Datasets:
damilojohn
/
Text-Descrambling

Dataset card Data Studio Files
xet
 Community
text
stringlengths
27
153
label
stringlengths
27
153
id
int64
0
40k
classic about penguin is the A most Tweety. example
A most classic example is about the penguin Tweety.
6,800
in on works inheritance. focused primarily probabilistic this have Previous area
Previous works in this area have primarily focused on probabilistic inheritance.
6,801
Networks. and operations the state coarsening presents This two refining Bayesian paper in space for
This paper presents two operations for refining and coarsening the state space in Bayesian Networks.
6,802
for also acquisition. their We knowledge implications practical discuss
We also discuss their practical implications for knowledge acquisition.
6,803
are other representing Reiter's Though this distinction, capable formalism is of original not. approaches
Though Reiter's original formalism is capable of representing this distinction, other approaches are not.
6,804
of is closely to probability paradox Simpson's The theory. related problem
The problem is closely related to Simpson's paradox of probability theory.
6,805
reasoning with We information problem concerned the credibility into are type introducing of systems.
We are concerned with the problem of introducing credibility type information into reasoning systems.
6,806
information to provided discount The of by concept credibility allows us agents.
The concept of credibility allows us to discount information provided by agents.
6,807
credibility qualification reasoning. approximate We of the suggest representational theory scheme for a in
We suggest a representational scheme for credibility qualification in the theory of approximate reasoning.
6,808
We of the discuss credibility. relative concept
We discuss the concept of relative credibility.
6,809
situation to structures very in This much the of nonmonotonic leads reasoning. spirit
This situation leads to structures very much in the spirit of nonmonotonic reasoning.
6,810
of on approach in exploitation based is equations The max-min algebra. the
The approach is based on the exploitation of equations in max-min algebra.
6,811
limit includes of case precise information. the certain and This formalism
This formalism includes the limit case of certain and precise information.
6,812
adding at a time. one built The incrementally is network node
The network is built incrementally adding one node at a time.
6,813
in can answer queries predicate that independencies about The a the domain. model probabilistic is
The probabilistic model is a predicate that can answer queries about independencies in the domain.
6,814
implemented in In model ways. can the practice be various
In practice the model can be implemented in various ways.
6,815
of research. discuss solution propose for future limitations We this this directions and
We discuss limitations of this solution and propose future directions for this research.
6,816
cycles reasoning task The in most handling be difficult may probabilistic in belief directed networks.
The most difficult task in probabilistic reasoning may be handling directed cycles in belief networks.
6,817
a multidisorder Such produced called for clustering. diagnosis symptom by candidate sets recent are method
Such candidate sets are produced by a recent method for multidisorder diagnosis called symptom clustering.
6,818
of formalizes implementation functions Truth Assumption-based Maintenance analysis (ATMS). an Belief within the This System
This analysis formalizes the implementation of Belief functions within an Assumption-based Truth Maintenance System (ATMS).
6,819
Dempster visual VICTORS Without Shafer (i.e. all theory, possible interpretations computes
Without Dempster Shafer theory, VICTORS computes all possible visual interpretations (i.e.
6,820
best the without interpretation(s). determining logical models) all
all logical models) without determining the best interpretation(s).
6,821
is constraints A of from of system method calculating presented. marginal probability values a
A method of calculating probability values from a system of marginal constraints is presented.
6,822
expert . This system calculating appropriate for time in method a real is probabilities
This method is appropriate for calculating probabilities in a real time expert system .
6,823
normal study of multiscale presents skin mathematical This a model hybrid (vSkin).
This study presents a hybrid multiscale mathematical model of normal skin (vSkin).
6,824
observations. with our as experimental are results These well as clinical consistent predictions
These predictions are consistent with our experimental results as well as clinical observations.
6,825
technique error an The algorithm function. involves greedy search that using locally a minimizes
The technique involves using a greedy search algorithm that locally minimizes an error function.
6,826
reasoning, accounting the for Scenario-based the causal of generation alternative involves "stories" The other, evidence.
The other, Scenario-based reasoning, involves the generation of alternative causal "stories" accounting for the evidence.
6,827
well employ as probabilistic schemes as Both causal knowledge.
Both schemes employ causal as well as probabilistic knowledge.
6,828
Probabilities be may numbers. and/or as presented phrases
Probabilities may be presented as phrases and/or numbers.
6,829
control can style, completeness explanations. and abstraction Users the of
Users can control the style, abstraction and completeness of explanations.
6,830
in mid show a detection peak in speeds. browsing results Our performance
Our results show a peak in detection performance in mid browsing speeds.
6,831
single masses. or micro-calcifications by simulated inserting Lesion are cases
Lesion cases are simulated by inserting single micro-calcifications or masses.
