Patrick L. Combettes, Christian L. Müller.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 207--238.

Abstract:
We introduce a flexible optimization model for maximum likelihood-type estimation (M-estimation) that encompasses and generalizes a large class of existing statistical models, including Huber’s concomitant M-estimator, Owen’s Huber/Berhu concomitant estimator, the scaled lasso, support vector machine regression, and penalized estimation with structured sparsity. The model, termed perspective M-estimation, leverages the observation that convex M-estimators with concomitant scale as well as various regularizers are instances of perspective functions, a construction that extends a convex function to a jointly convex one in terms of an additional scale variable. These nonsmooth functions are shown to be amenable to proximal analysis, which leads to principled and provably convergent optimization algorithms via proximal splitting. We derive novel proximity operators for several perspective functions of interest via a geometrical approach based on duality. We then devise a new proximal splitting algorithm to solve the proposed M-estimation problem and establish the convergence of both the scale and regression iterates it produces to a solution. Numerical experiments on synthetic and real-world data illustrate the broad applicability of the proposed framework.

We study the connections between spectral clustering and the problems of maximum margin clustering, and estimation of the components of level sets of a density function. Specifically, we obtain bounds on the eigenvectors of graph Laplacian matrices in terms of the between cluster separation, and within cluster connectivity. These bounds ensure that the spectral clustering solution converges to the maximum margin clustering solution as the scaling parameter is reduced towards zero. The sensitivity of maximum margin clustering solutions to outlying points is well known, but can be mitigated by first removing such outliers, and applying maximum margin clustering to the remaining points. If outliers are identified using an estimate of the underlying probability density, then the remaining points may be seen as an estimate of a level set of this density function. We show that such an approach can be used to consistently estimate the components of the level sets of a density function under very mild assumptions.

Sufficient dimension reduction (SDR) is a very useful concept for exploratory analysis and data visualization in regression, especially when the number of covariates is large. Many SDR methods have been proposed for regression with a continuous response, where the central subspace (CS) is the target of estimation. Various conditions, such as the linearity condition and the constant covariance condition, are imposed so that these methods can estimate at least a portion of the CS. In this paper we study SDR for regression and discriminant analysis with categorical response. Motivated by the exploratory analysis and data visualization aspects of SDR, we propose a new geometric framework to reformulate the SDR problem in terms of manifold optimization and introduce a new concept called Maximum Separation Subspace (MASES). The MASES naturally preserves the “sufficiency” in SDR without imposing additional conditions on the predictor distribution, and directly inspires a semi-parametric estimator. Numerical studies show MASES exhibits superior performance as compared with competing SDR methods in specific settings.

Andreas Anastasiou, Robert E. Gaunt.

Source: Brazilian Journal of Probability and Statistics, Volume 34, Number 1, 136--149.

Abstract:
We use the delta method and Stein’s method to derive, under regularity conditions, explicit upper bounds for the distributional distance between the distribution of the maximum likelihood estimator (MLE) of a $d$-dimensional parameter and its asymptotic multivariate normal distribution. Our bounds apply in situations in which the MLE can be written as a function of a sum of i.i.d. $t$-dimensional random vectors. We apply our general bound to establish a bound for the multivariate normal approximation of the MLE of the normal distribution with unknown mean and variance.

Bastien Mallein.

Source: Brazilian Journal of Probability and Statistics, Volume 33, Number 2, 356--373.

Abstract:
Consider a supercritical branching random walk on the real line. The consistent maximal displacement is the smallest of the distances between the trajectories followed by individuals at the $n$th generation and the boundary of the process. Fang and Zeitouni, and Faraud, Hu and Shi proved that under some integrability conditions, the consistent maximal displacement grows almost surely at rate $lambda^{*}n^{1/3}$ for some explicit constant $lambda^{*}$. We obtain here a necessary and sufficient condition for this asymptotic behaviour to hold.

