Inference and learning in hybrid probabilistic network

This paper proposed a novel hybrid probabilistic network, which is a good tradeoff between the model complexity and learnability in practice. It relaxes the conditional independence assumptions of Naive Bayes while still permitting efficient inference and learning. Experimental studies on a set of natural domains prove its clear advantages with respect to the generalization ability.     

Conditions for the Acceptance of Deontic Conditionals.

Recent psychological research has investigated how people assess the probability of an indicative conditional. Most people give the conditional probability of q given p as the probability of if p then q. Asking about the probability of an indicative conditional, one is in effect asking about its acceptability. But on what basis are deontic conditionals judged to be acceptable or unacceptable? Using a decision theoretic analysis, we argue that a deontic conditional, of the form if p then must q or if p then may q, will be judged acceptable to the extent that the p & q possibility is preferred to the p & not-q possibility. Two experiments are reported in which this prediction was upheld. There was also evidence that the pragmatic suitability of permission rules is partly determined by evaluations of the not-p & q possibility. Implications of these results for theories of deontic reasoning are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

"Temporal encoding in fear conditioning revealed through associative reflex facilitation": Correction to Lindquist and Brown (2004).

Reports an error in "Temporal Encoding in Fear Conditioning Revealed Through Associative Reflex Facilitation" by Derick H. Lindquist and Thomas H. Brown (Behavioral Neuroscience, 2004[Apr], Vol 118[2], 395-402). The article contained several errors. On page 396, second paragraph, the sentence beginning on line 6 should read as follows: "Having a stable baseline is critical for studies of reflex facilitation because the experimental designs invariably entail repetitive CR testing, if only to achieve reasonable statistical power (see Choi et al., 2001b; Lindquist & Brown, 2004)." On page 400, the first heading should read as follows: "Comparison of New and Old Reflex Facilitation Procedures." On page 400, the first sentence under the abovementioned heading should read as follows: "We decided not to use the original measure of reflex facilitation, developed by J. S. Brown et al. (1951), because it suffers from severe interpretational limitations, elaborated in detail elsewhere (Choi et al., 2001b; Leaton & Cranney, 1990; Lindquist & Brown, 2004)." (The following abstract of the original article appeared in record 2004-12681-016.) Temporal encoding in Pavlovian fear conditioning was examined through conditional facilitation of the short-latency (Rl) component of the rat eyeblink reflex. Rats were fear-conditioned to a tone conditional stimulus (CS) with either a 3- or 9-s interstimulus interval (ISI) between CS onset and the onset of the grid-shock unconditional stimulus (US). Rl facilitation was tested over 2 days, in counterbalanced order, at a latency of 3 s and 9 s from CS onset. CS-produced Rl facilitation, the conditional response (CR), was 3-4 times larger when the test latency equaled the conditioning ISI. These results, coupled with the known neurophysiology of Rl facilitation, suggest that this CR could disclose differences in the time course of CS-generated output from the amygdala when driven by cortical versus subcortical CS-CR pathways. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Promise is Debt, Threat Another Matter: The Effect of Credibility on the Interpretation of Conditional Promises and Threats.

Evidence from reasoning tasks shows that promises and threats both tend to receive biconditional interpretations. They also both display high speaker control. On the face of it, the only difference seems to be the positive or negative signing of the consequent. In a promise, the speaker tries to persuade the hearer to do something by holding out the prospect of a particular reward; in a threat, the speaker tries to refrain the hearer from doing something by holding out the prospect of a particular punishment. This paper investigates the respects in which conditional promises and threats differ further by means of an inference task. The credibility of the consequent was manipulated in order to examine whether the acceptability ratings of inferences based on promises and on threats would be equally affected. The results of the inference task and an analysis of the reasons people give for their answers suggest that the credibility of promises is less affected by the use of excessive consequents than the credibility of threats. In other words, promise remains debt, whereas threat is another matter. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Inference for pth‐order random coefficient integer‐valued autoregressive processes

Abstract. A pth‐order random coefficient integer‐valued autoregressive [RCINAR(p)] model is proposed for count data. Stationarity and ergodicity properties are established. Maximum likelihood, conditional least squares, modified quasi‐likelihood and generalized method of moments are used to estimate the model parameters. Asymptotic properties of the estimators are derived. Simulation results on the comparison of the estimators are reported. The models are applied to two real data sets.     

The meaning(s) of conditionals: Conditional probabilities, mental models, and personal utilities.

[Correction Notice: An erratum for this article was reported in Vol 29(6) of Journal of Experimental Psychology: Learning, Memory, and Cognition (see record 2007-16865-001). On page 684, Table 4, all correlations should have been identified as having a pp then q") as indicating a high conditional probability P(q|p). Participants estimated the probability that a given conditional is true (Experiments 1A, 1B, and 3) or judged whether a conditional was true or false (Experiments 2 and 4) given information about the frequencies of the relevant truth table cases. Judgments were strongly influenced by the ratio of pq to p?q cases, supporting the conditional probability account. In Experiments 1A, 1B, and 3, judgments were also affected by the frequency of pq cases, consistent with a version of mental model theory. Experiments 3 and 4 extended the results to thematic conditionals and showed that the pragmatic utility associated with believing a statement also affected the degree of belief in conditionals but not in logically equivalent quantified statements. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Efficient Legendre moment computation for grey level images

Legendre orthogonal moments have been widely used in the field of image analysis. Because their computation by a direct method is very time expensive, recent efforts have been devoted to the reduction of computational complexity. Nevertheless, the existing algorithms are mainly focused on binary images. We propose here a new fast method for computing the Legendre moments, which is not only suitable for binary images but also for grey level images. We first establish a recurrence formula of one-dimensional (1D) Legendre moments by using the recursive property of Legendre polynomials. As a result, the 1D Legendre moments of order p, L_p=L_p(0), can be expressed as a linear combination of L_p-1(1) and L_p-2(0). Based on this relationship, the 1D Legendre moments L_p(0) can thus be obtained from the arrays of L₁(a) and L₀(a), where a is an integer number less than p. To further decrease the computation complexity, an algorithm, in which no multiplication is required, is used to compute these quantities. The method is then extended to the calculation of the two-dimensional Legendre moments L_pq. We show that the proposed method is more efficient than the direct method.     

中性红的光谱电化学研究

用ＦＯＳＥＣＳ研究了中性红的光谱电化学特性，测定了它的热力学函数、条件平衡常数和参加电极反应的Ｈ＾＋数，其结果与文献值一致。     

Implicit induction in conditional theories

We propose a new procedure for proof by induction in conditional theories where case analysis is simulated by term rewriting. This technique reduces considerably the number of variables of a conjecture to be considered for applying induction schemes. Our procedure is presented as a set of inference rules whose correctness has been formally proved. Moreover, when the axioms are ground convergent and the functions are completely defined, it is possible to apply the system for refuting conjectures. The procedure is even refutationally complete for conditional equations with Boolean preconditions over free constructors. The method is entirely implemented in the proverSPIKE. This system has solved interesting problems in a completely automatic way, that is, without interaction with the user and without ad hoc heuristics. It has also proved the challenging Gilbreath card trick, with only two easy lemmas.Preliminary versions of the results have been presented at the 13th International Joint Conference on Artificial Intelligence, Chambéry (France), 1993 (Bouhoula and Rusinowith, 1993).