Search results for "probabilistic"
showing 10 items of 380 documents
Frequency format facilitates reasoning in simple numerical tasks.
2005
This study examined whether it is easier to reason in terms of frequencies or with percentages for simple numerical tasks. Research on probabilistic reasoning has shown that humans can draw correct inferences when problems are presented in terms of natural frequencies but not when in percentages. Whether the same effect can be observed in other numerically simple tasks which are not probabilistic was studied with 40 undergraduate students who volunteered for the experiment (13 men, 27 women; M age of 23 yr.). In a simple numerical task involving frequencies or percentages ( N = 20), their performance showed representation in frequencies facilitates the task.
Logical Operations among Conditional Events: theoretical aspects and applications
2019
We generalize the notions of conjunction and disjunction of two conditional events to the case of $n$ conditional events. These notions are defined, in the setting of coherence, by means of suitable conditional random quantities with values in the interval $[0,1]$. We also define the notion of negation, by verifying De Morgan's Laws. Then, we give some results on coherence of prevision assessments for some families of compounded conditionals and we show that some well known properties which are satisfied by conjunctions and disjunctions of unconditional events are also satisfied by conjunctions and disjunction of conditional events. We also examine in detail the coherence of the prevision a…
Interpreting Connexive Principles in Coherence-Based Probability Logic
2021
We present probabilistic approaches to check the validity of selected connexive principles within the setting of coherence. Connexive logics emerged from the intuition that conditionals of the form If \(\mathord {\thicksim }A\), then A, should not hold, since the conditional’s antecedent \(\mathord {\thicksim }A\) contradicts its consequent A. Our approach covers this intuition by observing that for an event A the only coherent probability assessment on the conditional event \(A|\bar{A}\) is \(p(A|\bar{A})=0\). Moreover, connexive logics aim to capture the intuition that conditionals should express some “connection” between the antecedent and the consequent or, in terms of inferences, valid…
Quasi conjunction and p-entailment in nonmonotonic reasoning
2010
We study, in the setting of coherence, the extension of a probability assessment defined on n conditional events to their quasi conjunction. We consider, in particular, two special cases of logical dependencies; moreover, we examine the relationship between the notion of p-entailment of Adams and the inclusion relation of Goodman and Nguyen. We also study the probabilistic semantics of the QAND rule of Dubois and Prade; then, we give a theoretical result on p-entailment.
Probabilistic squares and hexagons of opposition under coherence
2017
Various semantics for studying the square of opposition and the hexagon of opposition have been proposed recently. We interpret sentences by imprecise (set-valued) probability assessments on a finite sequence of conditional events. We introduce the acceptability of a sentence within coherence-based probability theory. We analyze the relations of the square and of the hexagon in terms of acceptability. Then, we show how to construct probabilistic versions of the square and of the hexagon of opposition by forming suitable tripartitions of the set of all coherent assessments on a finite sequence of conditional events. Finally, as an application, we present new versions of the square and of the…
Statistically Validated Networks for evaluating coherence in topic models
2022
Probabilistic topic models have become one of the most widespread machine learning technique for textual analysis purpose. In this framework, Latent Dirichlet Allocation (LDA) gained more and more popularity as a text modelling technique. The idea is that documents are represented as random mixtures over latent topics, where a distribution over words characterizes each topic. Unfortunately, topic models do not guarantee the interpretability of their outputs. The topics learned from the model may be characterized by a set of irrelevant or unchained words, being useless for the interpretation. In the framework of topic quality evaluation, the pairwise semantic cohesion among the top-N most pr…
A probabilistic compressive sensing framework with applications to ultrasound signal processing
2019
Abstract The field of Compressive Sensing (CS) has provided algorithms to reconstruct signals from a much lower number of measurements than specified by the Nyquist-Shannon theorem. There are two fundamental concepts underpinning the field of CS. The first is the use of random transformations to project high-dimensional measurements onto a much lower-dimensional domain. The second is the use of sparse regression to reconstruct the original signal. This assumes that a sparse representation exists for this signal in some known domain, manifested by a dictionary. The original formulation for CS specifies the use of an l 1 penalised regression method, the Lasso. Whilst this has worked well in l…
Understanding disease mechanisms with models of signaling pathway activities
2014
Background Understanding the aspects of the cell functionality that account for disease or drug action mechanisms is one of the main challenges in the analysis of genomic data and is on the basis of the future implementation of precision medicine. Results Here we propose a simple probabilistic model in which signaling pathways are separated into elementary sub-pathways or signal transmission circuits (which ultimately trigger cell functions) and then transforms gene expression measurements into probabilities of activation of such signal transmission circuits. Using this model, differential activation of such circuits between biological conditions can be estimated. Thus, circuit activation s…
Proof I: Upper Bounds
2019
In this chapter we study upper bounds on singular values and determinants of certain operators related to Pδ. The bounds are not probabilistic; they only depend on a certain smallness of the perturbation.
Fuzzy filter design for discrete-time delayed systems with distributed probabilistic sensor faults
2013
In this paper, the problem of distributed fuzzy filter design has been solved for T-S fuzzy systems with time-varying delays and multiple probabilistic packet losses. Our attention is paid to designing the distributed fuzzy filters to guarantee the filtering error dynamic system to be mean-square asymptotically stable with an average ℋ∞ performance. Sufficient conditions for the obtained filtering error dynamic system are proposed by applying a comparison model and the scaled small gain theorem. Based on the measurements and estimates of the system states for each sensor and its neighbors, the solution of the parameters of the distributed fuzzy filters is characterized in terms of the feasi…