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Text-Descrambling

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networks approximate probabilistic on an anytime We evaluation this of present based idea. for procedure
We present an anytime procedure for approximate evaluation of probabilistic networks based on this idea.
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be the We correct. algorithm prove to
We prove the algorithm to be correct.
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by already proposed scheme out local that It turns our is Shenoy. computation
It turns out that our local computation scheme is already proposed by Shenoy.
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are different that completely of from intuitions However, our Shenoy.
However, our intuitions are completely different from that of Shenoy.
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networks as belief Bayesian (IB) assignments abductive proposed Independence-based were originally to explanations.
Independence-based (IB) assignments to Bayesian belief networks were originally proposed as abductive explanations.
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We networks. marginal approximate use Bayesian belief to in probabilities assignments IB
We use IB assignments to approximate marginal probabilities in Bayesian belief networks.
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obtained be efficiently. approximation fewer sufficient, more are assignments can a IB good and Thus,
Thus, fewer IB assignments are sufficient, and a good approximation can be obtained more efficiently.
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feasible is highly networks. approach this belief for that connected results Experimental show
Experimental results show that this approach is feasible for highly connected belief networks.
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thinking Some to and an require instances build of test hypothetical creative agent theories.
Some instances of creative thinking require an agent to build and test hypothetical theories.
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have true, true?") counterfactual A queries were C been would (e.g., Evaluation of "If
Evaluation of counterfactual queries (e.g., "If A were true, would C have been true?")
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planning, and important diagnosis, of fault determination liability. is to
is important to fault diagnosis, planning, and determination of liability.
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some must of solve fundamental we reject the To theory. problem, postulates this
To solve this problem, we must reject some fundamental postulates of the theory.
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variables. two networks primitives and add networks: persistent controllable Action probabilistic variables causal to
Action networks add two primitives to probabilistic causal networks: controllable variables and persistent variables.
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recent paper progress. This results in both work and describes
This paper describes both recent results and work in progress.
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are The these investigated, independence and non-interactivity are links between properties given. and of relations
The links between independence and non-interactivity are investigated, and properties of these relations are given.
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three to contributes topics. these This paper all
This paper contributes to all these three topics.
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with belief networks that minimallity It certain shown is properties selecting is NP-hard.
It is shown that selecting belief networks with certain minimallity properties is NP-hard.
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in We the efficiently be heuristic. search by it can implemented argue incorporating smoothing that
We argue that smoothing can be efficiently implemented by incorporating it in the search heuristic.
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belief networks that Experimental results probabilities learning is for suggest smoothing of helpful.
Experimental results suggest that for learning probabilities of belief networks smoothing is helpful.
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probabilities occurrence. conditions of by are and enabling The events represented
The events are represented by enabling conditions and probabilities of occurrence.
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issues The updating connection with networks. beliefs deals with in paper optimality in
The paper deals with optimality issues in connection with updating beliefs in networks.
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two processes: trees. triangulation of We junction construction and address
We address two processes: triangulation and construction of junction trees.
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that integrals. a evaluates Carlo these Moreover, we Monte procedure develop new
Moreover, we develop a new Monte Carlo procedure that evaluates these integrals.
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It and is acceptancerejection. aspects of bootstrap sampling some on based
It is based on some aspects of bootstrap sampling and acceptancerejection.
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leak to enforce describe assumption of probabilities We model. in the the our use closed-world
We describe the use of leak probabilities to enforce the closed-world assumption in our model.
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simulation and discussion example. an by illustrative real-world Theoretical results is supplemented
Theoretical discussion is supplemented by simulation results and an illustrative real-world example.
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be speed-up maintaining achieved Additional can by path information. the
Additional speed-up can be achieved by maintaining the path information.
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also default We competing systems. comparisons make reasoning with
We also make comparisons with competing default reasoning systems.
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for Bayesian simulation technique is an networks. approximate inference Backward belief
Backward simulation is an approximate inference technique for Bayesian belief networks.
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this expensive, impossible via indirectly is or recognition. be information must plan communication When acquired
When communication is impossible or expensive, this information must be acquired indirectly via plan recognition.
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license. this dis- modify of can tribution Users make terms and new under the
Users can modify and make new dis- tribution under the terms of this license.
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are neutral. Synonymous to affect do be mutations interplay often and this assumed not
Synonymous mutations do not affect this interplay and are often assumed to be neutral.
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most the Recognition today. fields one of Language Sign growing of research is
Sign Language Recognition is one of the most growing fields of research today.
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these have been recently techniques developed Many fields. new in
Many new techniques have been developed recently in these fields.