Area under ROC curve (AUC) is a widely used performance measure for classification models. We propose two new distributionally robust AUC maximization models (DR-AUC) that rely on the Kantorovich metric and approximate the AUC with the hinge loss function. We consider the two cases with respectively fixed and variable support for the worst-case distribution. We use duality theory to reformulate the DR-AUC models and derive tractable convex optimization problems. The numerical experiments show that the proposed DR-AUC models -- benchmarked with the standard deterministic AUC and the support vector machine models - perform better in general and in particular improve the worst-case out-of-sample performance over the majority of the considered datasets, thereby showing their robustness. The results are particularly encouraging since our numerical experiments are conducted with training sets of small size which have been known to be conducive to low out-of-sample performance.

Given a multivariate data set, sparse principal component analysis (SPCA) aims to extract several linear combinations of the variables that together explain the variance in the data as much as possible, while controlling the number of nonzero loadings in these combinations. In this paper we consider 8 different optimization formulations for computing a single sparse loading vector; these are obtained by combining the following factors: we employ two norms for measuring variance (L2, L1) and two sparsity-inducing norms (L0, L1), which are used in two different ways (constraint, penalty). Three of our formulations, notably the one with L0 constraint and L1 variance, have not been considered in the literature. We give a unifying reformulation which we propose to solve via a natural alternating maximization (AM) method. We show the the AM method is nontrivially equivalent to GPower (Journ'{e}e et al; JMLR 11:517--553, 2010) for all our formulations. Besides this, we provide 24 efficient parallel SPCA implementations: 3 codes (multi-core, GPU and cluster) for each of the 8 problems. Parallelism in the methods is aimed at i) speeding up computations (our GPU code can be 100 times faster than an efficient serial code written in C++), ii) obtaining solutions explaining more variance and iii) dealing with big data problems (our cluster code is able to solve a 357 GB problem in about a minute).

The $p$-tensor Curie-Weiss model is a two-parameter discrete exponential family for modeling dependent binary data, where the sufficient statistic has a linear term and a term with degree $p geq 2$. This is a special case of the tensor Ising model and the natural generalization of the matrix Curie-Weiss model, which provides a convenient mathematical abstraction for capturing, not just pairwise, but higher-order dependencies. In this paper we provide a complete description of the limiting properties of the maximum likelihood (ML) estimates of the natural parameters, given a single sample from the $p$-tensor Curie-Weiss model, for $p geq 3$, complementing the well-known results in the matrix ($p=2$) case (Comets and Gidas (1991)). Our results unearth various new phase transitions and surprising limit theorems, such as the existence of a 'critical' curve in the parameter space, where the limiting distribution of the ML estimates is a mixture with both continuous and discrete components. The number of mixture components is either two or three, depending on, among other things, the sign of one of the parameters and the parity of $p$. Another interesting revelation is the existence of certain 'special' points in the parameter space where the ML estimates exhibit a superefficiency phenomenon, converging to a non-Gaussian limiting distribution at rate $N^{frac{3}{4}}$. We discuss how these results can be used to construct confidence intervals for the model parameters and, as a byproduct of our analysis, obtain limit theorems for the sample mean, which provide key insights into the statistical properties of the model.

Data-driven modelling and computational predictions based on maximum entropy principle (MaxEnt-principle) aim at finding as-simple-as-possible - but not simpler then necessary - models that allow to avoid the data overfitting problem. We derive a multivariate non-parametric and non-stationary formulation of the MaxEnt-principle and show that its solution can be approximated through a numerical maximisation of the sparse constrained optimization problem with regularization. Application of the resulting algorithm to popular financial benchmarks reveals memoryless models allowing for simple and qualitative descriptions of the major stock market indexes data. We compare the obtained MaxEnt-models to the heteroschedastic models from the computational econometrics (GARCH, GARCH-GJR, MS-GARCH, GARCH-PML4) in terms of the model fit, complexity and prediction quality. We compare the resulting model log-likelihoods, the values of the Bayesian Information Criterion, posterior model probabilities, the quality of the data autocorrelation function fits as well as the Value-at-Risk prediction quality. We show that all of the considered seven major financial benchmark time series (DJI, SPX, FTSE, STOXX, SMI, HSI and N225) are better described by conditionally memoryless MaxEnt-models with nonstationary regime-switching than by the common econometric models with finite memory. This analysis also reveals a sparse network of statistically-significant temporal relations for the positive and negative latent variance changes among different markets. The code is provided for open access.

