Policing Kentucky\u27s School Children: Issues and Trends

The purpose of this research bulletin is to document the scope and nature of an important dimension of the school safety movement--the degree to which schools in Kentucky are being policed by public police agencies. A shift toward having an active police presence in our public schools, an unprecedented and significiant development, should be examined carefully

From internationalization to global citizenship: Dialogues in international higher education

As we consider assessment and, by implication, graduation, the question of what sort of graduate we are sending out into the world arises. A university education is not simply more stuff than A-level: it is, we hope, part of the transformation of a student into the adult they were always capable of being, realizing their potential. But as our opening chapter argued, there has to be a selection process for what is going to be emphasized: just being knowledgeable is a recipe for narrowness, and for our new graduate to be wrong-footed by a world that is far more complex than their university life prepared them for. Universities were ‘global’ long before almost any other ventures, with international collaboration on research going back centuries; our students come from all over the world, and our graduates go just about everywhere. We would be irresponsible not to consider how best to prepare them for that fact, but it is not straightforward – there are competing versions of what it is to be a ‘global citizen’, as this chapter explores

A Cost-based Optimizer for Gradient Descent Optimization

As the use of machine learning (ML) permeates into diverse application domains, there is an urgent need to support a declarative framework for ML. Ideally, a user will specify an ML task in a high-level and easy-to-use language and the framework will invoke the appropriate algorithms and system configurations to execute it. An important observation towards designing such a framework is that many ML tasks can be expressed as mathematical optimization problems, which take a specific form. Furthermore, these optimization problems can be efficiently solved using variations of the gradient descent (GD) algorithm. Thus, to decouple a user specification of an ML task from its execution, a key component is a GD optimizer. We propose a cost-based GD optimizer that selects the best GD plan for a given ML task. To build our optimizer, we introduce a set of abstract operators for expressing GD algorithms and propose a novel approach to estimate the number of iterations a GD algorithm requires to converge. Extensive experiments on real and synthetic datasets show that our optimizer not only chooses the best GD plan but also allows for optimizations that achieve orders of magnitude performance speed-up.Comment: Accepted at SIGMOD 201

Beyond Amateurism: The Rebranding of Major College Athletics

For decades prior to NCAA v. Board of Regents, the brand of college athletics, even at the highest level, was amateurism. However, the last three decades of surging revenues and costs, as well as the current wave of litigation challenging amateurism, force decision makers in major college athletics to contemplate a future in which amateurism is banished or in retreat. In sum, the brand has outgrown amateurism. Major college athletics can survive a paradigm shift by selling the action in its games, the game day experience, and the traditions of the institutions

LINVIEW: Incremental View Maintenance for Complex Analytical Queries

Many analytics tasks and machine learning problems can be naturally expressed by iterative linear algebra programs. In this paper, we study the incremental view maintenance problem for such complex analytical queries. We develop a framework, called LINVIEW, for capturing deltas of linear algebra programs and understanding their computational cost. Linear algebra operations tend to cause an avalanche effect where even very local changes to the input matrices spread out and infect all of the intermediate results and the final view, causing incremental view maintenance to lose its performance benefit over re-evaluation. We develop techniques based on matrix factorizations to contain such epidemics of change. As a consequence, our techniques make incremental view maintenance of linear algebra practical and usually substantially cheaper than re-evaluation. We show, both analytically and experimentally, the usefulness of these techniques when applied to standard analytics tasks. Our evaluation demonstrates the efficiency of LINVIEW in generating parallel incremental programs that outperform re-evaluation techniques by more than an order of magnitude.Comment: 14 pages, SIGMO

Consistency in scalable systems

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