Generalization Bounds in the Predict-then-Optimize Framework

The predict-then-optimize framework is fundamental in many practical settings: predict the unknown parameters of an optimization problem, and then solve the problem using the predicted values of the parameters. A natural loss function in this environment is to consider the cost of the decisions induced by the predicted parameters, in contrast to the prediction error of the parameters. This loss function was recently introduced in Elmachtoub and Grigas (2017) and referred to as the Smart Predict-then-Optimize (SPO) loss. In this work, we seek to provide bounds on how well the performance of a prediction model fit on training data generalizes out-of-sample, in the context of the SPO loss. Since the SPO loss is non-convex and non-Lipschitz, standard results for deriving generalization bounds do not apply. We first derive bounds based on the Natarajan dimension that, in the case of a polyhedral feasible region, scale at most logarithmically in the number of extreme points, but, in the case of a general convex feasible region, have linear dependence on the decision dimension. By exploiting the structure of the SPO loss function and a key property of the feasible region, which we denote as the strength property, we can dramatically improve the dependence on the decision and feature dimensions. Our approach and analysis rely on placing a margin around problematic predictions that do not yield unique optimal solutions, and then providing generalization bounds in the context of a modified margin SPO loss function that is Lipschitz continuous. Finally, we characterize the strength property and show that the modified SPO loss can be computed efficiently for both strongly convex bodies and polytopes with an explicit extreme point representation.Comment: Preliminary version in NeurIPS 201

Jupiter's red spot in 1968 - 1969

Photographic observations of Jupiter Red Spo

The Specialist Chambers and the Specialist Prosecutor’s Office in Kosovo. The ‘Regionalization’ of International Criminal Justice in Context

In August 2015, Kosovo established the Specialist Chambers (SC) and the Specialist Prosecutor’s Office (SPO) with the mandate of prosecuting international and transborder crimes committed during and after the 1998^1999 armed conflict. This article examines the founding instruments of the SC and the SPO, the influence of certain regional organizations in their creation and management, their organization, jurisdiction, legal nature and the function they exercise within the international legal system. The key question is whether the SC and the SPO may be included in existing categories of judicial entities established to deal with international criminal justice. The article concludes that they represent a regional variation of mixed criminal tribunals

Obywatele ACTA

S\u142owa kluczowe: ruchy spo\u142eczne; nowe media; dyskusje publiczne; ruch obywatelski; internet; media cyfrowe; portale spo\u142eczno\u15bciow

Software process measuring model

U ovom radu opisan je Model mjerenja softverskog procesa (MMSP). MMSP je metoda procjene softverskih procesa, kvantitativnog mjerenja i unapređenja procesa za organizacije koje se bave razvojem softvera (SPO). Metoda je razvijena dijelom na temelju poboljšanja metoda CMM/CMMI, Bootstrap i SPICE, i na standardima ESA PSS05 i ISO 90003. U žarištu MMSP-a je proces razvoja softvera u softverskim poduzećima. Članak objašnjava glavni koncept dobavljanja podataka o softverskim inženjerskim organizacijama i njihovim projektima pomoću temeljito izgrađenog upitnika. MMSP se može interpretirati kao metoda za opisivanje kakav je položaj organizacije i koje se promjene predlažu u slijedećim koracima. Osnovna ideja MMSP-a je utvrditi profil zrelosti procesa SPO-a. Ciljevi MMSP procjene su: a) izmjeriti i razviti profil zrelosti kvalitete procesa prikazom jakih i slabih strana procijenjenog SPŠO-a, b) derivirati korake za unapređenja iz prikazanog profila kvalitete procesa. Prikazan je rezultat procjene obavljene u jedan dan u organizaciji koja se bavi proizvodnjom softvera (SPO X) i Projekta X unutar SPO-a X koji je održan početkom listopada 2010. Rezultati procjene prikazuju ukupne organizacijske i metodološke razine za Projekt X. Organizacija je na razini zrelosti od 2,83. Metodologija je na razini zrelosti od 2,48. Ukupna razina zrelosti za organizaciju SPO X je na razini zrelosti od 2,42, dok je metodologija na razini zrelosti od 2,57. Organizacija članka je sljedeća: nakon uvoda u poglavlju jedan, poglavlje dva objašnjava razloge razvoja sustava MMSP. Poglavlje tri opisuje razvoj MMSP-a. Algoritam razina zrelosti je prikazan u slijedećem poglavlju. Poglavlje pet objašnjava evaluaciju SPO-a, rezultati procjene prikazani su u poglavlju šest. Poglavlje sedam sadrži zaključak, popis literature je u poglavlju osam.In this paper the Software Process Measuring Model (SPMM) is described. SPMM is a method for software process assessment, quantitative measurement and improvement for software producing organizations (SPOs). It has been developed partly based on a renovation of the CMM/CMMI, Bootstrap and SPICE methods, standards ESA PSS 05, and ISO 90003. SPMM focuses on the software development process in software production enterprises. The article explains the central concept of gaining data about software engineering organizations with a thoroughly constructed questionnaire. It gives a ground to measure the quality maturity level of organization and its projects. The SPMM can be interpreted as a method for describing where an organization stands and what changes are to be recommended in the next steps. The main idea of the SPMM is to determine the process maturity profile of an SPO. The goals of a SPMM self-assessment are: a) to measure and develop an SPO maturity quality profile showing strengths and weaknesses of the SPO assessed, b) to derive the steps for improvement from the shown quality profile. The result of one day assessment in software production organization X (SPO X), and Project X within the SPO X which was held at the beginning of October 2010 is presented. The result of the assessment showed the total organization and methodology maturity levels of the Project X. The organization is on maturity level 2,83. The methodology is on maturity level of 2,48. The total maturity level of the organization of SPO X is on maturity level of 2,42, and the methodology is on maturity level of 2,57. The organization of the paper is as follows: after the introduction in section one, section two explains the reasons of the SPMM development. Section three depicts the SPMM development. The maturity level algorithm is explicated in the next section. Section five explains the evaluation of the SPO, the assessment results are in section six. The conclusion is given in section seven, and the list of literature in section eight

A novel fontanelle probe for sensing oxygen saturation in the neonate

Monitoring of blood oxygen saturation (SpO 2 ) of the neonate is essential to the quality of health care provided on a neonatal intensive care unit (NICU). Current sensors are usually placed at the hand or foot, which are dependent of a peripheral blood supply. When the peripheral blood circulation of neonates is compromised conventional peripheral pulse oximeters, in many cases, fail to operate accurately or at all. A new reflectance anterior fontanelle (ANTF) SpO 2 sensor and instrumentation has been developed to investigate SpO 2 s from the neonatal fontanelle. The hypothesis is that perfusion at a central site should be preserved at times of compromised peripheral circulation. Fifteen neonates on an NICU (9 male, 6 female) with a median age of 7 d (IQR = 41.5 d) were selected for monitoring. ANTF photoplethysmographic (PPG) signals were monitored for a maximum period of 2 h. The developed system and custom made sensors were successful at acquiring good quality signals at both wavelengths necessary for pulse oximetry calculations. ANTF SpO 2 s, estimated from the acquired PPGs, were in broad agreement with SpO 2 s obtained from the commercial foot pulse oximeter. A Bland and Altman analysis of the differences between SpO 2 s from the fontanelle PPG sensor and the commercial device show a relatively small mean difference (d = ±2.2%), but with a wide variation (2s = ±17.4%) this observation may be due to the varied levels of ill health patients and is backed up by comparing the commercial device SpO 2 readings at the same moment a blood gas sample was taken (d = 4.8%, 2s = ±15.8%)