Emmanuel J. Candès, Pragya Sur.

Source: The Annals of Statistics, Volume 48, Number 1, 27--42.

Abstract:
This paper rigorously establishes that the existence of the maximum likelihood estimate (MLE) in high-dimensional logistic regression models with Gaussian covariates undergoes a sharp “phase transition.” We introduce an explicit boundary curve $h_{mathrm{MLE}}$, parameterized by two scalars measuring the overall magnitude of the unknown sequence of regression coefficients, with the following property: in the limit of large sample sizes $n$ and number of features $p$ proportioned in such a way that $p/n ightarrow kappa $, we show that if the problem is sufficiently high dimensional in the sense that $kappa >h_{mathrm{MLE}}$, then the MLE does not exist with probability one. Conversely, if $kappa <h_{mathrm{MLE}}$, the MLE asymptotically exists with probability one.

Gilles Bonnet, Nicolas Chenavier.

Source: Bernoulli, Volume 26, Number 2, 948--979.

Abstract:
We investigate the maximal degree in a Poisson–Delaunay graph in $mathbf{R}^{d}$, $dgeq 2$, over all nodes in the window $mathbf{W}_{ ho }:= ho^{1/d}[0,1]^{d}$ as $ ho $ goes to infinity. The exact order of this maximum is provided in any dimension. In the particular setting $d=2$, we show that this quantity is concentrated on two consecutive integers with high probability. A weaker version of this result is discussed when $dgeq 3$.

Łukasz Rajkowski.

Source: Bayesian Analysis, Volume 14, Number 2, 477--494.

Abstract:
Mixture models are a natural choice in many applications, but it can be difficult to place an a priori upper bound on the number of components. To circumvent this, investigators are turning increasingly to Dirichlet process mixture models (DPMMs). It is therefore important to develop an understanding of the strengths and weaknesses of this approach. This work considers the MAP (maximum a posteriori) clustering for the Gaussian DPMM (where the cluster means have Gaussian distribution and, for each cluster, the observations within the cluster have Gaussian distribution). Some desirable properties of the MAP partition are proved: ‘almost disjointness’ of the convex hulls of clusters (they may have at most one point in common) and (with natural assumptions) the comparability of sizes of those clusters that intersect any fixed ball with the number of observations (as the latter goes to infinity). Consequently, the number of such clusters remains bounded. Furthermore, if the data arises from independent identically distributed sampling from a given distribution with bounded support then the asymptotic MAP partition of the observation space maximises a function which has a straightforward expression, which depends only on the within-group covariance parameter. As the operator norm of this covariance parameter decreases, the number of clusters in the MAP partition becomes arbitrarily large, which may lead to the overestimation of the number of mixture components.

Ruosi Guo, Chunming Zhang, Zhengjun Zhang.

Source: Statistical Science, Volume 35, Number 1, 145--157.

Abstract:
In many scientific disciplines, finding hidden influential factors behind observational data is essential but challenging. The majority of existing approaches, such as the independent component analysis (${mathrm{ICA}}$), rely on linear transformation, that is, true signals are linear combinations of hidden components. Motivated from analyzing nonlinear temporal signals in neuroscience, genetics, and finance, this paper proposes the “maximum independent component analysis” (${mathrm{MaxICA}}$), based on max-linear combinations of components. In contrast to existing methods, ${mathrm{MaxICA}}$ benefits from focusing on significant major components while filtering out ignorable components. A major tool for parameter learning of ${mathrm{MaxICA}}$ is an augmented genetic algorithm, consisting of three schemes for the elite weighted sum selection, randomly combined crossover, and dynamic mutation. Extensive empirical evaluations demonstrate the effectiveness of ${mathrm{MaxICA}}$ in either extracting max-linearly combined essential sources in many applications or supplying a better approximation for nonlinearly combined source signals, such as $mathrm{EEG}$ recordings analyzed in this paper.