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system and four Hand Classification. Skin Extraction of Feature Cropping, comprises The parts: Filtering,
The system comprises of four parts: Skin Filtering, Hand Cropping, Feature Extraction and Classification.
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decisions. time treatment a is change critical in Volumetric multiforme (GBM) in over glioblastoma factor
Volumetric change in glioblastoma multiforme (GBM) over time is a critical factor in treatment decisions.
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structures. are complicated medical the an researches and Normally, exclusive more data
Normally, the medical data researches are more complicated and an exclusive structures.
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expands diagnostic PET paper, in the various scope for functions. brain task In image this
In this paper, the scope diagnostic task expands for PET image in various brain functions.
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the sensitive Here orientation study to second-order psychophysical visual modulations. mechanisms we of show
Here we show psychophysical study of second-order visual mechanisms sensitive to the orientation modulations.
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phase measured. to and Selectivity spatial is of modulation frequency orientation,
Selectivity to orientation, phase and spatial frequency of modulation is measured.
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field. emerged work as a has Nuclear in image research medical promising
Nuclear image has emerged as a promising research work in medical field.
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challenge. its Images own from different meet modality
Images from different modality meet its own challenge.
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world it testing It real for effectiveness its demonstrated by has sets. data patient
It has demonstrated its effectiveness by testing it for real world patient data sets.
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algorithm. are Experimental compared Means with K and results FCM clustering conventional
Experimental results are compared with conventional FCM and K Means clustering algorithm.
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compared provides algorithms SFCM performance The with PET the two of other satisfactory results .
The performance of the PET SFCM provides satisfactory results compared with other two algorithms .
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now Positron replaced a resolution. (PET) and Tomography caring the Emission has issues high
Positron Emission Tomography (PET) has now replaced the issues and caring a high resolution.
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method detection a sequences. brain based fully approach symmetry automated abnormality presents PET for This
This approach presents a fully automated symmetry based brain abnormality detection method for PET sequences.
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like performance accuracy considered diagnosis. the of The evolution metric by is
The performance evolution is considered by the metric like accuracy of diagnosis.
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obtained of result surely the surgeon seizures automated the is for focus. assists identification The
The obtained result is surely assists the surgeon for the automated identification of seizures focus.
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Neural by feedback often is subject currents. firing adaptation negative to
Neural firing is often subject to negative feedback by adaptation currents.
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between can currents correlations spikes. strong time among the induce These intervals
These currents can induce strong correlations among the time intervals between spikes.
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this properties. phenomenon explain paper attempts to analyze This and its
This paper attempts to explain this phenomenon and analyze its properties.
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in This into ongoing describes research paper environment. uncertain an planning
This paper describes ongoing research into planning in an uncertain environment.
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strategic where in abstraction are place decisions made an hierarchy takes decisions. Planning before tactical
Planning takes place in an abstraction hierarchy where strategic decisions are made before tactical decisions.
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dependence networks independence variables. encoding quantifying conditional Belief among probabilistic and graphs are and
Belief networks are graphs encoding and quantifying probabilistic dependence and conditional independence among variables.
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presented. is the adequacy experimental of method discussed results preliminary are The and theoretical
The theoretical adequacy of the method is discussed and preliminary experimental results are presented.
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reasoning Evidential Artificial topic Intelligence. leading in a is now
Evidential reasoning is now a leading topic in Artificial Intelligence.
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is functions. Evidence represented of by variety a evidential
Evidence is represented by a variety of evidential functions.
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certain operation carried functions. fundamental out reasoning kinds by these Evidential of is on
Evidential reasoning is carried out by certain kinds of fundamental operation on these functions.
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involve decision and commonly under probabilistic variables. uncertainty random making of continuous Problems inference
Problems of probabilistic inference and decision making under uncertainty commonly involve continuous random variables.
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computations. discretized a to simplify to and points, are Often assessments these few
Often these are discretized to a few points, to simplify assessments and computations.
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An to approximation is distributions. alternative continuous fit analytically tractable probability
An alternative approximation is to fit analytically tractable continuous probability distributions.
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variables especially can advantages, accuracy and potential This has if be transformed approach simplicity first.
This approach has potential simplicity and accuracy advantages, especially if variables can be transformed first.
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is well-known this in algorithm. case the The procedure fitting EM
The fitting procedure in this case is the well-known EM algorithm.
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presented. two algorithm LED) preliminary are the on Results evaluation of networks (ALARM and of
Results of preliminary evaluation of the algorithm on two networks (ALARM and LED) are presented.
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algorithm open discuss some issues and also We problems. performance
We also discuss some algorithm performance issues and open problems.
