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509
The Communication of Inductive Inferences
, 1997
"... We propose a new approach to communication between agents that perform inductive inference. Consider a community of agents where each agent has a limited view of the overall world. When an agent in this community induces a hypothesis about the world, it necessarily reflects that agent's part ..."
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We propose a new approach to communication between agents that perform inductive inference. Consider a community of agents where each agent has a limited view of the overall world. When an agent in this community induces a hypothesis about the world, it necessarily reflects that agent
Unsupervised Lexical Learning as Inductive Inference
, 2000
"... To learn a language, the learners must first learn its words, the essential building blocks for utterances. The difficulty in learning words lies in the unavailability of explicit word boundaries in speech input. The learners have to infer lexical items with some innately endowed learning mechanism( ..."
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Cited by 14 (5 self)
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To learn a language, the learners must first learn its words, the essential building blocks for utterances. The difficulty in learning words lies in the unavailability of explicit word boundaries in speech input. The learners have to infer lexical items with some innately endowed learning mechanism
Inductive Inference of Approximations for Recursive Concepts
, 2005
"... This paper provides a systematic study of inductive inference of indexable concept classes in learning scenarios where the learner is successful if its final hypothesis describes a finite variant of the target concept, i.e., learning with anomalies. Learning from positive data only and from both pos ..."
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This paper provides a systematic study of inductive inference of indexable concept classes in learning scenarios where the learner is successful if its final hypothesis describes a finite variant of the target concept, i.e., learning with anomalies. Learning from positive data only and from both
Inductive Inference of Limiting Programs with Bounded Number of Mind Changes
"... We consider inductive inference of total recursive functions in the case, when produced hypotheses are allowed some finite number of times to change "their mind" about each value of identifiable function. Such type of identification, which we call inductive inference of limiting programs w ..."
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of allowed mind changes and the number of anomalies, and ffl relations between classes of functions identifiable with different probabilities. For the case of probabilistic identification we establish probabilistic hierarchies which are quite unusual for EX and BC types of inference. 1 Introduction In many
Inductive Inference with Procrastination: Back to Definitions
 Fundamenta Informaticae
, 1999
"... In this paper, we reconsider the denition of procrastinating learning machines. In the original denition of Freivalds and Smith [FS93], constructive ordinals are used to bound mindchanges. We investigate possibility of using arbitrary linearly ordered sets to bound mindchanges in similar way. It ..."
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Cited by 8 (1 self)
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.599 and NSF Grant 9421640. Some of the results from this paper were presented earlier [AFS96]. y The third author was supported in part by NSF Grant 9301339. 1 Introduction We study inductive inference using the model developed by Gold [Gol67]. There is a well known hierarchy of larger and larger classes
D = 4 chiral string compactifications from intersecting branes,” hepth/0011073; “Intersecting brane worlds,” JHEP0102
, 2001
"... Intersecting Dpbranes often give rise to chiral fermions living on their intersections. We study the construction of fourdimensional chiral gauge theories by considering configurations of type II D(3 + n)branes wrapped on nontrivial ncycles on T 2n × (R 2(3−n) /ZN), for n = 1,2,3. The gauge the ..."
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Cited by 107 (24 self)
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theories on the four noncompact dimensions of the brane worldvolume are generically chiral and nonsupersymmetric. We analyze consistency conditions (RR tadpole cancellation) for these models, and their relation to fourdimensional anomaly cancellation. Cancellation of U(1) gauge anomalies involves a
GUT Model Hierarchies from Intersecting
 Branes”, JHEP 0208 (2002) 018, hepth/0203187
"... By employing D6branes intersecting at angles in D = 4 type I strings, we construct three generation models with minimal structure, based on the group SU(4)C × SU(2)L × SU(2)R. The models are nonsupersymmetric, even though SUSY is unbroken in the bulk, and contain at low energy the standard model s ..."
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Cited by 30 (6 self)
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spectrum augmented by an extra anomaly free global U(1) symmetry, with no extra matter and/or extra gauge group factors. Baryon number is gauged and its anomalies are cancelled through a generalized GreenSchwarz mechanism. We also show that multibrane wrappings correspond to a trivial redefinition
Identification Criteria in Uniform Inductive Inference
"... Uniform Inductive Inference is concerned with the existence and the learning behaviour of strategies identifying infinitely many classes of recursive functions. The success of such strategies depends on the hypothesis spaces they use, as well as on the chosen identification criteria resulting from a ..."
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Uniform Inductive Inference is concerned with the existence and the learning behaviour of strategies identifying infinitely many classes of recursive functions. The success of such strategies depends on the hypothesis spaces they use, as well as on the chosen identification criteria resulting from
Reasoning about naming systems
 ACM Transactions on Programming Languages and Systems
, 1993
"... This paper reasons about naming systems as specialized inference mechanisms, It describes a preference)zierarch.v that can be used to specify the structure of a naming system’s inference mechanism and defines criteria by which different naming systems can be evaluated, For example, the preference h ..."
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Cited by 97 (1 self)
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This paper reasons about naming systems as specialized inference mechanisms, It describes a preference)zierarch.v that can be used to specify the structure of a naming system’s inference mechanism and defines criteria by which different naming systems can be evaluated, For example, the preference
Theorybased causal induction
 In
, 2003
"... Inducing causal relationships from observations is a classic problem in scientific inference, statistics, and machine learning. It is also a central part of human learning, and a task that people perform remarkably well given its notorious difficulties. People can learn causal structure in various s ..."
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Cited by 56 (19 self)
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and are rarely studied together, but at heart they present the same inductive challenge—identifying the unobservable mechanisms that generate observable relations between variables, objects, or events, given only sparse and limited data. We present a computationallevel analysis of this inductive problem and a
Results 11  20
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509