Georg Lindgren.

Source: Statistical Science, Volume 34, Number 1, 100--128.

Abstract:
We describe and compare how methods based on the classical Rice’s formula for the expected number, and higher moments, of level crossings by a Gaussian process stand up to contemporary numerical methods to accurately deal with crossing related characteristics of the sample paths. We illustrate the relative merits in accuracy and computing time of the Rice moment methods and the exact numerical method, developed since the late 1990s, on three groups of distribution problems, the maximum over a finite interval and the waiting time to first crossing, the length of excursions over a level, and the joint period/amplitude of oscillations. We also treat the notoriously difficult problem of dependence between successive zero crossing distances. The exact solution has been known since at least 2000, but it has remained largely unnoticed outside the ocean science community. Extensive simulation studies illustrate the accuracy of the numerical methods. As a historical introduction an attempt is made to illustrate the relation between Rice’s original formulation and arguments and the exact numerical methods.

Microglial cells are considered as sensors of brain pathology by detecting any sign of brain lesions, infections, or dysfunction and can influence the onset and progression of neurological diseases. They are capable of sensing their neuronal environment via many different signaling molecules, such as neurotransmitters, neurohormones and neuropeptides. The neuropeptide VGF has been associated with many metabolic and neurological disorders. TLQP21 is a VGF-derived peptide and has been shown to signal via C3aR1 and C1qBP receptors. The effect of TLQP21 on microglial functions in health or disease is not known. Studying microglial cells in acute brain slices, we found that TLQP21 impaired metabotropic purinergic signaling. Specifically, it attenuated the ATP-induced activation of a K⁺ conductance, the UDP-stimulated phagocytic activity, and the ATP-dependent laser lesion-induced process outgrowth. These impairments were reversed by blocking C1qBP, but not C3aR1 receptors. While microglia in brain slices from male mice lack C3aR1 receptors, both receptors are expressed in primary cultured microglia. In addition to the negative impact on purinergic signaling, we found stimulating effects of TLQP21 in cultured microglia, which were mediated by C3aR1 receptors: it directly evoked membrane currents, stimulated basal phagocytic activity, evoked intracellular Ca²⁺ transient elevations, and served as a chemotactic signal. We conclude that TLQP21 has differential effects on microglia depending on C3aR1 activation or C1qBP-dependent attenuation of purinergic signaling. Thus, TLQP21 can modulate the functional phenotype of microglia, which may have an impact on their function in health and disease.

SIGNIFICANCE STATEMENT The neuropeptide VGF and its peptides have been associated with many metabolic and neurological disorders. TLQP21 is a VGF-derived peptide that activates C1qBP receptors, which are expressed by microglia. We show here, for the first time, that TLQP21 impairs P2Y-mediated purinergic signaling and related functions. These include modulation of phagocytic activity and responses to injury. As purinergic signaling is central for microglial actions in the brain, this TLQP21-mediated mechanism might regulate microglial activity in health and disease. We furthermore show that, in addition to C1qBP, functional C3aR1 responses contribute to TLQP21 action on microglia. However, C3aR1 responses were only present in primary cultures but not in situ, suggesting that the expression of these receptors might vary between different microglial activation states.

We find out how UEFA is ensuring a lasting legacy for its major club finals.

Upper respiratory tract infections (URIs) are very common in children. Currently, there are no effective preventive measures for URI. There are no studies on the effect of montelukast for prevention of URI.