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diagnosing uncertain logical analyses. through combining a and reasoning describe software method We problems for
We describe a method for diagnosing software problems through combining logical and uncertain reasoning analyses.
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for "compiling" are simple decision presented of diagrams influence set Two algorithms into rules. a
Two algorithms are presented for "compiling" influence diagrams into a set of simple decision rules.
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define rules near-optimal and complete, consistent, simple-to-execute, These decision procedures. decision
These decision rules define simple-to-execute, complete, consistent, and near-optimal decision procedures.
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Valuation networks graphical (VBSs). representations been as have proposed valuation-based of systems
Valuation networks have been proposed as graphical representations of valuation-based systems (VBSs).
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show valuation networks how paper, independence In relations. we encode this conditional
In this paper, we show how valuation networks encode conditional independence relations.
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discusses several methods This from for reasoning inconsistent and presents paper bases. knowledge
This paper presents and discusses several methods for reasoning from inconsistent knowledge bases.
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of handled theory. priority levels the in The framework are possibility
The priority levels are handled in the framework of possibility theory.
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design. to Application oil the offshore platforms illustrates
Application to offshore oil platforms illustrates the design.
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this system embedded in expert application, the real-time system. is normative For a
For this application, the normative system is embedded in a real-time expert system.
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of the dynamic, automating construction on models. decision been little There incremental has research
There has been little research on automating the dynamic, incremental construction of decision models.
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proposed the diagnosis. construction for hierarchical uniform decision A of value-driven is model method complete
A uniform value-driven method of decision model construction is proposed for the hierarchical complete diagnosis.
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modeled and Hierarchical complete influence process is diagnostic a using stochastic as formulated diagrams. reasoning
Hierarchical complete diagnostic reasoning is formulated as a stochastic process and modeled using influence diagrams.
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construction probe incrementally, models method interleaving model and evaluation. with This decision construct actions
This method construct decision models incrementally, interleaving probe actions with model construction and evaluation.
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tasks The method treats and uniformly. meta-level baselevel
The method treats meta-level and baselevel tasks uniformly.
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It calculations exactly those efficient to graphs. undirected corresponding on inference allows
It allows efficient inference calculations corresponding exactly to those on undirected graphs.
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weighted Watersheds been have graphs. edge defined node both for and
Watersheds have been defined both for node and edge weighted graphs.
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same weighted the and graph basin. minima with catchment edge)
edge) weighted graph with the same minima and catchment basin.
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values. optimal expected The the perfect the two of information difference between value is
The value of perfect information is the difference between the two optimal expected values.
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the evaluating proposed. of tradeoffs the are of accuracy/efficiency Methods
Methods of evaluating the accuracy/efficiency of the tradeoffs are proposed.
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still which addressed from instability, GIB-MAP be may ?approximate? a problem explanations using suffer
GIB-MAP explanations still suffer from instability, a problem which may be addressed using ?approximate?
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independence for as a condition irrelevance. conditional
conditional independence as a condition for irrelevance.
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on focuses literature the descriptors identification Most of holistic in closed-set applications. relevant
Most of the relevant literature focuses on holistic descriptors in closed-set identification applications.
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face to an verification approach then alternative propose SR. We via
We then propose an alternative approach to face verification via SR.
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utility-based to a categorization. take We approach
We take a utility-based approach to categorization.
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probabilities are presented. methods eliciting Parsimonious for dependent
Parsimonious methods for eliciting dependent probabilities are presented.
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models from we Bayesian Network In raw method learning of data. developed work previous a
In previous work we developed a method of learning Bayesian Network models from raw data.
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minimal on well method (MDL) the description This principle. relies known length
This method relies on the well known minimal description length (MDL) principle.
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work. that present we some our results In have paper arisen new this from
In this paper we present some new results that have arisen from our work.
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computing of particular, In length. local description way present the a new we
In particular, we present a new local way of computing the description length.
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This improvements allows in search our make algorithm. to us significant
This allows us to make significant improvements in our search algorithm.
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involving practical networks size. of is The of our experiments feasibility a demonstrated by approach
The feasibility of our approach is demonstrated by experiments involving networks of a practical size.
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while measures relative ambiguity those judgments. Probability surrounding likelihoods, vagueness measures
Probability measures relative likelihoods, while ambiguity measures vagueness surrounding those judgments.
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representation important of Ambiguity knowledge. is uncertain an
Ambiguity is an important representation of uncertain knowledge.
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uncertainty deals or probability by subjective of belief. modeled type a with different, It
It deals with a different, type of uncertainty modeled by subjective probability or belief.
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