Arming some school staff provides a needed safety option for rural districts far from law enforcement, educators told the Federal School Safety Commission during an Arkansas site visit Wednesday.

Worried that far too many students have weak reading skills, states are passing new laws that require aspiring teachers—and, increasingly, teachers who are already in the classroom—to master reading instruction that’s solidly grounded in research.

A statewide initiative aims to enroll half the state's high school students into career pathways to close a "skills gap."

Geoff Schwartz joins the latest Talkin' Ducks Podcast with host Jordan Kent

Cricket -- Australia -- Anecdotes.

Death -- Philosophy.

Dodd, Reg, 1940-

Commonwealth Railways (Australia) -- History.

Food.

Pollock, David.

Environmentalism.

Self-help techniques.

The District of Columbia's charters aren't always "backfilling" seats, and there's little financial incentive for them to do so.

Edinburgh : MacLachlan and Stewart, 1870.

Worried that far too many students have weak reading skills, states are passing new laws that require aspiring teachers—and, increasingly, teachers who are already in the classroom—to master reading instruction that’s solidly grounded in research.

London : printed by W. Wilson, for E. Brewster, and George Sawbridge, at the Bible on Ludgate-Hill, neere Fleet-bridge, 1653.

[Paris], [1807]

(Printed in Austria)

Five of the top NHL prospects took part in a video call with Gretzky and were given advice as they prepare to take the next step in their careers.

Ducks defensemen Christian Djoos and Jani Hakanpaa will stay with the team through the 2020-21 season after each signed a one-year, one-way contract extension.

The Flyers have had quite a bit of luck when drafting players from the Brandon Wheat Kings. Could they keep their streak alive with Braden Schneider in the first round of the 2020 NHL draft? By Brooke Destra

Berkeley, California : Tabor Sarah Books, 1988.

[London] : [publisher not identified], [2019]

[London] : [publisher not identified], [2019]

The women's basketball committee will start using the NCAA Evaluation Tool instead of RPI to help evaluate teams for the tournament starting with the upcoming season. “It’s an exciting time for the game as we look to the future,” said Nina King, senior deputy athletics director and chief of staff at Duke, who chair the Division I Women’s Basketball Committee next season. “We felt after much analysis that the women’s basketball NET, which will be determined by who you played, where you played, how efficiently you played and the result of the game, is a more accurate tool and should be used by the committee going forward.”

Ming Yu, Varun Gupta, Mladen Kolar.

Source: Electronic Journal of Statistics, Volume 14, Number 1, 413--457.

Abstract:
We study the problem of recovery of matrices that are simultaneously low rank and row and/or column sparse. Such matrices appear in recent applications in cognitive neuroscience, imaging, computer vision, macroeconomics, and genetics. We propose a GDT (Gradient Descent with hard Thresholding) algorithm to efficiently recover matrices with such structure, by minimizing a bi-convex function over a nonconvex set of constraints. We show linear convergence of the iterates obtained by GDT to a region within statistical error of an optimal solution. As an application of our method, we consider multi-task learning problems and show that the statistical error rate obtained by GDT is near optimal compared to minimax rate. Experiments demonstrate competitive performance and much faster running speed compared to existing methods, on both simulations and real data sets.

A common divide-and-conquer approach for Bayesian computation with big data is to partition the data, perform local inference for each piece separately, and combine the results to obtain a global posterior approximation. While being conceptually and computationally appealing, this method involves the problematic need to also split the prior for the local inferences; these weakened priors may not provide enough regularization for each separate computation, thus eliminating one of the key advantages of Bayesian methods. To resolve this dilemma while still retaining the generalizability of the underlying local inference method, we apply the idea of expectation propagation (EP) as a framework for distributed Bayesian inference. The central idea is to iteratively update approximations to the local likelihoods given the state of the other approximations and the prior. The present paper has two roles: we review the steps that are needed to keep EP algorithms numerically stable, and we suggest a general approach, inspired by EP, for approaching data partitioning problems in a way that achieves the computational benefits of parallelism while allowing each local update to make use of relevant information from the other sites. In addition, we demonstrate how the method can be applied in a hierarchical context to make use of partitioning of both data and parameters. The paper describes a general algorithmic framework, rather than a specific algorithm, and presents an example implementation for it.

Newly launched REBA Institute shares research suggesting multiple policy pathways increase access, lower costs and drive decarbonization of the electricity sector.

(PRWeb May 05, 2020)

Read the full story at https://www.prweb.com/releases/viable_policy_pathways_expand_access_to_renewable_energy_for_commercial_industrial_sector/prweb17099869.htm

Federico Castelletti, Guido Consonni.

Source: The Annals of Applied Statistics, Volume 13, Number 4, 2289--2311.