In a randomized, double-blind, placebo-controlled study of preschool-aged children, 12-week prophylactic treatment with montelukast did not reduce the incidence of URI. (Read the full article)

Hypothalamic-pituitary-adrenal axis suppression caused by inhaled corticosteroids is considered rare. Adrenal crisis has been described in children treated with high doses of inhaled fluticasone propionate. It was recommended that doses licensed for children should not be exceeded.

Biochemically confirmed hypothalamic-pituitary-adrenal axis dysfunction may occur in two-thirds of children treated with corticosteroids. Suppression may occur at low doses and especially with concomitant nasal steroids. Children with poor adherence or obesity may be less prone to adrenal crisis. (Read the full article)

Delayed anaphylaxis, urticaria, and angioedema to mammalian meat products were first described in the adult population in 2009. Patients with this syndrome who consume mammalian meat typically develop symptoms 4 to 6 hours after ingestion.

Specific diagnoses for children who develop urticaria, angioedema, and idiopathic anaphylaxis are few and far between. We have now shown delayed anaphylaxis, urticaria, and angioedema due to mammalian meat products in the pediatric population. (Read the full article)

Stress affects health of children, potentially persisting as a trajectory into adulthood. Earlier biological markers assess only momentary stress, making it difficult to investigate stress over longer periods of time. Cortisol in hair is a new biomarker of prolonged stress.

Mother and child hair cortisol association suggests a heritable part or maternal calibration. Cortisol output gradually stabilizes, has a stable trait, and is positively correlated to birth weight. Hair cortisol is a promising noninvasive biomarker of prolonged stress, especially applicable for children. (Read the full article)

Palivizumab prophylaxis prevents respiratory syncytial virus lower respiratory tract infection. An association between respiratory syncytial virus infection and subsequent recurrent wheezing has been suggested by many studies. Only a few studies conducted from Europe and North America have addressed this causal association.

In a prospective, multicenter, case-control study of 440 children with high follow-up rate of 98.4%, palivizumab prophylaxis administered to preterm Japanese infants (33–35 weeks’ gestational age) in their first respiratory season reduced the incidence of subsequent recurrent wheezing up to 3 years. (Read the full article)

Down syndrome is an independent risk factor for severe respiratory syncytial virus infection and subsequent hospitalization.

This observational study suggests that immunoprophylaxis may reduce respiratory syncytial virus-related hospitalization by 3.6-fold (95% confidence interval, 1.5–8.7) in children with Down syndrome overall. (Read the full article)

As a student in Penn State's College of Information Sciences and Technology, Steve Ney learned critical skills, from coding to data design and architecture. Today, he applies that foundation in his "dream job" as a healthcare data analyst for Geisinger Health, where he uses those skills to help produce visual outputs for doctors and staff to utilize in caring for patients.

Blade Urban Air Mobility Program in India: The air-taxi has begun operations in Mumbai, Pune, and Shirdi, today

A wildfire crew led by the Delaware Forest Service is near completion of a two-week assignment on the Fork Complex Fire, a 28,736-acre blaze near Hayfork, California in the Shasta-Trinity National Forest. Almost 2,400 personnel are battling the fire that is currently 26 percent contained. The Fork Complex is one of several large wildfires in Northern California that together cover more than 223,000 acres, one of the major factors that prompted the National Interagency Fire Center (NIFC) to increase its National Preparedness Level today to the maximum of 5 on a 5-point scale.

While Maharashtra appears to be adequately equipped to handle the crisis, the report makes it clear the problem is that while the capacity is evenly spread across the state, the infection is mostly centred in Mumbai.

  First time users of Intel® HAXM can occasionally run into situations where they are not sure if their Android* emulator is in fact using HAXM technology. This article will provide the necessary st...

The private sector lender had reported a net profit of Rs? 1,505.06 crore in the same quarter of the previous financial year.