6,832
improve of ways them are to methods and our Limitations discussed.
Limitations of our methods and ways to improve them are discussed.
6,833
Previous the linguistic probabilities and between has absolute work empirical correspondence investigated phrases.
Previous empirical work has investigated the correspondence between absolute probabilities and linguistic phrases.
6,834
describe such to selected phrases probability updates. numerical best Subjects
Subjects selected such phrases to best describe numerical probability updates.
6,835
the before managing of focuses This cost action. on paper deliberation
This paper focuses on managing the cost of deliberation before action.
6,836
a consisting with into boolean of belief (i.e. nodes The network is only compiled network
The belief network is compiled into a network consisting only of nodes with boolean (i.e.
6,837
on the is using resulting search found a best-first then MAP network. The assignment
The MAP assignment is then found using a best-first search on the resulting network.
6,838
during IDEAL development. and some describes This paper lessons its learned
This paper describes IDEAL and some lessons learned during its development.
6,839
representing problems. and optimization describes for solving discrete paper This systems valuation-based
This paper describes valuation-based systems for representing and solving discrete optimization problems.
6,840
called the function. objective an valuations, of factors functions, The represent
The functions, called valuations, represent the factors of an objective function.
6,841
the using operations problem called and marginalization. involves optimization two Solving combination
Solving the optimization problem involves using two operations called combination and marginalization.
6,842
of the factors us the objective joint function. how combine tells Combination to
Combination tells us how to combine the factors of the joint objective function.
6,843
non-serial For method systems valuation-based solution the problems, of optimization programming. to reduces dynamic
For optimization problems, the solution method of valuation-based systems reduces to non-serial dynamic programming.
6,844
use dynamic that axioms programming. viewed permit as conditions the And be our can of
And our axioms can be viewed as conditions that permit the use of dynamic programming.
6,845
But, procedures to are strongly the the support Bayesian more also hypothesis. likely wrong
But, the Bayesian procedures are also more likely to strongly support the wrong hypothesis.
6,846
techniques more powerful, more Bayesian also are but error prone. are
Bayesian techniques are more powerful, but are also more error prone.
6,847
is idea this inference paper, of an policy some the detail. in explored In
In this paper, the idea of an inference policy is explored in some detail.
6,848
of characteristics are To inference this support policies standard nonstandard some exploration, the and examined.
To support this exploration, the characteristics of some standard and nonstandard inference policies are examined.
6,849
introduced established. the a are expert approximations on through Bounds system into CPN-based errors
Bounds on the errors introduced into a CPN-based expert system through approximations are established.
6,850
number solve algorithms belief A have developed to on problems probabilistic of inference networks. been
A number of algorithms have been developed to solve probabilistic inference problems on belief networks.
6,851
sound. show and the are optimal transformations We
We show the transformations are optimal and sound.
6,852
describe considerably networks. an environment generating We process simplifies of the Bayesian that belief
We describe an environment that considerably simplifies the process of generating Bayesian belief networks.
6,853
Augustus of analysis proposed. is An busts
An analysis of Augustus busts is proposed.
6,854
However, of probability the aggregates, lack e.g.
However, the lack of probability aggregates, e.g.
6,855
this to In extend probability we allow paper, arbitrary DHPP aggregates.
In this paper, we extend DHPP to allow arbitrary probability aggregates.
6,856
Limited of the implementation provided. empirical data on an are methodology
Limited empirical data on an implementation of the methodology are provided.
6,857
a special This theories. proof of presents cases paper some between equivalence these straightforward
This paper presents a straightforward equivalence proof between some special cases of these theories.
6,858
To in an actions. the about world, operate must its intelligently reason agent
To operate intelligently in the world, an agent must reason about its actions.
6,859
temporal propositional paper reasoning This representing a about and logic presents for actions. probability
This paper presents a propositional temporal probability logic for representing and reasoning about actions.
6,860
that the various logic facts occur events represent The probability times. hold and can at
The logic can represent the probability that facts hold and events occur at various times.
6,861
affect represent and that future. can actions It the probability events the other
It can represent the probability that actions and other events affect the future.
6,862
The over time. probability model probabilities of relates
The model of probability relates probabilities over time.
6,863
Several the given. logic illustrating use the of are examples
Several examples illustrating the use of the logic are given.
6,864
probabilistic belief Key words: inference, computational complexity simulation, theory, algorithms. randomized stochastic networks,
Key words: probabilistic inference, belief networks, stochastic simulation, computational complexity theory, randomized algorithms.
6,865
relevant with associated time-points the of occurrence events.
time-points associated with the occurrence of relevant events.
