between ecient quantum and classical learnability. For both the model of exact learning from membership queries and the PAC model, we show that under a widely held computational hardness assumption for classical computation (the intractability of factoring), there is a concept class which is polynomialtime learnable in the quantum version but not in the classical version of the model.