Fast Label Embeddings via Randomized Linear Algebra

Many modern multiclass and multilabel problems are characterized by increasingly large output spaces. For these problems, label embeddings have been shown to be a useful primitive that can improve computational and statistical efficiency. In this work we utilize a correspondence between rank constrained estimation and low dimensional label embeddings that uncovers a fast label embedding algorithm which works in both the multiclass and multilabel settings. The result is a randomized algorithm whose running time is exponentially faster than naive algorithms. We demonstrate our techniques on two large-scale public datasets, from the Large Scale Hierarchical Text Challenge and the Open Directory Project, where we obtain state of the art results.Comment: To appear in the proceedings of the ECML/PKDD 2015 conference. Reference implementation available at https://github.com/pmineiro/randembe

Non-Redundant Spectral Dimensionality Reduction

Spectral dimensionality reduction algorithms are widely used in numerous domains, including for recognition, segmentation, tracking and visualization. However, despite their popularity, these algorithms suffer from a major limitation known as the "repeated Eigen-directions" phenomenon. That is, many of the embedding coordinates they produce typically capture the same direction along the data manifold. This leads to redundant and inefficient representations that do not reveal the true intrinsic dimensionality of the data. In this paper, we propose a general method for avoiding redundancy in spectral algorithms. Our approach relies on replacing the orthogonality constraints underlying those methods by unpredictability constraints. Specifically, we require that each embedding coordinate be unpredictable (in the statistical sense) from all previous ones. We prove that these constraints necessarily prevent redundancy, and provide a simple technique to incorporate them into existing methods. As we illustrate on challenging high-dimensional scenarios, our approach produces significantly more informative and compact representations, which improve visualization and classification tasks

Regularized Linear Inversion with Randomized Singular Value Decomposition

In this work, we develop efficient solvers for linear inverse problems based on randomized singular value decomposition (RSVD). This is achieved by combining RSVD with classical regularization methods, e.g., truncated singular value decomposition, Tikhonov regularization, and general Tikhonov regularization with a smoothness penalty. One distinct feature of the proposed approach is that it explicitly preserves the structure of the regularized solution in the sense that it always lies in the range of a certain adjoint operator. We provide error estimates between the approximation and the exact solution under canonical source condition, and interpret the approach in the lens of convex duality. Extensive numerical experiments are provided to illustrate the efficiency and accuracy of the approach.Comment: 20 pages, 4 figure

Marketing research of the state of gender policy in the system of public administration of region

Представлено частину досліджень, проведених у ході проєкту «Громадська оцінка стану виконання державних документів з ґендерної рівності» спільно з Київським інститутом гендерних досліджень за фінансового підтримання. Міністерства закордонних справ Данії. Аналіз наукових праць виявив брак досліджень щодо впровадження державних документів з гендерної рівності органами місцевої влади. Метою статті було виявлення стану виконання завдань Державної соціальної програми забезпечення рівних прав та можливостей жінок і чоловіків на період до 2021 року в Тернопільській області. Використано такі методи: аналіз вторинної інформації; анкетування; спостереження; особисті інтерв’ю; метод компаративного аналізу; графічний метод; синтез; узагальнення; групування. Надіслані інформаційні запити відповідно до Закону України «Про доступ до публічної інформації» до органів виконавчої влади. Основні результати дослідження. Виявлено наступне: 1. На рівні області виконано 69% усіх передбачених Держпрограмою завдань. 2. Окремої обласної програми на виконання Держпрограми в Тернопільській області немає, заходи інтегровані в інші обласні програми з неґендерної тематики. 3. Обсяги фінансування на виконання завдань Держпрограми з обласного бюджету склали 92,5 тис грн; 4. Виконано 44% усіх заходів Держпрограми. 5. Багато заходів спрямувались на навчання галузевих спеціалістів; розвиток лідерських навичок жінок; інформаційно-просвітницьку діяльність; сприяння самозайнятості жінок. 6. Найбільшу кількість невиконаних завдань склали ті, що потребували аналітичної, організаційної, інформаційно-просвітницької роботи. 7. Обсяги фінансування на виконання завдань Державної соціальної програми склали 278,5 тис грн. Висновки й перспективи подальших розвідок. Встановлено потребу інтенсифікувати імплементацію державних документів із гендерної рівності на рівні регіону. Подальші дослідження будуть присвячені аналізу стану виконання Національного плану дій з виконання рекомендацій Комітету ООН з ліквідації дискримінації щодо жінок.Part of the research conducted during the project «Public assessment of the state of implementation of state documents on gender equality» in conjunction with the Kyiv Institute for Gender Studies with the financial support of the Ministry of Foreign Affairs of Denmark is presented. The analysis of scientific works confirmed the relevance of the study of the determinants of gender policy in the context of covid-19 and revealed a lack of research on the implementation of state documents on gender equality by local authorities. The purpose of the article was to identify the state of implementation of the State Social Program to ensure equal rights and opportunities for women and men for the period up to 2021 in Ternopil region. The following methods were used: analysis of secondary information; questionnaires; observation; personal interviews; method of comparative analysis; graphic method; synthesis; generalization; grouping. Information requests were sent to the executive authorities in accordance with the Law of Ukraine «On Access to Public Information». The conducted research allows doing the followings conclusions: 1. 69% of all tasks envisaged by the State Program have been completed. 2. There is no separate regional program for the implementation of the State Program in Ternopil region; the measures are integrated into other regional non-gender programs. 3. Volumes of financing for performance of tasks of the State program from the regional budget made 92,5 thousand UAH. 4. 44% of all measures of the State Program have been implemented. 5. Many activities were aimed at training industry professionals; development of women's leadership skills; information and educational activities; promoting women's self-employment. 6. The largest number of uncompleted tasks required analytical, organizational, informational and educational work. 7. The amount of funding for the tasks of the State Social Program amounted to 278.5 thousand UAH. The need to intensify the implementation of state documents on gender equality at the regional level has been identified. Further research will focus on the analysis of the state of implementation by local authorities of the National Action Plan to implement the recommendations set out in the concluding observations of the UN Committee on the Elimination of Discrimination against Wome

