Search results for "computational complexity"

showing 10 items of 249 documents

Weak and strong recognition by 2-way randomized automata

1997

Languages weakly recognized by a Monte Carlo 2-way finite automaton with n states are proved to be strongly recognized by a Monte Carlo 2-way finite automaton with no(n) states. This improves dramatically over the previously known result by M.Karpinski and R.Verbeek [10] which is also nontrivial since these languages can be nonregular [5]. For tally languages the increase in the number of states is proved to be only polynomial, and these languages are regular.

Deterministic pushdown automatonCombinatoricsDeterministic automatonProbabilistic automatonPushdown automatonQuantum finite automataBüchi automatonTwo-way deterministic finite automatonNondeterministic finite automatonComputer Science::Computational ComplexityComputer Science::Formal Languages and Automata TheoryMathematics
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Quantum Lower Bound for Graph Collision Implies Lower Bound for Triangle Detection

2015

We show that an improvement to the best known quantum lower bound for GRAPH-COLLISION problem implies an improvement to the best known lower bound for TRIANGLE problem in the quantum query complexity model. In GRAPH-COLLISION we are given free access to a graph $(V,E)$ and access to a function $f:V\rightarrow \{0,1\}$ as a black box. We are asked to determine if there exist $(u,v) \in E$, such that $f(u)=f(v)=1$. In TRIANGLE we have a black box access to an adjacency matrix of a graph and we have to determine if the graph contains a triangle. For both of these problems the known lower bounds are trivial ($\Omega(\sqrt{n})$ and $\Omega(n)$, respectively) and there is no known matching upper …

Quantum queryQuantum PhysicsGeneral Computer ScienceFree accessTheoryofComputation_GENERALCollisionUpper and lower boundsOmegaGraphCombinatoricsComputer Science - Computational ComplexityAdjacency matrixQuantumMathematicsMathematicsofComputing_DISCRETEMATHEMATICS
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Quantum counter automata

2011

The question of whether quantum real-time one-counter automata (rtQ1CAs) can outperform their probabilistic counterparts has been open for more than a decade. We provide an affirmative answer to this question, by demonstrating a non-context-free language that can be recognized with perfect soundness by a rtQ1CA. This is the first demonstration of the superiority of a quantum model to the corresponding classical one in the real-time case with an error bound less than 1. We also introduce a generalization of the rtQ1CA, the quantum one-way one-counter automaton (1Q1CA), and show that they too are superior to the corresponding family of probabilistic machines. For this purpose, we provide gene…

SoundnessFOS: Computer and information sciencesQuantum PhysicsGeneralizationComputer scienceProbabilistic logicFOS: Physical sciences0102 computer and information sciences02 engineering and technologyComputational Complexity (cs.CC)01 natural sciencesAutomatonAlgebraComputer Science - Computational Complexity010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineeringComputer Science (miscellaneous)Quantum finite automata020201 artificial intelligence & image processingPoint (geometry)Quantum Physics (quant-ph)Quantum
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Do Randomized Algorithms Improve the Efficiency of Minimal Learning Machine?

2020

Minimal Learning Machine (MLM) is a recently popularized supervised learning method, which is composed of distance-regression and multilateration steps. The computational complexity of MLM is dominated by the solution of an ordinary least-squares problem. Several different solvers can be applied to the resulting linear problem. In this paper, a thorough comparison of possible and recently proposed, especially randomized, algorithms is carried out for this problem with a representative set of regression datasets. In addition, we compare MLM with shallow and deep feedforward neural network models and study the effects of the number of observations and the number of features with a special dat…

0209 industrial biotechnologyrandom projectionlcsh:Computer engineering. Computer hardwareComputational complexity theoryComputer scienceRandom projectionlcsh:TK7885-789502 engineering and technologyMachine learningcomputer.software_genresupervised learningapproximate algorithmsSet (abstract data type)regressioanalyysi020901 industrial engineering & automationdistance–based regressionalgoritmit0202 electrical engineering electronic engineering information engineeringordinary least–squaresbusiness.industrySupervised learningsingular value decompositionminimal learning machineMultilaterationprojektioRandomized algorithmkoneoppiminenmachine learningScalabilityFeedforward neural network020201 artificial intelligence & image processingArtificial intelligenceapproksimointibusinesscomputerMachine Learning and Knowledge Extraction
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If P≠NP then some strongly noninvertible functions are invertible

2006

AbstractRabi, Rivest, and Sherman alter the standard notion of noninvertibility to a new notion they call strong noninvertibility, and show—via explicit cryptographic protocols for secret-key agreement (Rabi and Sherman attribute this protocol to Rivest and Sherman) and digital signatures (Rabi and Sherman)—that strongly noninvertible functions are very useful components in protocol design. Their definition of strong noninvertibility has a small twist (“respecting the argument given”) that is needed to ensure cryptographic usefulness. In this paper, we show that this small twist has a consequence: unless P=NP, some strongly noninvertible functions are invertible.

