Learning Rational Functions

International audienceRational functions are transformations from words to words that can be defined by string transducers. Rational functions are also captured by deterministic string transducers with lookahead. We show for the first time that the class of rational functions can be learned in the limit with polynomial time and data, when represented by string transducers with lookahead in the diagonal-minimal normal form that we introduce

Synthesizing Program Input Grammars

We present an algorithm for synthesizing a context-free grammar encoding the language of valid program inputs from a set of input examples and blackbox access to the program. Our algorithm addresses shortcomings of existing grammar inference algorithms, which both severely overgeneralize and are prohibitively slow. Our implementation, GLADE, leverages the grammar synthesized by our algorithm to fuzz test programs with structured inputs. We show that GLADE substantially increases the incremental coverage on valid inputs compared to two baseline fuzzers

Fundamento del derecho natural según los principios de la doctrina de la ciencia

1.-El carácter de la racionalidad consiste en que el agente [das Handelnde] y lo actuado [das Behandelte] son uno y lo mismo; y con esta descripción se ha agotado el ámbito de la razón como tal. El uso del lenguaje ha depositado en la palabra Yo este concepto sublime para aquéllos que son capaces de él, para los que son capaces de la abstracción de su propio Yo

Minimal Synthesis of String To String Functions From Examples

We study the problem of synthesizing string to string transformations from a set of input/output examples. The transformations we consider are expressed using deterministic finite automata (DFA) that read pairs of letters, one letter from the input and one from the output. The DFA corresponding to these transformations have additional constraints, ensuring that each input string is mapped to exactly one output string. We suggest that, given a set of input/output examples, the smallest DFA consistent with the examples is a good candidate for the transformation the user was expecting. We therefore study the problem of, given a set of examples, finding a minimal DFA consistent with the examples and satisfying the functionality and totality constraints mentioned above. We prove that, in general, this problem (the corresponding decision problem) is NP-complete. This is unlike the standard DFA minimization problem which can be solved in polynomial time. We provide several NP-hardness proofs that show the hardness of multiple (independent) variants of the problem. Finally, we propose an algorithm for finding the minimal DFA consistent with input/output examples, that uses a reduction to SMT solvers. We implemented the algorithm, and used it to evaluate the likelihood that the minimal DFA indeed corresponds to the DFA expected by the user.Comment: SYNT 201

Inducing Probabilistic Grammars by Bayesian Model Merging

We describe a framework for inducing probabilistic grammars from corpora of positive samples. First, samples are {\em incorporated} by adding ad-hoc rules to a working grammar; subsequently, elements of the model (such as states or nonterminals) are {\em merged} to achieve generalization and a more compact representation. The choice of what to merge and when to stop is governed by the Bayesian posterior probability of the grammar given the data, which formalizes a trade-off between a close fit to the data and a default preference for simpler models (`Occam's Razor'). The general scheme is illustrated using three types of probabilistic grammars: Hidden Markov models, class-based $n$-grams, and stochastic context-free grammars.Comment: To appear in Grammatical Inference and Applications, Second International Colloquium on Grammatical Inference; Springer Verlag, 1994. 13 page

Olive oil consumption and all-cause, cardiovascular and cancer mortality in an adult mediterranean population in Spain

Objective: We assessed the association between usual olive oil consumption (OOC) and all-cause, cardiovascular (CVD) and cancer mortality in an adult population in Spain. Materials and methods: OOC was evaluated at baseline in 1,567 participants aged 20 years and older from the Valencia Nutrition Study in Spain using validated food frequency questionnaires. During an 18-year follow-up period, 317 died, 115 due to CVD and 82 due to cancer. Cox regression models were used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (95%CI). Results: After adjusting for demographic and lifestyle factors, the OOC was associated with a lower risk of all-cause, CVD and cancer mortality. Compared to the less than once per month consumption, the consumption of up to one tablespoon per day was associated with a 9% lower risk of all-cause mortality (HR: 0.91; 95%CI: 0.68-1.22) and the consumption of 2 or more tablespoons with a 31% lower risk of all-cause mortality (HR: 0.69; 95%CI: 0.50–0.93; p-trend = 0.011). The consumption of 2 or more tablespoons per day was also associated with lower risk of mortality for CVD (HR: 0.54; 95%CI: 0.32–0.91; p-trend = 0.018) and cancer (HR: 0.49, 95%CI: 0.26–0.94; p-trend = 0.019). Conclusion: Higher olive oil consumption was associated with lower long-term risk of all-cause, CVD and cancer mortality in an adult Mediterranean population. The maximum benefit was observed for the consumption of two or more tablespoons per day. Copyright © 2022 Torres-Collado, García-de la Hera, Lopes, Compañ-Gabucio, Oncina-Cánovas, Notario-Barandiaran, González-Palacios and Vioque.The VNS study was supported by a grant from the Dirección General de Salud Pública, Generalitat Valenciana 1994 and the Fondo Investigacion Sanitaria (FIS 00/0985). This study has also received support from the Instituto de Salud Carlos III FEDER funds (FIS PI13/00654), CIBER of Epidemiology and Public Health (CIBERESP), CB06/02/0013 and ISABIAL

Melody recognition with learned edit distances

In a music recognition task, the classification of a new melody is often achieved by looking for the closest piece in a set of already known prototypes. The definition of a relevant similarity measure becomes then a crucial point. So far, the edit distance approach with a-priori fixed operation costs has been one of the most used to accomplish the task. In this paper, the application of a probabilistic learning model to both string and tree edit distances is proposed and is compared to a genetic algorithm cost fitting approach. The results show that both learning models outperform fixed-costs systems, and that the probabilistic approach is able to describe consistently the underlying melodic similarity model.This work was funded by the French ANR Marmota project, the Spanish PROSEMUS project (TIN2006-14932-C02), the research programme Consolider Ingenio 2010 (MIPRCV, CSD2007-00018), and the Pascal Network of Excellence

