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1,166
A Digital Signature Scheme Secure Against Adaptive ChosenMessage Attacks
, 1995
"... We present a digital signature scheme based on the computational diculty of integer factorization. The scheme possesses the novel property of being robust against an adaptive chosenmessage attack: an adversary who receives signatures for messages of his choice (where each message may be chosen in a ..."
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Cited by 959 (40 self)
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in a way that depends on the signatures of previously chosen messages) can not later forge the signature of even a single additional message. This may be somewhat surprising, since the properties of having forgery being equivalent to factoring and being invulnerable to an adaptive chosenmessage attack
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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limit performance of "Turbo Codes" codes whose decoding algorithm is equivalent to loopy belief propagation in a chainstructured Bayesian network. In this paper we ask: is there something spe cial about the errorcorrecting code context, or does loopy propagation work as an ap proximate inference scheme
Informationtheoretic metric learning
 in NIPS 2006 Workshop on Learning to Compare Examples
, 2007
"... We formulate the metric learning problem as that of minimizing the differential relative entropy between two multivariate Gaussians under constraints on the Mahalanobis distance function. Via a surprising equivalence, we show that this problem can be solved as a lowrank kernel learning problem. Spe ..."
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Cited by 359 (15 self)
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We formulate the metric learning problem as that of minimizing the differential relative entropy between two multivariate Gaussians under constraints on the Mahalanobis distance function. Via a surprising equivalence, we show that this problem can be solved as a lowrank kernel learning problem
Expectationbased syntactic comprehension
, 2006
"... This paper investigates the role of resource allocation as a source of processing difficulty in human sentence comprehension. The paper proposes a simple informationtheoretic characterization of processing difficulty as the work incurred by resource reallocation during parallel, incremental, probabi ..."
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Cited by 231 (18 self)
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, probabilistic disambiguation in sentence comprehension, and demonstrates its equivalence to the theory of Hale (2001), in which the difficulty of a word is proportional to its surprisal (its negative logprobability) in the context within which it appears. This proposal subsumes and clarifies findings that high
Mirror Symmetry is TDuality
, 1996
"... It is argued that every CalabiYau manifold X with a mirror Y admits a family of supersymmetric toroidal 3cycles. Moreover the moduli space of such cycles together with their flat connections is precisely the space Y . The mirror transformation is equivalent to Tduality on the 3cycles. The geomet ..."
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Cited by 182 (10 self)
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It is argued that every CalabiYau manifold X with a mirror Y admits a family of supersymmetric toroidal 3cycles. Moreover the moduli space of such cycles together with their flat connections is precisely the space Y . The mirror transformation is equivalent to Tduality on the 3cycles
Behavioral Equivalence in the Polymorphic PiCalculus
 JOURNAL OF THE ACM
, 1997
"... We investigate parametric polymorphism in messagebased concurrent programming, focusing on behavioral equivalences in a typed process calculus analogous to the polymorphic lambdacalculus of Girard and Reynolds. Polymorphism constrains the power of observers by preventing them from directly manip ..."
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Cited by 63 (8 self)
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We investigate parametric polymorphism in messagebased concurrent programming, focusing on behavioral equivalences in a typed process calculus analogous to the polymorphic lambdacalculus of Girard and Reynolds. Polymorphism constrains the power of observers by preventing them from directly
Coil sensitivity encoding for fast MRI. In:
 Proceedings of the ISMRM 6th Annual Meeting,
, 1998
"... New theoretical and practical concepts are presented for considerably enhancing the performance of magnetic resonance imaging (MRI) by means of arrays of multiple receiver coils. Sensitivity encoding (SENSE) is based on the fact that receiver sensitivity generally has an encoding effect complementa ..."
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Cited by 193 (3 self)
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imaging techniques, MRI stands out by a rarely stated peculiarity: the size of the details resolved with MRI is much smaller than the wavelength of the radiation involved. The reason for this surprising ability is that the origin of a resonance signal is not determined by optical means such as focusing
Surprises in openstring perturbation theory
 Nucl. Phys. Proc. Suppl
, 1997
"... The perturbative analysis of models of open and closed superstrings presents a number of surprises. For instance, variable numbers of antisymmetric tensors ensure their consistency via generalized GreenSchwarz cancellations and a novel type of singularity occurs in their moduli spaces. All these fe ..."
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Cited by 1 (0 self)
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The perturbative analysis of models of open and closed superstrings presents a number of surprises. For instance, variable numbers of antisymmetric tensors ensure their consistency via generalized GreenSchwarz cancellations and a novel type of singularity occurs in their moduli spaces. All
Branes: cosmological surprise and observational deception
, 2008
"... Using some supernovae and CMB data, we constrain the Cardassian, RandallSundrum, and DvaliGabadadzePorrati braneinspired cosmological models. We show that a transient acceleration and an early loitering period are usually excluded by the data. Moreover, the three models are equivalent to some us ..."
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Using some supernovae and CMB data, we constrain the Cardassian, RandallSundrum, and DvaliGabadadzePorrati braneinspired cosmological models. We show that a transient acceleration and an early loitering period are usually excluded by the data. Moreover, the three models are equivalent to some
Behavioral theories and the neurophysiology of reward,
 Annu. Rev. Psychol.
, 2006
"... ■ Abstract The functions of rewards are based primarily on their effects on behavior and are less directly governed by the physics and chemistry of input events as in sensory systems. Therefore, the investigation of neural mechanisms underlying reward functions requires behavioral theories that can ..."
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Cited by 187 (0 self)
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equivalent for the prediction error term of (λV) of the RescorlaWagner learning rule. With these characteristics, the THEORY AND NEUROPHYSIOLOGY OF REWARD 101 bidirectional dopamine error response would constitute an ideal teaching signal for neural plasticity. The neural prediction error signal provides
Results 1  10
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1,166