Differentially Private Publication of Sparse Data

The problem of privately releasing data is to provide a version of a dataset without revealing sensitive information about the individuals who contribute to the data. The model of differential privacy allows such private release while providing strong guarantees on the output. A basic mechanism achieves differential privacy by adding noise to the frequency counts in the contingency tables (or, a subset of the count data cube) derived from the dataset. However, when the dataset is sparse in its underlying space, as is the case for most multi-attribute relations, then the effect of adding noise is to vastly increase the size of the published data: it implicitly creates a huge number of dummy data points to mask the true data, making it almost impossible to work with. We present techniques to overcome this roadblock and allow efficient private release of sparse data, while maintaining the guarantees of differential privacy. Our approach is to release a compact summary of the noisy data. Generating the noisy data and then summarizing it would still be very costly, so we show how to shortcut this step, and instead directly generate the summary from the input data, without materializing the vast intermediate noisy data. We instantiate this outline for a variety of sampling and filtering methods, and show how to use the resulting summary for approximate, private, query answering. Our experimental study shows that this is an effective, practical solution, with comparable and occasionally improved utility over the costly materialization approach

Global solutions of the Landau--Lifshitz--Baryakhtar equation

The Landau--Lifshitz--Baryakhtar (LLBar) equation is a generalisation of the Landau--Lifshitz--Gilbert and the Landau--Lifshitz--Bloch equations which takes into account contributions from nonlocal damping and is valid at moderate temperature below the Curie temperature. Therefore, it is used to explain some discrepancies between the experimental observations and the known theories in various problems on magnonics and magnetic domain-wall dynamics. In this paper, the existence and uniqueness of global weak, strong, and regular solutions to LLBar equation are proven. H\"older continuity of the solution is also discussed.Comment: title changed, existence & uniqueness of global weak and strong solutions are show

Stable C1C^1-conforming finite element methods for the Landau--Lifshitz--Baryakhtar equation

The Landau--Lifshitz--Baryakhtar equation describes the evolution of magnetic spin field in magnetic materials at elevated temperature below the Curie temperature, when long-range interactions and longitudinal dynamics are taken into account. We propose two linear fully-discrete $C^1$-conforming methods to solve the problem, namely a semi-implicit Euler method and a semi-implicit BDF method, and show that these schemes are unconditionally stable. Error analysis is performed which shows optimal convergence rates in each case. Numerical results corroborate our theoretical results

Indochinese Mental Health In North America: Measures, Status, and Treatments

The massive influx of Indochinese refugees and immigrants to North America since the end of the Indochina war, especially to the United States of America, has resulted in numerous multi-disciplinary efforts to document and study their mental well-being. As a group, Indochinese Americans arrived from war-torn countries where many had experienced various forms of trauma, poverty, and oppression. Their pre-migration experiences, and experiences in adjusting and adapting to the new life in the host society have influenced their mental health status and overall quality of life in various ways. This paper analyzes and synthesizes a wealth of multi-disciplinary research on the mental health of Indochinese Americans over the course of two decades. The content of the paper encompasses three important dimensions: measures, status, and treatment. Practical implications are presented and discussed around each dimension of mental health research

A generic domain pruning technique for GDL-based DCOP algorithms in cooperative multi-agent systems

Generalized Distributive Law (GDL) based message passing algorithms, such as Max-Sum and Bounded Max-Sum, are often used to solve distributed constraint optimization problems in cooperative multi-agent systems (MAS). However, scalability becomes a challenge when these algorithms have to deal with constraint functions with high arity or variables with a large domain size. In either case, the ensuing exponential growth of search space can make such algorithms computationally infeasible in practice. To address this issue, we develop a generic domain pruning technique that enables these algorithms to be effectively applied to larger and more complex problems. We theoretically prove that the pruned search space obtained by our approach does not affect the outcome of the algorithms. Moreover, our empirical evaluation illustrates a significant reduction of the search space, ranging from 33% to 81%, without affecting the solution quality of the algorithms, compared to the state-of-the-art

Displacement and equilibrium mesh-free formulation based on integrated radial basis functions for dual yield design

