Optimal provision of distributed reserves under dynamic energy service preferences

We propose and solve a stochastic dynamic programming (DP) problem addressing the optimal provision of regulation service reserves (RSR) by controlling dynamic demand preferences in smart buildings. A major contribution over past dynamic pricing work is that we pioneer the relaxation of static, uniformly distributed utility of demand. In this paper we model explicitly the dynamics of energy service preferences leading to a non-uniform and time varying probability distribution of demand utility. More explicitly, we model active and idle duty cycle appliances in a smart building as a closed queuing system with price-controlled arrival rates into the active appliance queue. Focusing on cooling appliances, we model the utility associated with the transition from idle to active as a non-uniform time varying function. We (i) derive an analytic characterization of the optimal policy and the differential cost function, and (ii) prove optimal policy monotonicity and value function convexity. These properties enable us to propose and implement a smart assisted value iteration (AVI) algorithm and an approximate DP (ADP) that exploits related functional approximations. Numerical results demonstrate the validity of the solution techniques and the computational advantage of the proposed ADP on realistic, large-state-space problems

Divide and Conquer Kernel Ridge Regression: A Distributed Algorithm with Minimax Optimal Rates

We establish optimal convergence rates for a decomposition-based scalable approach to kernel ridge regression. The method is simple to describe: it randomly partitions a dataset of size N into m subsets of equal size, computes an independent kernel ridge regression estimator for each subset, then averages the local solutions into a global predictor. This partitioning leads to a substantial reduction in computation time versus the standard approach of performing kernel ridge regression on all N samples. Our two main theorems establish that despite the computational speed-up, statistical optimality is retained: as long as m is not too large, the partition-based estimator achieves the statistical minimax rate over all estimators using the set of N samples. As concrete examples, our theory guarantees that the number of processors m may grow nearly linearly for finite-rank kernels and Gaussian kernels and polynomially in N for Sobolev spaces, which in turn allows for substantial reductions in computational cost. We conclude with experiments on both simulated data and a music-prediction task that complement our theoretical results, exhibiting the computational and statistical benefits of our approach

IT2017 Report: Implementing A Competency-Based Information Technology Program (Panel)

ACMand IEEE have developed a computing curriculum report titled Information Technology Curricular 2017: Curriculum Guidelines for Undergraduate Degree Programs in Information Technology, also known as IT2017 [4]. The development of this report has received content contributions from industry and academia through surveys as well as many international conferences and workshops. Open online publication of the report became available in fall of 2017. In this special session, �ve members of the IT2017 executive committee will present a digest of the content of the report, describe the proposed IT curricular framework, and facilitate open and vigorous discussion of the report\u27s guidelines for developing new information technology programs or enhancing existing ones. The novelty of the report is its focus on industry-informed competencies that IT graduates should have to meet the growing demands of a changing technological world in the next decade. The experience should provide a better understanding of IT in a modern age

URBAN ENVIRONMENTAL SERVICES IN DEVELOPING COUNTRIES

As cities in the developing world grow, their poor residents are being deprived of services, especially water, sewer, and solid waste collection, that can only be purchased expensively in private markets. But the inadequate provision of urban environmental services is not inevitable. A lack of will in this respect is partly due to an ambivalent attitude toward city growth and a widespread feeling that rural-urban migration is excessive. Provision of optimal urban environmental services is also expensive. While the budget problems are exacerbated by foolish pricing policies and cost inefficiencies, it may not be feasible for developing countries to provide all urban residents with optimal service levels. There are many ways to provide basic services to poor residents.Resource /Energy Economics and Policy,