The bank’s advances grew 15% y-o-y to Rs 5,71,424 crore as on March 31, with retail loans up 24% y-o-y to Rs 3.05 lakh crore, accounting for 53% of the net advances.

The marginal cost lending rate cut by banks and finance companies is good news for home loan and car loan borrowers whose loans are linked to MCLR. With the rate cut, all loans including home loans, auto loans, personal loans, etc., tied to the MCLR will become cheaper.

Phishing is the most common method for scamsters to illegally siphon money from people. In simple terms, phishing is a method of scamming people by sending them emails pretending to be from reputable companies in order to get people to reveal their confidential information, such as passwords and credit card numbers. A report has revealed […]

The post Maximum Frauds Done Using Apple, Netflix Branding: This Is How They Fool You first appeared on Trak.in . Trak.in Mobile Apps: Android | iOS.

[SAPS] A 35-year-old taxi driver is facing attempted murder charges (read with DMA Regulation 14(3) and in a quarantine site in Cape Town after he was stopped in a vehicle checkpoint (VCP) on the R61 in Beaufort West yesterday ferrying about seven passengers. The driver, who had apparently tested positive for the virus after taking a test on 30 April 2020 on the N2 Tsitsikamma roadblock in the Eastern Cape, was duly informed two days ago by the testing authority of the outcome of the test. Yet, he allegedly proce

[Daily Maverick] The Eastern Cape Department of Health has confirmed that 80 of a group of 188 seasonal farmworkers who returned to the province from the Western Cape over the past two weeks have tested positive for coronavirus. The taxis were 'intercepted' on the province's back roads near Elliotdale. Some drivers were allegedly in possession of fake permits. The positive test results come as nearly 10,000 people returned home during the window period allowed for interprovincial travel.

I have a problem connected with my AXI4 coverage.

I enable coverage collection in AXI4 

      set_config_int("axi4_active_slave_agent_0.monitor.coverModel", "burst_started_enable", 1);
      set_config_int("axi4_active_slave_agent_0.monitor.coverModel", "coverageEnable", 1);

but i don't have a result.

I think the problem in Callback, but i try to connect all callback and i don't have positive result.

Can you help me?

Marcus Weldon, chief technology officer of Nokia and president of its research arm Nokia Bell Labs, talks about what guided the decision to set up a new global R&D centre and the company’s strategy for driving innovation.

As part of its acquisition of Maximum Solar, Ameresco said, it will further develop in-house services to operate and maintain solar facilities. Maximum Solar currently manages about 150 MW of solar throughout the northeastern U.S.

Presentation by Chrys Shea of Christopher Associates.

This week global engineering company Emerson announced that it had formed a 3-year alliance with Vayu to combine Emerson’s Ovation automation platform with Vayu’s cloud-computing wind energy optimization technology. The new technology will optimize wind farms in the Americas, Caribbean and Europe.

The Government has today announced, just as predicted, a fall in RPI-linked compensation limits. The maximum compensatory award for unfair dismissal will decrease from £66,200 to £65,300 for effective dates ...

The UK has suffered widespread damage as a result of recent flooding over the winter of 2019/20, with anticipated losses in excess of £400m. If flood-related interruption to a business is significant, property and business interruption (“BI”) polici...

Introduction On 31 January 2020, the OECD issued a further update on its work on the taxation of the digital economy. The catchily titled “Statement by the OECD/G20 Inclusive Framework on BEPS on the Two-Pillar Approach to Address the Tax Chal...

Prague Daily Monitor

According to a story run in Deník N, a blind woman going out for a morning walk ran into a nightmare scenario on Monday in Prague's trendy Žižkov area.

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Singapore’s carbon tax is designed to maximize green investments while minimizing negative effects on the overall economy.

A sophisticated computer simulation of the universe, approximately 1 billion light years across, is modelling tens of thousands of galaxies

Food tastes satisfying thanks to the amino acid glutamate, which stimulates the umami taste. Sam Wong explains how to boost it in your recipes