This paper presents displacement and equilibrium mesh-free formulation based on integrated radial basis functions(iRBF) for upper and lower bound yield design problems. In these approaches, displacement and stress fields are approximated by the integrated radial basis functions, and the equilibrium equations and boundary conditions are imposed directly at the collocation points. In this paper it has been shown that direct nodal integration of the iRBF approximation can prevent volumetric locking in the kinematic formulation, and instability problems can also be avoided. Moreover, with the use of the collocation method in the static problem, equilibrium equations and yield conditions only need to be enforced at the nodes, leading to the reduction in computational cost. The mean value of the approximated upper and lower bound is found to be in excellent agreement with the available analytical solution, and can be considered as the actual collapse load multiplier for most practical engineering problems, for which exact solution is unknown

What prize is right? How to learn the optimal structure for crowdsourcing contests

In crowdsourcing, one effective method for encouraging par-ticipants to perform tasks is to run contests where participants compete against each other for rewards. However, there are numerous ways to implement such contests in specific projects. They could vary in their structure (e.g., performance evaluation and the number of prizes) and parameters (e.g., the maximum number of participants and the amount of prize money). Additionally, with a given budget and a time limit, choosing incentives (i.e., contest structures with specific parameter values) that maximise the overall utility is not trivial, as their respective effectiveness in a specific project is usually unknown a priori. Thus, in this paper, we propose a novel algorithm, BOIS (Bayesian-optimisation-based incentive selection), to learn the optimal structure and tune its parameters effectively. In detail, the learning and tuning problems are solved simultaneously by using online learning in combination with Bayesian optimisation. The results of our extensive simulations show that the performance of our algorithm is up to 85% of the optimal and up to 63% better than state-of-the-art benchmarks

Optimal interdiction of urban criminals with the aid of real-time information

Most violent crimes happen in urban and suburban cities. With emerging tracking techniques, law enforcement officers can have real-time location information of the escaping criminals and dynamically adjust the security resource allocation to interdict them. Unfortunately, existing work on urban network security games largely ignores such information. This paper addresses this omission. First, we show that ignoring the real-time information can cause an arbitrarily large loss of efficiency. To mitigate this loss, we propose a novel NEtwork purSuiT game (NEST) model that captures the interaction between an escaping adversary and a defender with multiple resources and real-time information available. Second, solving NEST is proven to be NP-hard. Third, after transforming the non-convex program of solving NEST to a linear program, we propose our incremental strategy generation algorithm, including: (i) novel pruning techniques in our best response oracle; and (ii) novel techniques for mapping strategies between subgames and adding multiple best response strategies at one iteration to solve extremely large problems. Finally, extensive experiments show the effectiveness of our approach, which scales up to realistic problem sizes with hundreds of nodes on networks including the real network of Manhattan

Maize in Vietnam: Production Systems, Constraints, and Research Priorities

Crop Production/Industries,

One-loop expressions for h→llˉγh\rightarrow l\bar{l}\gamma in Higgs extensions of the Standard Model

A systematic study of one-loop contributions to the decay channels $h\rightarrow l\bar{l}\gamma$ with $l=\nu_{e,\mu, \tau}, e, \mu$, performed in Higgs extended versions of the Standard Model, is presented in the 't Hooft-Veltman gauge. Analytic formulas for one-loop form factors are expressed in terms of the logarithm and di-logarithmic functions. As a result, these form factors can be reduced to those relating to the loop-induced decay processes $h\rightarrow \gamma\gamma, Z\gamma$, confirming not only previous results using different approaches but also close relations between the three kinds of the loop-induced Higgs decay rates. For phenomenological study, we focus on the two observables, namely the enhancement factors defined as ratios of the decay rates calculated between the Higgs extended versions and the standard model, and the forward-backward asymmetries of fermions, which can be used to search for Higgs extensions of the SM. We show that direct effects of mixing between neutral Higgs bosons and indirect contributions of charged Higg boson exchanges can be probed at future colliders.Comment: 39 pages, 9 Figures, 11 Tables of dat