Learning Moore Machines from Input-Output Traces

The problem of learning automata from example traces (but no equivalence or membership queries) is fundamental in automata learning theory and practice. In this paper we study this problem for finite state machines with inputs and outputs, and in particular for Moore machines. We develop three algorithms for solving this problem: (1) the PTAP algorithm, which transforms a set of input-output traces into an incomplete Moore machine and then completes the machine with self-loops; (2) the PRPNI algorithm, which uses the well-known RPNI algorithm for automata learning to learn a product of automata encoding a Moore machine; and (3) the MooreMI algorithm, which directly learns a Moore machine using PTAP extended with state merging. We prove that MooreMI has the fundamental identification in the limit property. We also compare the algorithms experimentally in terms of the size of the learned machine and several notions of accuracy, introduced in this paper. Finally, we compare with OSTIA, an algorithm that learns a more general class of transducers, and find that OSTIA generally does not learn a Moore machine, even when fed with a characteristic sample

Pro-vegetarian dietary patterns and essential and heavy metal exposure in children of 4-5-years from the INfancia y medio Ambiente cohort (INMA)

Dietary patterns provide a comprehensive assessment of food consumption, including essential nutrients and potential exposure to environmental contaminants. While pro-vegetarian (PVG) dietary patterns have shown health benefits in adults, their effects on children are less well studied. This study aims to explore the association between children's adherence to the most common PVG dietary patterns and their exposure to metals, assessed through urine concentration. In our study, we included a population of 723 children aged 4-5-years from the INfancia y Medio Ambiente (INMA) cohort in Spain. We calculated three predefined PVG dietary patterns, namely general (gPVG), healthful (hPVG), and unhealthful (uPVG), using dietary information collected through a validated Food Frequency Questionnaire. Urinary concentrations of various essential and heavy metals (Co, Cu, Zn, Se, Mo, Pb, and Cd) were measured using mass spectrometry. Additionally, urinary arsenic speciation, including arsenobetaine (AsB), dimethylarsinic acid (DMA), monomethylarsonic acid (MMA), and inorganic arsenic (iAs), was measured. The sum of urinary MMA and iAs was used to assess iAs exposure. We estimated primary (PMI) and secondary iAs methylation (SMI) indices. To explore the association between PVG dietary patterns in quintiles and metal exposure, we utilized multiple-adjusted linear regression models and the quantile g-computation approach. Compared with the lowest quintile, participants in the highest quintile of gPVG showed a 22.7% lower urinary Co (95% confidence interval (CI): −38.7; −1.98) and a 12.6% lower Se (95%CI: −22.9; −1.00) concentrations. Second quintile of adherence to hPVG was associated with a 51.7% lower urinary iAs + MMA concentrations (95%CI: −74.3; −8.61). Second quintile of adherence to an uPVG was associated with a 13.6% lower Se levels (95%CI: −22.9; −2.95) while the third quintile to this pattern was associated with 17.5% lower Mo concentrations (95%CI: −29.5; −2.95). The fourth quintile of adherence to gPVG was associated with a 68.5% higher PMI and a 53.7% lower SMI. Our study showed that adherence to a gPVG dietary pattern in childhood may modestly reduce the intakes of some essential metals such as Co and Se. Further investigations are warranted to explore any potential health implications.</p

Pro-vegetarian dietary patterns and essential and heavy metal exposure in children of 4-5-years from the INfancia y medio Ambiente cohort (INMA)

Dietary patterns provide a comprehensive assessment of food consumption, including essential nutrients and potential exposure to environmental contaminants. While pro-vegetarian (PVG) dietary patterns have shown health benefits in adults, their effects on children are less well studied. This study aims to explore the association between children's adherence to the most common PVG dietary patterns and their exposure to metals, assessed through urine concentration. In our study, we included a population of 723 children aged 4-5-years from the INfancia y Medio Ambiente (INMA) cohort in Spain. We calculated three predefined PVG dietary patterns, namely general (gPVG), healthful (hPVG), and unhealthful (uPVG), using dietary information collected through a validated Food Frequency Questionnaire. Urinary concentrations of various essential and heavy metals (Co, Cu, Zn, Se, Mo, Pb, and Cd) were measured using mass spectrometry. Additionally, urinary arsenic speciation, including arsenobetaine (AsB), dimethylarsinic acid (DMA), monomethylarsonic acid (MMA), and inorganic arsenic (iAs), was measured. The sum of urinary MMA and iAs was used to assess iAs exposure. We estimated primary (PMI) and secondary iAs methylation (SMI) indices. To explore the association between PVG dietary patterns in quintiles and metal exposure, we utilized multiple-adjusted linear regression models and the quantile g-computation approach. Compared with the lowest quintile, participants in the highest quintile of gPVG showed a 22.7% lower urinary Co (95% confidence interval (CI): −38.7; −1.98) and a 12.6% lower Se (95%CI: −22.9; −1.00) concentrations. Second quintile of adherence to hPVG was associated with a 51.7% lower urinary iAs + MMA concentrations (95%CI: −74.3; −8.61). Second quintile of adherence to an uPVG was associated with a 13.6% lower Se levels (95%CI: −22.9; −2.95) while the third quintile to this pattern was associated with 17.5% lower Mo concentrations (95%CI: −29.5; −2.95). The fourth quintile of adherence to gPVG was associated with a 68.5% higher PMI and a 53.7% lower SMI. Our study showed that adherence to a gPVG dietary pattern in childhood may modestly reduce the intakes of some essential metals such as Co and Se. Further investigations are warranted to explore any potential health implications.</p