Optimal Neighborhood Selection for AR-ARCH Random Fields with Application to Mortality

This article proposes an optimal and robust methodology for model selection. The model of interest is a parsimonious alternative framework for modeling the stochastic dynamics of mortality improvement rates introduced recently in the literature. The approach models mortality improvements using a random field specification with a given causal structure instead of the commonly used factor-based decomposition framework. It captures some well-documented stylized facts of mortality behavior including: dependencies among adjacent cohorts, the cohort effects, cross-generation correlations, and the conditional heteroskedasticity of mortality. Such a class of models is a generalization of the now widely used AR-ARCH models for univariate processes. A the framework is general, it was investigated and illustrated a simple variant called the three-level memory model. However, it is not clear which is the best parameterization to use for specific mortality uses. In this paper, we investigate the optimal model choice and parameter selection among potential and candidate models. More formally, we propose a methodology well-suited to such a random field able to select thebest model in the sense that the model is not only correct but also most economical among all thecorrectmodels. Formally, we show that a criterion based on a penalization of the log-likelihood, e.g., the using of the Bayesian Information Criterion, is consistent. Finally, we investigate the methodology based on Monte-Carlo experiments as well as real-world datasets.

Allocation Mechanisms without Reduction

We study a simple variant of the house allocation problem (one-sided matching). We demonstrate that agents with recursive preferences may systematically prefer one allocation mechanism to the other, even among mechanisms that are considered to be the same in standard models, in the sense that they induce the same probability distribution over successful matchings. Using this, we propose a new priority groups mechanism and provide conditions under which it is preferred to two popular mechanisms, random top cycle and random serial dictatorship. (JEL C78, D44, D82)

Kernel-based Methods for Bandit Convex Optimization

We consider the adversarial convex bandit problem and we build the first poly( T )-time algorithm with poly( n ) √ T -regret for this problem. To do so, we introduce three new ideas in the derivative-free optimization literature: (i) kernel methods, (ii) a generalization of Bernoulli convolutions, and (iii) a new annealing schedule for exponential weights (with increasing learning rate). The basic version of our algorithm achieves Õ( n 9.5 √ T )-regret, and we show that a simple variant of this algorithm can be run in poly( n log ( T ))-time per step (for polytopes with polynomially many constraints) at the cost of an additional poly( n ) T o(1) factor in the regret. These results improve upon the Õ( n 11 √ T -regret and exp (poly( T ))-time result of the first two authors and the log ( T ) poly( n ) √ T -regret and log( T ) poly( n ) -time result of Hazan and Li. Furthermore, we conjecture that another variant of the algorithm could achieve Õ( n 1.5 √ T )-regret, and moreover that this regret is unimprovable (the current best lower bound being Ω ( n √ T ) and it is achieved with linear functions). For the simpler situation of zeroth order stochastic convex optimization this corresponds to the conjecture that the optimal query complexity is of order n 3 / ɛ 2 .

Device-independent quantum key distribution with random key basis

Device-independent quantum key distribution (DIQKD) is the art of using untrusted devices to distribute secret keys in an insecure network. It thus represents the ultimate form of cryptography, offering not only information-theoretic security against channel attacks, but also against attacks exploiting implementation loopholes. In recent years, much progress has been made towards realising the first DIQKD experiments, but current proposals are just out of reach of today’s loophole-free Bell experiments. Here, we significantly narrow the gap between the theory and practice of DIQKD with a simple variant of the original protocol based on the celebrated Clauser-Horne-Shimony-Holt (CHSH) Bell inequality. By using two randomly chosen key generating bases instead of one, we show that our protocol significantly improves over the original DIQKD protocol, enabling positive keys in the high noise regime for the first time. We also compute the finite-key security of the protocol for general attacks, showing that approximately 108–1010 measurement rounds are needed to achieve positive rates using state-of-the-art experimental parameters. Our proposed DIQKD protocol thus represents a highly promising path towards the first realisation of DIQKD in practice.

The European Arrest Warrant in Designer Drugs Cases. With or Without Verification of Double Criminality?

The cross-border character of the designer drugs crimes forced the UE countries to cooperate in criminal prosecution. At first sight, in European Union law, there are proper instruments to enforce such cooperation. The Framework Decision on the European Arrest Warrant introduces the model of cross-border prosecution and abandons the requirement of double criminality in case of the group of the 32 crimes, listed in the Article 2 (2) of the FD EAW. The question is whether such a simple variant of EAW (without checking double criminality) may be enforced in designer drug cases. The work presents an argumentation that the normative meaning of Article 2 (2) of the FD EAW has to be established under European and international law. As long as a particular new drug is not internationally recognized as ‘psychotropic substance’ or ‘narcotic drug’, its trafficking cannot be treated as one of the 32 crimes, mentioned above.