Abstract:
A signalling pathway is a sequence of chemical reactions initiated by a stimulus which in turn affects a receptor, and then through some intermediate steps cascades down to the final cell response. Based on the technique of flow cytometry, samples of cell-by-cell measurements are collected under each experimental condition, resulting in a collection of interventional data (assuming no latent variables are involved). Usually several external interventions are applied at different points of the pathway, the ultimate aim being the structural recovery of the underlying signalling network which we model as a causal Directed Acyclic Graph (DAG) using intervention calculus. The advantage of using interventional data, rather than purely observational one, is that identifiability of the true data generating DAG is enhanced. More technically a Markov equivalence class of DAGs, whose members are statistically indistinguishable based on observational data alone, can be further decomposed, using additional interventional data, into smaller distinct Interventional Markov equivalence classes. We present a Bayesian methodology for structural learning of Interventional Markov equivalence classes based on observational and interventional samples of multivariate Gaussian observations. Our approach is objective, meaning that it is based on default parameter priors requiring no personal elicitation; some flexibility is however allowed through a tuning parameter which regulates sparsity in the prior on model space. Based on an analytical expression for the marginal likelihood of a given Interventional Essential Graph, and a suitable MCMC scheme, our analysis produces an approximate posterior distribution on the space of Interventional Markov equivalence classes, which can be used to provide uncertainty quantification for features of substantive scientific interest, such as the posterior probability of inclusion of selected edges, or paths.

Jeng-Min Chiou, Yu-Ting Chen, Tailen Hsing.

Source: The Annals of Applied Statistics, Volume 13, Number 3, 1430--1463.

Abstract:
Motivated by the study of road segmentation partitioned by shifts in traffic conditions along a freeway, we introduce a two-stage procedure, Dynamic Segmentation and Backward Elimination (DSBE), for identifying multiple changes in the mean functions for a sequence of functional data. The Dynamic Segmentation procedure searches for all possible changepoints using the derived global optimality criterion coupled with the local strategy of at-most-one-changepoint by dividing the entire sequence into individual subsequences that are recursively adjusted until convergence. Then, the Backward Elimination procedure verifies these changepoints by iteratively testing the unlikely changes to ensure their significance until no more changepoints can be removed. By combining the local strategy with the global optimal changepoint criterion, the DSBE algorithm is conceptually simple and easy to implement and performs better than the binary segmentation-based approach at detecting small multiple changes. The consistency property of the changepoint estimators and the convergence of the algorithm are proved. We apply DSBE to detect changes in traffic streams through real freeway traffic data. The practical performance of DSBE is also investigated through intensive simulation studies for various scenarios.

The CEO of Move This World isn't big on screen time, but in the midst of the coronavirus pandemic, technology--when used with care--can help strengthen relationships.

The post 4 Ways to Help Students Cultivate Meaningful Connections Through Tech appeared first on Market Brief.

Vice President Pence’s trip to Iowa shows how the Trump administration’s aims to move past coronavirus are sometimes complicated by the virus itself.

Austin-Bergstrom International Airport said it was "aware of an individual that was struck and killed on runway 17-R by a landing aircraft."

The New York City police department (NYPD) is conducting an internal investigation into a May 2 incident involving the violent arrests of multiple people, allegedly members of a group who were not social distancing

Barack Obama said the “rule of law is at risk” following the justice department’s decision to drop charges against former Trump advisor Mike Flynn, as he issued a stark warning about the long-term impact on the American way of life by his successor.

Maxim Rabinovich, Aaditya Ramdas, Michael I. Jordan, Martin J. Wainwright.

Source: Bayesian Analysis, Volume 15, Number 2, 505--532.

Abstract:
Slow mixing is the central hurdle is applications of Markov chains, especially those used for Monte Carlo approximations (MCMC). In the setting of Bayesian inference, it is often only of interest to estimate the stationary expectations of a small set of functions, and so the usual definition of mixing based on total variation convergence may be too conservative. Accordingly, we introduce function-specific analogs of mixing times and spectral gaps, and use them to prove Hoeffding-like function-specific concentration inequalities. These results show that it is possible for empirical expectations of functions to concentrate long before the underlying chain has mixed in the classical sense, and we show that the concentration rates we achieve are optimal up to constants. We use our techniques to derive confidence intervals that are sharper than those implied by both classical Markov-chain Hoeffding bounds and Berry-Esseen-corrected central limit theorem (CLT) bounds. For applications that require testing, rather than point estimation, we show similar improvements over recent sequential testing results for MCMC. We conclude by applying our framework to real-data examples of MCMC, providing evidence that our theory is both accurate and relevant to practice.

Mathieu Wolff
Jan 2, 2019; 39:3-14
Viewpoints

Does your customer relationship management strategy have what it takes to reach Generation Y? It's estimated that by 2021, an additional $394 billion in revenue could be gained from artificial intelligence adoption in CRM activities in the U.S. As companies grow and technology evolves at a faster-than-ever pace, collecting, storing and providing data is becoming a bigger and bigger task.

Oracle and Zoom just entered a deal that for once is more about technological audacity than about dollars -- a partnership to host Zoom on Oracle Cloud Infrastructure. In just a few months -- basically since the beginning of the novel coronavirus pandemic -- Zoom has seen demand for its service grow from about 10 million daily meeting participants to more than 300 million.

Paper by Mr Luiz Awazu Pereira da Silva, Deputy General Manager of the BIS, Enisse Kharroubi, Emanuel Kohlscheen and Benoît Mojon based on remarks at the University of Basel, 5 May 2019.