Discrete mathematicsGeneral Computer ScienceComputational complexity theorybusiness.industryP versus NP problemOne-way functionsCryptographyOne-way functionCryptographic protocolTheoretical Computer Sciencelaw.inventionComputational complexityInvertible matrixDigital signaturelawAssociativityCryptographyStrong noninvertibilitybusinessAssociative propertyMathematicsTheoretical Computer Science
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New separation between $s(f)$ and $bs(f)$

2011

In this note we give a new separation between sensitivity and block sensitivity of Boolean functions: $bs(f)=(2/3)s(f)^2-(1/3)s(f)$.

FOS: Computer and information sciencesComputational Complexity (cs.CC)
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Very Narrow Quantum OBDDs and Width Hierarchies for Classical OBDDs

2014

In the paper we investigate a model for computing of Boolean functions – Ordered Binary Decision Diagrams (OBDDs), which is a restricted version of Branching Programs. We present several results on the comparative complexity for several variants of OBDD models. We present some results on the comparative complexity of classical and quantum OBDDs. We consider a partial function depending on a parameter k such that for any k > 0 this function is computed by an exact quantum OBDD of width 2, but any classical OBDD (deterministic or stable bounded-error probabilistic) needs width 2 k + 1. We consider quantum and classical nondeterminism. We show that quantum nondeterminism can be more efficient …

Discrete mathematicsImplicit functionBinary decision diagram010102 general mathematics02 engineering and technologyFunction (mathematics)Computer Science::Artificial IntelligenceComputer Science::Computational Complexity01 natural sciencesCombinatoricsNondeterministic algorithmComputer Science::Logic in Computer SciencePartial function0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processing0101 mathematicsBoolean functionQuantumQuantum computerMathematics
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Reduced complexity models in the identification of dynamical networks: Links with sparsification problems

2009

In many applicative scenarios it is important to derive information about the topology and the internal connections of more dynamical systems interacting together. Examples can be found in fields as diverse as Economics, Neuroscience and Biochemistry. The paper deals with the problem of deriving a descriptive model of a network, collecting the node outputs as time series with no use of a priori insight on the topology. We cast the problem as the optimization of a cost function operating a trade-off between accuracy and complexity in the final model. We address the problem of reducing the complexity by fixing a certain degree of sparsity, and trying to find the solution that “better” satisfi…

Approximation theoryMathematical optimizationSettore ING-INF/04 - AutomaticaDynamical systems theoryComputational complexity theoryNode (networking)A priori and a posteriorisparsification compressing sensing estimation networksNetwork topologyGreedy algorithmTopology (chemistry)MathematicsProceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference
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Alternating, private alternating, and quantum alternating realtime automata

2014

We present new results on realtime alternating, private alternating, and quantum alternating automaton models. Firstly, we show that the emptiness problem for alternating one-counter automata on unary alphabets is undecidable. Then, we present two equivalent definitions of realtime private alternating finite automata (PAFAs). We show that the emptiness problem is undecidable for PAFAs. Furthermore, PAFAs can recognize some nonregular unary languages, including the unary squares language, which seems to be difficult even for some classical counter automata with two-way input. Regarding quantum finite automata (QFAs), we show that the emptiness problem is undecidable both for universal QFAs o…

FOS: Computer and information sciencesComputer Science - Computational ComplexityComputer Science - Logic in Computer ScienceQuantum PhysicsFormal Languages and Automata Theory (cs.FL)Computer Science::Logic in Computer ScienceFOS: Physical sciencesComputer Science - Formal Languages and Automata TheoryComputer Science::Computational ComplexityComputational Complexity (cs.CC)Quantum Physics (quant-ph)Computer Science::Formal Languages and Automata TheoryLogic in Computer Science (cs.LO)
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Quantum lower bound for inverting a permutation with advice

2014

Given a random permutation $f: [N] \to [N]$ as a black box and $y \in [N]$, we want to output $x = f^{-1}(y)$. Supplementary to our input, we are given classical advice in the form of a pre-computed data structure; this advice can depend on the permutation but \emph{not} on the input $y$. Classically, there is a data structure of size $\tilde{O}(S)$ and an algorithm that with the help of the data structure, given $f(x)$, can invert $f$ in time $\tilde{O}(T)$, for every choice of parameters $S$, $T$, such that $S\cdot T \ge N$. We prove a quantum lower bound of $T^2\cdot S \ge \tilde{\Omega}(\epsilon N)$ for quantum algorithms that invert a random permutation $f$ on an $\epsilon$ fraction of…

FOS: Computer and information sciencesNuclear and High Energy PhysicsComputer Science - Cryptography and SecurityGeneral Physics and AstronomyFOS: Physical sciencesOne-way functionComputational Complexity (cs.CC)Upper and lower boundsTheoretical Computer ScienceCyclic permutationCombinatoricsPermutationMathematical PhysicsMathematicsDiscrete mathematicsQuantum PhysicsBit-reversal permutationStatistical and Nonlinear PhysicsRandom permutationComputer Science - Computational ComplexityComputational Theory and MathematicsQuantum algorithmQuantum Physics (quant-ph)Advice (complexity)Cryptography and Security (cs.CR)MathematicsofComputing_DISCRETEMATHEMATICS
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