6,866
are of analogues and Jeffrey's discussed. first of In the rule introduced conditioning cases, two
In the two first cases, analogues of Jeffrey's rule of conditioning are introduced and discussed.
6,867
possibilistic Shenoy's rule that combination counterpart. well-known shown has a It is
It is shown that Shenoy's combination rule has a well-known possibilistic counterpart.
6,868
None qualification has Dempster-Shafer. models the received of these of
None of these models has received the qualification of Dempster-Shafer.
6,869
down. the component conclusions is these once dynamic But break considered,
But once the dynamic component is considered, these conclusions break down.
6,870
too restricted. on based is the static comparison only Any component
Any comparison based only on the static component is too restricted.
6,871
object this search task. call We the
We call this the object search task.
6,872
medical On-line over is time. short of relatively a data period available
On-line medical data is available over a relatively short period of time.
6,873
extracted from with are opinions. Functions (Dempster-Shafer modified then theory) and Belief expert data first
Belief Functions (Dempster-Shafer theory) are first extracted from data and then modified with expert opinions.
6,874
symptoms about Expert and opinions information among derived dependencies are also statistically compared.
Expert opinions and statistically derived information about dependencies among symptoms are also compared.
6,875
theory for argument. presented computational of A is probabilistic framework a
A framework is presented for a computational theory of probabilistic argument.
6,876
knowledge Probabilistic Reasoning levels. The encodes Environment at three
The Probabilistic Reasoning Environment encodes knowledge at three levels.
6,877
of encoding a are knowledge. the deepest schemata the system's At level set domain
At the deepest level are a set of schemata encoding the system's domain knowledge.
6,878
constructed the level network Bayesian top is Finally, at from a the arguments.
Finally, at the top level is a Bayesian network constructed from the arguments.
6,879
paper, this of optimum is networks In decomposition discussed. belief
In this paper, optimum decomposition of belief networks is discussed.
6,880
allow have cycles We and nommonotonic nonmonotonic inferences RUM within to rules. extended
We have extended RUM to allow nommonotonic inferences and cycles within nonmonotonic rules.
6,881
a basis measures for among multiple Uncertainty defaults. provide deciding
Uncertainty measures provide a basis for deciding among multiple defaults.
6,882
the defaults optimal Different for finding discussed. heuristics algorithms and are
Different algorithms and heuristics for finding the optimal defaults are discussed.
6,883
problems all of involve Nearly reasoning uncertainty or another. one spatial sort
Nearly all spatial reasoning problems involve uncertainty of one sort or another.
6,884
in arises used sensors inaccuracies the angles. distances due measuring of to and Uncertainty
Uncertainty arises due to the inaccuracies of sensors used in measuring distances and angles.
6,885
We refer as this directional to uncertainty.
We refer to this as directional uncertainty.
6,886
also Uncertainty in with spatial information location mistakenly when arises combining is one identified another.
Uncertainty also arises in combining spatial information when one location is mistakenly identified with another.
6,887
as uncertainty. to recognition this refer We
We refer to this as recognition uncertainty.
6,888
arise We attention the problems to due particular to uncertainty. that recognition pay
We pay particular attention to the problems that arise due to recognition uncertainty.
6,889
this overly Response or has to either been view pessimistic. enthusiastic unduly
Response to this view has been either overly enthusiastic or unduly pessimistic.
6,890
expended for is available for However, reformulation time performing not inference.
However, time expended for reformulation is not available for performing inference.
6,891
We uncertainty. principles for general describe of the ideal under computing partition first resources shall
We shall describe first general principles for computing the ideal partition of resources under uncertainty.
6,892
problems illustrates these An example given how is arise. that
An example is given that illustrates how these problems arise.
6,893
a usage. investigation that finite The be limited of probability very model shows may
The investigation shows that a finite probability model may be of very limited usage.
6,894
decision-theoretic Problem Bayesian control BPS, the applies to probabilistic inference Solver, problem-solving. resource-constrained and flexible,
BPS, the Bayesian Problem Solver, applies probabilistic inference and decision-theoretic control to flexible, resource-constrained problem-solving.
6,895
sound significantly traditional with outperform By computational effort. performing inference, less BPS can techniques
By performing sound inference, BPS can outperform traditional techniques with significantly less computational effort.
6,896
a information. means expressing however, Probability incompleteness for constitute of intervals,
Probability intervals, however, constitute a means for expressing incompleteness of information.
6,897
data a to discussed between Finally, distinguish it rare and case. how conflicting is
Finally, it is discussed how to distinguish between conflicting data and a rare case.
6,898
basic search of used has control as unit. previously its Decision-theoretic
Decision-theoretic control of search has previously used as its basic unit.
6,899