Emirati women do not shy away from competition: evidence from a patriarchal society in transition

We explore gender attitudes towards competition in the United Arab Emirates—a traditionally patriarchal society which in recent times has adopted numerous policies to empower women and promote their role in the labor force. The experimental treatments vary whether individuals compete in single-sex or mixed-sex groups. In contrast to previous studies, women in our sample are not less willing to compete than men. In fact, once we control for individual performance, Emirati women are more likely to select into competition. Our analysis shows that neither women nor men shy away from competition, and both compete more than what would be optimal in monetary terms as the fraction of men in their group increases. We offer a detailed survey of the literature and discuss possible reasons for the lack of gender differences in our experiment

Approximation of integral operators using product-convolution expansions

International audienceWe consider a class of linear integral operators with impulse responses varying regularly in time or space. These operators appear in a large number of applications ranging from signal/image processing to biology. Evaluating their action on functions is a computationally intensive problem necessary for many practical problems. We analyze a technique called product-convolution expansion: the operator is locally approximated by a convolution, allowing to design fast numerical algorithms based on the fast Fourier transform. We design various types of expansions, provide their explicit rates of approximation and their complexity depending on the time varying impulse response smoothness. This analysis suggests novel wavelet based implementations of the method with numerous assets such as optimal approximation rates, low complexity and storage requirements as well as adaptivity to the kernels regularity. The proposed methods are an alternative to more standard procedures such as panel clustering, cross approximations, wavelet expansions or hierarchical matrices

Top-Down Feedback in an HMAX-Like Cortical Model of Object Perception Based on Hierarchical Bayesian Networks and Belief Propagation

PubMed ID: 2313976

A cohort of 17 patients with kyphoscoliotic Ehlers-Danlos syndrome caused by biallelic mutations in FKBP14: expansion of the clinical and mutational spectrum and description of the natural history.

PurposeIn 2012 we reported in six individuals a clinical condition almost indistinguishable from PLOD1-kyphoscoliotic Ehlers-Danlos syndrome (PLOD1-kEDS), caused by biallelic mutations in FKBP14, and characterized by progressive kyphoscoliosis, myopathy, and hearing loss in addition to connective tissue abnormalities such as joint hypermobility and hyperelastic skin. FKBP14 is an ER-resident protein belonging to the family of FK506-binding peptidyl-prolyl cis-trans isomerases (PPIases); it catalyzes the folding of type III collagen and interacts with type III, type VI, and type X collagens. Only nine affected individuals have been reported to date.MethodsWe report on a cohort of 17 individuals with FKBP14-kEDS and the follow-up of three previously reported patients, and provide an extensive overview of the disorder and its natural history based on clinical, biochemical, and molecular genetics data.ResultsBased on the frequency of the clinical features of 23 patients from the present and previous cohorts, we define major and minor features of FKBP14-kEDS. We show that myopathy is confirmed by histology and muscle imaging only in some patients, and that hearing impairment is predominantly sensorineural and may not be present in all individuals.ConclusionOur data further support the extensive clinical overlap with PLOD1-kEDS and show that vascular complications are rare manifestations of FKBP14-kEDS

Geometric methods on low-rank matrix and tensor manifolds

In this chapter we present numerical methods for low-rank matrix and tensor problems that explicitly make use of the geometry of rank constrained matrix and tensor spaces. We focus on two types of problems: The first are optimization problems, like matrix and tensor completion, solving linear systems and eigenvalue problems. Such problems can be solved by numerical optimization for manifolds, called Riemannian optimization methods. We will explain the basic elements of differential geometry in order to apply such methods efficiently to rank constrained matrix and tensor spaces. The second type of problem is ordinary differential equations, defined on matrix and tensor spaces. We show how their solution can be approximated by the dynamical low-rank principle, and discuss several numerical integrators that rely in an essential way on geometric properties that are characteristic to sets of low rank matrices and tensors

Friend versus foe: Neural correlates of prosocial decisions for liked and disliked peers

Although the majority of our social interactions are with people we know, few studies have investigated the neural correlates of sharing valuable resources with familiar others. Using an ecologically valid research paradigm, this functional magnetic resonance imaging study examined the neural correlates of prosocial and selfish behavior in interactions with real-life friends and disliked peers in young adults. Participants (N = 27) distributed coins between themselves and another person, where they could make selfish choices that maximized their own gains or prosocial choices that maximized outcomes of the other. Participants were more prosocial toward friends and more selfish toward disliked peers. Individual prosociality levels toward friends were associated negatively with supplementary motor area and anterior insula activity. Further preliminary analyses showed that prosocial decisions involving friends were associated with heightened activity in the bilateral posterior temporoparietal junction, and selfish decisions involving disliked peers were associated with heightened superior temporal sulcus activity, which are brain regions consistently shown to be involved in mentalizing and perspective taking in prior studies. Further, activation of the putamen was observed during prosocial choices involving friends and selfish choices involving disliked peers. These findings provide insights into the modulation of neural processes that underlie prosocial behavior as a function of a positive or negative relationship with the interaction partner