Learning an L1-regularized Gaussian Bayesian Network in the Equivalence Class Space

Learning the structure of a graphical model from data is a common task in a wide range of practical applications. In this paper, we focus on Gaussian Bayesian networks, i.e., on continuous data and directed acyclic graphs with a joint probability density of all variables given by a Gaussian. We propose to work in an equivalence class search space, specifically using the k-greedy equivalence search algorithm. This, combined with regularization techniques to guide the structure search, can learn sparse networks close to the one that generated the data. We provide results on some synthetic networks and on modeling the gene network of the two biological pathways regulating the biosynthesis of isoprenoids for the Arabidopsis thaliana plant

Comparing the effectiveness of equivalence partitioning, branch testing and code reading by stepwise abstraction applied by subjects

Some verification and validation techniques have been evaluated both theoretically and empirically. Most empirical studies have been conducted without subjects, passing over any effect testers have when they apply the techniques. We have run an experiment with students to evaluate the effectiveness of three verification and validation techniques (equivalence partitioning, branch testing and code reading by stepwise abstraction). We have studied how well able the techniques are to reveal defects in three programs. We have replicated the experiment eight times at different sites. Our results show that equivalence partitioning and branch testing are equally effective and better than code reading by stepwise abstraction. The effectiveness of code reading by stepwise abstraction varies significantly from program to program. Finally, we have identified project contextual variables that should be considered when applying any verification and validation technique or to choose one particular technique.

Proof of concept of an imaging system demonstrator for PET applications with SiPM

A PET imaging system demonstrator based on LYSO crystal arrays coupled to SiPM matrices is under construction at the University and INFN of Pisa. Two SiPM matrices, composed of 8×8 SiPM pixels, and 1,5 mm pitch, have been coupled one to one to a LYSO crystals array and read out by a custom electronics system. front-end ASICs were used to read 8 channels of each matrix. Data from each front-end were multiplexed and sent to a DAQ board for the digital conversion; a motherboard collects the data and communicates with a host computer through a USB port for the storage and off-line data processing. In this paper we show the first preliminary tomographic image of a point-like radioactive source acquired with part of the two detection heads in time coincidence.

Operational Aspects of Full Reduction in Lambda Calculi

Esta tesis estudia la reducción plena (‘full reduction’ en inglés) en distintos cálculos lambda. 1 En esencia, la reducción plena consiste en evaluar los cuerpos de las funciones en los lenguajes de programación funcional con ligaduras. Se toma el cálculo lambda clásico (i.e., puro y sin tipos) como el sistema formal que modela el paradigma de programación funcional. La reducción plena es una técnica fundamental cuando se considera a los programas como datos, por ejemplo para la optimización de programas mediante evaluación parcial, o cuando algún atributo del programa se representa a su vez por un programa, como el tipo en los demostradores automáticos de teoremas actuales. Muchas semánticas operacionales que realizan reducción plena tienen naturaleza híbrida. Se introduce formalmente la noción de naturaleza híbrida, que constituye el hilo conductor de todo el trabajo. En el cálculo lambda la naturaleza híbrida se manifiesta como una ‘distinción de fase’ en el tratamiento de las abstracciones, ya sean consideradas desde fuera o desde dentro de si mismas. Esta distinción de fase conlleva una estructura en capas en la que una semántica híbrida depende de una o más semánticas subsidiarias. Desde el punto de vista de los lenguajes de programación, la tesis muestra como derivar, mediante técnicas de transformación de programas, implementaciones de semánticas operacionales que reducen plenamente a partir de sus especificaciones. Las técnicas de transformación de programas consisten en transformaciones sintácticas que preservan la equivalencia semántica de los programas. Se ajustan las técnicas de transformación de programas existentes para trabajar con implementaciones de semánticas híbridas. Además, se muestra el impacto que tiene la reducción plena en las implementaciones que utilizan entornos. Los entornos son un ingrediente fundamental en las implementaciones realistas de una máquina abstracta. Desde el punto de vista de los sistemas formales, la tesis desvela una teoría novedosa para el cálculo lambda con paso por valor (‘call-by-value lambda calculus’ en inglés) que es consistente con la reducción plena. Dicha teoría induce una noción de equivalencia observacional que distingue más puntos que las teorías existentes para dicho cálculo. Esta contribución ayuda a establecer una ‘teoría estándar’ en el cálculo lambda con paso por valor que es análoga a la ‘teoría estándar’ del cálculo lambda clásico propugnada por Barendregt. Se presentan resultados de teoría de la demostración, y se sugiere como abordar el estudio de teoría de modelos. ABSTRACT This thesis studies full reduction in lambda calculi. In a nutshell, full reduction consists in evaluating the body of the functions in a functional programming language with binders. The classical (i.e., pure untyped) lambda calculus is set as the formal system that models the functional paradigm. Full reduction is a prominent technique when programs are treated as data objects, for instance when performing optimisations by partial evaluation, or when some attribute of the program is represented by a program itself, like the type in modern proof assistants. A notable feature of many full-reducing operational semantics is its hybrid nature, which is introduced and which constitutes the guiding theme of the thesis. In the lambda calculus, the hybrid nature amounts to a ‘phase distinction’ in the treatment of abstractions when considered either from outside or from inside themselves. This distinction entails a layered structure in which a hybrid semantics depends on one or more subsidiary semantics. From a programming languages standpoint, the thesis shows how to derive implementations of full-reducing operational semantics from their specifications, by using program transformations techniques. The program transformation techniques are syntactical transformations which preserve the semantic equivalence of programs. The existing program transformation techniques are adjusted to work with implementations of hybrid semantics. The thesis also shows how full reduction impacts the implementations that use the environment technique. The environment technique is a key ingredient of real-world implementations of abstract machines which helps to circumvent the issue with binders. From a formal systems standpoint, the thesis discloses a novel consistent theory for the call-by-value variant of the lambda calculus which accounts for full reduction. This novel theory entails a notion of observational equivalence which distinguishes more points than other existing theories for the call-by-value lambda calculus. This contribution helps to establish a ‘standard theory’ in that calculus which constitutes the analogous of the ‘standard theory’ advocated by Barendregt in the classical lambda calculus. Some prooftheoretical results are presented, and insights on the model-theoretical study are given.