Results 271 to 280 of about 386,074 (314)
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Learning in the Presence of Malicious Errors
SIAM Journal on Computing, 1988In 1984, \textit{L. G. Valiant} [Commun. ACM 27, 1134-1142 (1984; Zbl 0587.68077)] proposed a so-called distribution-free model of learning, in which the learner is given samples of negative and positive examples drawn (according to some unknown probability distributions \(p^ +\), \(p^ -\)) from the sets of all possible positive and negative examples ...
Michael J. Kearns, Ming Li 0001
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Learning with Errors in the Exponent
2016The Snowden revelations have shown that intelligence agencies have been successful in undermining cryptography and put in question the exact security provided by the underlying intractability problem. We introduce a new class of intractability problems, called Learning with Errors in the Exponent (LWEE).
Özgür Dagdelen +2 more
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New Electronics, 2023
Large-language models threaten to upend software and hardware development as we know it, but can they really deliver the goods? CHRIS EDWARDS investigates
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Large-language models threaten to upend software and hardware development as we know it, but can they really deliver the goods? CHRIS EDWARDS investigates
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Errors and Learning in Organizations
1998The essay theorizes on the role of errors - defined as events that cannot be interpreted through the current organizational cognitive schemes - in the organizational innovation and learning processes. An interpretative model of the different typologies of error production, and a normative model on the strategies organizations can adopt to manage errors,
VICARI, SALVATORE, TROILO, GABRIELE
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Middle-Product Learning with Errors
2017We introduce a new variant \(\mathsf {MP}\text {-}\mathsf {LWE}\) of the Learning With Errors problem (\(\mathsf {LWE}\)) making use of the Middle Product between polynomials modulo an integer q. We exhibit a reduction from the Polynomial-\(\mathsf {LWE}\) problem (\(\mathsf {PLWE}\)) parametrized by a polynomial f, to \(\mathsf {MP}\text {-}\mathsf ...
Miruna Rosca +3 more
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Training error, generalization error and learning curves in neural learning
Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, 2002A neural network is trained by using a set of available examples to minimize the training error such that the network parameters fit the examples well. However, it is desired to minimize the generalization error to which no direct access is possible. There are discrepancies between the training error and the generalization error due to the statistical ...
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Learning from errors and resilience
Current Opinion in Anaesthesiology, 2023Purpose of review Learning from errors has been the main objective of patient safety initiatives for the last decades. The different tools have played a role in the evolution of the safety culture to a nonpunitive system-centered one.
Daniel, Arnal-Velasco +1 more
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An “Errorful” Learning Deficit in Schizophrenia?
Journal of Clinical and Experimental Neuropsychology, 2006Disturbances in learning are prominent in schizophrenia. The present study examined the effect of committing mistakes (errors) on learning in schizophrenia. Subjects included schizophrenia and schizoaffective disorder patients (n = 36) and healthy adults (n = 22) who were administered a word-stem completion task under "errorfree" (no guessing) and ...
Jay W, Pope, Robert S, Kern
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2015
This form of alterity shakes the foundations of essentialism, imposing a creativity which falsifies the given and countermands received wisdom. From Deleuze’s perspective, a fear of falsification, or error, suggests a counterproductive attitude to change which relies on unrealistic expectations of life itself. When Parker (2009, p. 31) asserts that the
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This form of alterity shakes the foundations of essentialism, imposing a creativity which falsifies the given and countermands received wisdom. From Deleuze’s perspective, a fear of falsification, or error, suggests a counterproductive attitude to change which relies on unrealistic expectations of life itself. When Parker (2009, p. 31) asserts that the
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Rényi divergence on learning with errors
Science China Information Sciences, 2020Many lattice-based schemes are built from the hardness of the learning with errors problem, which naturally comes in two flavors: the decision LWE and search LWE. In this paper, we investigate the decision LWE and search LWE by Renyi divergence respectively and obtain the following results: For decision LWE, we apply RD on LWE variants with different ...
Yang Tao 0001, Han Wang, Rui Zhang 0002
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