Results 1  10
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18,816
Monotone Complexity
, 1990
"... We give a general complexity classification scheme for monotone computation, including monotone spacebounded and Turing machine models not previously considered. We propose monotone complexity classes including mAC i , mNC i , mLOGCFL, mBWBP , mL, mNL, mP , mBPP and mNP . We define a simple ..."
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Cited by 2825 (11 self)
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We give a general complexity classification scheme for monotone computation, including monotone spacebounded and Turing machine models not previously considered. We propose monotone complexity classes including mAC i , mNC i , mLOGCFL, mBWBP , mL, mNL, mP , mBPP and mNP . We define a
The knowledge complexity of interactive proof systems

, 1989
"... Usually, a proof of a theorem contains more knowledge than the mere fact that the theorem is true. For instance, to prove that a graph is Hamiltonian it suffices to exhibit a Hamiltonian tour in it; however, this seems to contain more knowledge than the single bit Hamiltonian/nonHamiltonian. In th ..."
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Cited by 1246 (39 self)
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/nonHamiltonian. In this paper a computational complexity theory of the "knowledge " contained in a proof is developed. Zeroknowledge proofs are defined as those proofs that convey no additional knowledge other than the correctness of the proposition in question. Examples of zeroknowledge proof systems are given
Intentions, implicatures and processing of complex questions
 In S. Harabagiu & F. Lacatusu (Eds.), Proceedings of the
, 2004
"... In this paper we introduce two methods for deriving the intentional structure of complex questions. Techniques that enable the derivation of implied information are also presented. We show that both the intentional structure and the implicatures enabled by it are essential components of Q/A systems ..."
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Cited by 3 (0 self)
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In this paper we introduce two methods for deriving the intentional structure of complex questions. Techniques that enable the derivation of implied information are also presented. We show that both the intentional structure and the implicatures enabled by it are essential components of Q/A systems
Eliciting selfexplanations improves understanding
 Cognitive Science
, 1994
"... Learning involves the integration of new information into existing knowledge. Generoting explanations to oneself (selfexplaining) facilitates that integration process. Previously, selfexplanation has been shown to improve the acquisition of problemsolving skills when studying workedout examples. ..."
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Cited by 577 (22 self)
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the pretest to the posttest. Moreover, prompted students who generated o large number of selfexplanations (the high explainers) learned with greater understanding than low explainers. Understanding was assessed by answering very complex questions and inducing the function of a component when it was only
Facial expression and emotion
 American Psychologist
, 1993
"... In this article, we review diverse studies of the antecedents, facial display, and social consequences of embarrassment. These studies indicate that embarrassment serves an appeasement function, reconciling social relations when they have gone awry. We then speculate about how embarrassment is elabo ..."
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Cited by 566 (12 self)
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is elaborated into more complex social interactions, such as teasing and flirtation. We conclude by raising questions about the blush and embarrassment that await empirical consideration.
Evolving Neural Networks through Augmenting Topologies
 Evolutionary Computation
"... An important question in neuroevolution is how to gain an advantage from evolving neural network topologies along with weights. We present a method, NeuroEvolution of Augmenting Topologies (NEAT), which outperforms the best fixedtopology method on a challenging benchmark reinforcement learning task ..."
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Cited by 536 (112 self)
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An important question in neuroevolution is how to gain an advantage from evolving neural network topologies along with weights. We present a method, NeuroEvolution of Augmenting Topologies (NEAT), which outperforms the best fixedtopology method on a challenging benchmark reinforcement learning
A framework for information systems architecture.
 IBM Syst. J.,
, 1987
"... With increasing size and complexity of the implementations of information systems, it is necessary to use some logical construct (or architecture) for defining and controlling the interfaces and the integration of all of the components of the system. This paper defines information systems architect ..."
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Cited by 546 (0 self)
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With increasing size and complexity of the implementations of information systems, it is necessary to use some logical construct (or architecture) for defining and controlling the interfaces and the integration of all of the components of the system. This paper defines information systems
Complex networks: Structure and dynamics
, 2006
"... Coupled biological and chemical systems, neural networks, social interacting species, the Internet and the World Wide Web, are only a few examples of systems composed by a large number of highly interconnected dynamical units. The first approach to capture the global properties of such systems is t ..."
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Cited by 435 (12 self)
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that are at the basis of real networks, and developing models to mimic the growth of a network and reproduce its structural properties. On the other hand, many relevant questions arise when studying complex networks ’ dynamics, such as learning how a large ensemble of dynamical systems that interact through a complex
Loopy belief propagation for approximate inference: An empirical study. In:
 Proceedings of Uncertainty in AI,
, 1999
"... Abstract Recently, researchers have demonstrated that "loopy belief propagation" the use of Pearl's polytree algorithm in a Bayesian network with loops can perform well in the context of errorcorrecting codes. The most dramatic instance of this is the near Shannonlimit performanc ..."
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Cited by 676 (15 self)
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and ap proximately 4000 findin nodes, with a number of ob served findings that varies per case. Due to the form of the noisyor CPTs the complexity of inference is ex ponential in the number of positive findings Results Initial experiments The experimental protocol for the PYRAMID network was as follows
Genomic control for association studies
, 1999
"... A dense set of single nucleotide polymorphisms (SNP) covering the genome and an efficient method to assess SNP genotypes are expected to be available in the near future. An outstanding question is how to use these technologies efficiently to identify genes affecting liability to complex disorders. ..."
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Cited by 480 (13 self)
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A dense set of single nucleotide polymorphisms (SNP) covering the genome and an efficient method to assess SNP genotypes are expected to be available in the near future. An outstanding question is how to use these technologies efficiently to identify genes affecting liability to complex disorders
Results 1  10
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