Primal-Dual Rates and Certificates

We propose an algorithm-independent framework to equip existing optimization methods with primal-dual certificates. Such certificates and corresponding rate of convergence guarantees are important for practitioners to diagnose progress, in particular in machine learning applications. We obtain new primal-dual convergence rates, e.g., for the Lasso as well as many L1, Elastic Net, group Lasso and TV-regularized problems. The theory applies to any norm-regularized generalized linear model. Our approach provides efficiently computable duality gaps which are globally defined, without modifying the original problems in the region of interest.Comment: appearing at ICML 2016 - Proceedings of the 33rd International Conference on Machine Learning, New York, NY, USA, 2016. JMLR: W&CP volume 4

L1-Regularized Distributed Optimization: A Communication-Efficient Primal-Dual Framework

Despite the importance of sparsity in many large-scale applications, there are few methods for distributed optimization of sparsity-inducing objectives. In this paper, we present a communication-efficient framework for L1-regularized optimization in the distributed environment. By viewing classical objectives in a more general primal-dual setting, we develop a new class of methods that can be efficiently distributed and applied to common sparsity-inducing models, such as Lasso, sparse logistic regression, and elastic net-regularized problems. We provide theoretical convergence guarantees for our framework, and demonstrate its efficiency and flexibility with a thorough experimental comparison on Amazon EC2. Our proposed framework yields speedups of up to 50x as compared to current state-of-the-art methods for distributed L1-regularized optimization

Top Quark Pair Production beyond NNLO

We construct an approximate expression for the total cross section for the production of a heavy quark-antiquark pair in hadronic collisions at next-to-next-to-next-to-leading order (N$^3$LO) in $\alpha_s$. We use a technique which exploits the analyticity of the Mellin space cross section, and the information on its singularity structure coming from large N (soft gluon, Sudakov) and small N (high energy, BFKL) all order resummations, previously introduced and used in the case of Higgs production. We validate our method by comparing to available exact results up to NNLO. We find that N$^3$LO corrections increase the predicted top pair cross section at the LHC by about 4% over the NNLO.Comment: 34 pages, 9 figures; final version, to be published in JHEP; reference added, minor improvement

CoCoA: A General Framework for Communication-Efficient Distributed Optimization

The scale of modern datasets necessitates the development of efficient distributed optimization methods for machine learning. We present a general-purpose framework for distributed computing environments, CoCoA, that has an efficient communication scheme and is applicable to a wide variety of problems in machine learning and signal processing. We extend the framework to cover general non-strongly-convex regularizers, including L1-regularized problems like lasso, sparse logistic regression, and elastic net regularization, and show how earlier work can be derived as a special case. We provide convergence guarantees for the class of convex regularized loss minimization objectives, leveraging a novel approach in handling non-strongly-convex regularizers and non-smooth loss functions. The resulting framework has markedly improved performance over state-of-the-art methods, as we illustrate with an extensive set of experiments on real distributed datasets

A Clean Energy Atlas for Energy Communities in Piedmont Region (Italy)

The energy community is defined as a “cooperative/partnership/non-profit organization of final customers (municipalities, public and private entities, citizens) aimed at achieving energy independence in order to guarantee energy security, low environment impact and affordable energy costs”. This work defines a place-based methodology for the dimensioning of energy communities, according to the requirements of the first Italian law on energy communities issued by the Piedmont Region. The aim is to evaluate the correct size and optimal aggregation of municipalities for future energy communities, considering the energy consumptions and the renewable energy sources available in a territory. In particular, with a place-based methodology, the electricity potentially produced by forest and agricultural biomass, waste, wind, solar and hydraulic sources was evaluated, in accordance with regulations and constrains. Thus, a renewable energy sources atlas was implemented to provide a tool for the estimation of energy, environmental and socio-economic performance indexes of the municipalities of the Piedmont Region. In conclusion, considering the energy production, productivity and consumption of each municipality and the requirements of energy communities, a tool to optimally aggregate municipalities for creating energetic communities is described

Strategies for Reducing Employee Absenteeism for a Sustainable Future: A Bermuda Perspective