Acute Myelogenous Leukemia with the t(7;7)(p15;p22) Translocation, a Novel Simple Variant of t(7;11)(p15;p15) Translocation: First Description

The t(7;11)(p15;p15) translocation is a recurrent genetic abnormality associated with acute myelogenous leukemia (AML). The translocation results in a fusion between the nucleoporin 98 and homeobox genes. We describe a case of AML with t(7; 7)(p15;p22) translocation, which is a novel simple variant of the t(7;11)(p15;p15) translocation. A 66-year-old woman presented with subcutaneous hemorrhage in both forearms. Laboratory test revealed hyperleukocytosis (white blood cell count: 97,800 cells/µL (blasts, 51.0%)), anemia (hemoglobin level: 7.6 g/dL), thrombocytopenia (platelet count: 6.5 × 104/μL), and hyperfibrinolysis (elevated d-dimer level: 12.4 µg/mL; fibrin/fibrinogen degradation products: 26.9 µg/mL). The patient was diagnosed with AML; the blast morphology was unclassifiable according to the French-American-British classification. Flow cytometry CD45 gating revealed that the blasts expressed CD34, CD13, CD33, and CD117. G-banding of tumor cells revealed the t(7;7)(p15;p22) translocation [20/20]. The patient underwent chemotherapy. At 48 days of admission, the patient died of multiple organ failure. The t(7;7)(p15;p22) translocation involved chromosome 7p15, indicating its association with the homeobox genes. To the best of our knowledge, this is the first report of a patient with AML with the t(7;7)(p15;p22) translocation, which is a simple novel variant of the t(7;11)(p15;p15) translocation.

Czy PIT komunalny może ograniczyć rozlewanie się miast?

The purpose of this article is twofold. First, to re-energize discussion on local personal tax, and second, to show how such a tax could curb urban sprawl. The authors start with a short description of the communal tax and its potential links to urban sprawl. In the current system of communities’ financing in Poland, suburban municipalities have a significant incentive to increase the number of inhabitants as the PIT revenues follow their inflow. The authors propose and discuss a simple variant of local PIT called Self-government Tax Rate which is a flat tax on a broadly defined tax base. Contrary to the present system of Polish local government units’ share in progressive PIT, this system is linear, which reduces the gains in PIT revenues from taxpayers in the second tax bracket moving to suburbia. This is the first paper in the relevant literature that investigates the links between communal tax and urban sprawl.

Pengenalan Pola Sinyal Electromyography (EMG) pada Gerakan Jari Tangan Kanan

ABSTRAKSinyal EMG merupakan salah satu sinyal yang dapat digunakan untuk memberikan perintah pada kursi roda listrik. Sinyal EMG yang digunakan diambil dari sinyal otot fleksor dan ekstensor yang berada di tangan kanan. Sinyal tersebut diambil menggunakan sensor Myo Armband. Klasifikasi sinyal EMG diambil dari pergerakan jari yang mewakili perintah gerak yaitu jari kelingking untuk bergerak maju, jari manis untuk berhenti, jari tengah untuk belok kanan dan jari telunjuk untuk belok kiri. Setiap sinyal EMG diekstraksi fitur untuk menentukan karakteristik sinyal sehingga fitur yang diperoleh adalah Average Absolute Value, Root Mean Square, Simple Integral Square, EMG Simple Variant and Integrated EMG. Kemudian fitur tersebut digunakan sebagai input dari metode klasifikasi Artificial Neural Network Backpropagation. Jumlah data latih yang digunakan adalah 800 data sedangkan data uji yang digunakan adalah 200 data. Tingkat keberhasilan proses klasifikasi ini sebesar 93%.Kata kunci: electromyogram, artificial neural network, klasifikasi sinyal, tangan kanan, Myo Armband. ABSTRACTEMG signal is one of the signals that can be used to give orders to electric wheelchairs. The EMG signal used is taken from the flexor and extensor muscle signals in the right hand. The signal is taken using the Myo Armband sensor. The EMG signal classification is taken from the movement of the finger which represents the command of motion ie the little finger to move forward, ring finger to stop, middle finger to turn right and index finger to turn left. Each EMG signal is extracted features to determine the signal characteristics so that the features obtained are Average Absolute Value, Root Mean Square, Simple Integral Square, EMG Simple Variant and Integrated EMG. Then the feature is used as input from the Backpropagation classification method. The amount of training data used is 800 data while the test data used is 200 data. The success rate of this classification process is 93%.Keywords: electromyogram, artificial neural network, signal classification, right hand, Myo Armband.

Stabilizing Adversarial Invariance Induction from Divergence Minimization Perspective

Adversarial invariance induction (AII) is a generic and powerful framework for enforcing an invariance to nuisance attributes into neural network representations. However, its optimization is often unstable and little is known about its practical behavior. This paper presents an analysis of the reasons for the optimization difficulties and provides a better optimization procedure by rethinking AII from a divergence minimization perspective. Interestingly, this perspective indicates a cause of the optimization difficulties: it does not ensure proper divergence minimization, which is a requirement of the invariant representations. We then propose a simple variant of AII, called invariance induction by discriminator matching, which takes into account the divergence minimization interpretation of the invariant representations. Our method consistently achieves near-optimal invariance in toy datasets with various configurations in which the original AII is catastrophically unstable. Extentive experiments on four real-world datasets also support the superior performance of the proposed method, leading to improved user anonymization and domain generalization.