Employee absenteeism results in billions of dollars in revenue losses and lost productivity annually. Given the consequences that organizations could face resulting from high levels of work absences, executives should develop strategies to manage absenteeism to support organizational growth and sustainability. Grounded in the theory of planned behavior, the purpose of the single case study was to explore strategies managers in the private insurance industry used to reduce employee absenteeism. The population consisted of 3 managers located in Bermuda who implemented strategies to decrease employee absenteeism from a Bermuda perspective. Data included semistructured interviews, results of the company\u27s 2016 engagement survey, and annual reports from 2014 to 2016 that highlighted the company\u27s commitment to providing strategies to enhance employees\u27 engagement and dedication to its strategic objectives. Through thematic analysis, 4 themes emerged: employee engagement, managerial communication, employee wellness and health promotion programs, and achieving work-life balance. Business managers could use these findings to understand how specific human resources strategies with a focus towards reducing employee absenteeism minimize work absences. Minimizing work absences could contribute to positive social change through increased economic growth in local communities and higher quality of life for its residents

FOXO3 on the Road to Longevity: Lessons From SNPs and Chromatin Hubs

Health span is driven by a precise interplay between genes and the environment. Cell response to environmental cues is mediated by signaling cascades and genetic variants that affect gene expression by regulating chromatin plasticity. Indeed, they can promote the interaction of promoters with regulatory elements by forming active chromatin hubs. FOXO3 encodes a transcription factor with a strong impact on aging and age-related phenotypes, as it regulates stress response, therefore affecting lifespan. A significant association has been shown between human longevity and several FOXO3 variants located in intron 2. This haplotype block forms a putative aging chromatin hub in which FOXO3 has a central role, as it modulates the physical connection and activity of neighboring genes involved in age-related processes. Here we describe the role of FOXO3 and its single-nucleotide polymorphisms (SNPs) in healthy aging, with a focus on the enhancer region encompassing the SNP rs2802292, which upregulates FOXO3 expression and can promote the activity of the aging hub in response to different stress stimuli. FOXO3 protective effect on lifespan may be due to the accessibility of this region to transcription factors promoting its expression. This could in part explain the differences in FOXO3 association with longevity between genders, as its activity in females may be modulated by estrogens through estrogen receptor response elements located in the rs2802292-encompassing region. Altogether, the molecular mechanisms described here may help establish whether the rs2802292 SNP can be taken advantage of in predictive medicine and define the potential of targeting FOXO3 for age-related diseases

Interpreting Housing Prices with a MultidisciplinaryApproach Based on Nature-Inspired Algorithms and Quantum Computing

Current technology still does not allow the use of quantum computers for broader and individual uses; however, it is possible to simulate some of its potentialities through quantum computing. Quantum computing can be integrated with nature-inspired algorithms to innovatively analyze the dynamics of the real estate market or any other economic phenomenon. With this main aim, this study implements a multidisciplinary approach based on the integration of quantum computing and genetic algorithms to interpret housing prices. Starting from the principles of quantum programming, the work applies genetic algorithms for the marginal price determination of relevant real estate characteristics for a particular segment of Naples’ real estate market. These marginal prices constitute the quantum program inputs to provide, as results, the purchase probabilities corresponding to each real estate characteristic considered. The other main outcomes of this study consist of a comparison of the optimal quantities for each real estate characteristic as determined by the quantum program and the average amounts of the same characteristics but relative to the real estate data sampled, as well as the weights of the same characteristics obtained with the implementation of genetic algorithms. With respect to the current state of the art, this study is among the first regarding the application of quantum computing to interpretation of selling prices in local real estate markets

Finite-top-mass effects in NNLO Higgs production

We construct an accurate approximation to the exact NNLO cross section for Higgs production in gluon-gluon fusion by matching the dominant finite top mass corrections recently computed by us to the known result in the infinite mass limit. The ensuing corrections to the partonic cross section are very large when the center of mass energy of the partonic collision is much larger than the Higgs mass, but lead to a moderate correction at the percent level to the total Higgs production cross section at the LHC. Our computation thus reduces the uncertainty related to these corrections at the LHC from the percent to the per mille level.Comment: 4 pages, 4 figures; to be published in the proceedings of QCD2008. Reference adde