For dynamic application scenarios of Mobile Edge Computing (MEC), an Energy-efficient Multiuser and Multitask Computation Offloading (EMMCO) optimization method is proposed. Under the consideration multiuser multitask computation offloading, first, EMMCO takes into account existence dependencies among different tasks within implementation, abstracts these as a Directed Acyclic Graph (DAG), mode...

Directed acyclic graph (DAG)-aware task scheduling algorithms have been studied extensively in recent years, and these achieved significant performance improvements data-parallel analytic platforms. However, current DAG-aware algorithms, among which HEFT GRAPHENE are notable, pay little attention to the cache management policy, plays a vital role in-memory systems such as Spark. Cache policies ...

1 JlŘÍ VOMLEL Wc propose a framework for building decision strategies using Bayesian network models and discuss its application to adaptive testing. Dynamic programming and AO* algorithm are used to find optimal adaptive tests. The proposed AO* algorithm is based on a new admissible heuristic function. 1. BAYESIAN NETWORKS Bayesian networks are probabilistic graphical models that are capable of...

Motivated by the problem of designing inference-friendly Bayesian nonparametric models in probabilistic programming languages, we introduce a general class partially exchangeable random arrays which generalizes notion hierarchical exchangeability introduced Austin and Panchenko (2014). We say that our are DAG-exchangeable since their structure is governed collection Directed Acyclic Graphs. Mor...

In a previous article, we considered game trees as graphical models. Adopting an evaluation function that returned a probability distribution over values likely to be taken at a given position, we described how to build a model of uncertainty and use it for utility-directed growth of the search tree and for deciding on a move after search was completed. In some games, such as chess and Othello,...

We assume that we have observational data generated from an unknown underlying directed acyclic graph (DAG) model. A DAG is typically not identifiable from observational data, but it is possible to consistently estimate the equivalence class of a DAG. Moreover, for any given DAG, causal effects can be estimated using intervention calculus. In this paper, we combine these two parts. For each DAG...

A primary object of causal reasoning concerns what would happen to a system under certain interventions. Specifically, we are often interested in estimating the probability distribution of some random variables that would result from forcing some other variables to take certain values. The renowned do-calculus (Pearl 1995) gives a set of rules that govern the identification of such post-interve...

Finding the origin of short phrases propagating through the web has been formalized by Leskovec et al. [ACM SIGKDD 2009] as DAG PARTITIONING: given an arc-weighted directed acyclic graph on n vertices and m arcs, delete arcs with total weight at most k such that each resulting weakly-connected component contains exactly one sink—a vertex without outgoing arcs. DAG PARTITIONING is NP-hard. We sh...

With the faster maturity and stability of digitization, connectivity edge technologies, number Internet Things (IoT) devices sensors is flourishing fast in important junctions such as homes, hotels, hospitals, retail stores, manufacturing floors, railway stations, airports, oil wells, warehouses, etc. However, this extremely connected world, security implications for IoT are getting worse with ...

Local-to-global learning approach plays an essential role in Bayesian network (BN) structure learning. Existing local-to-global algorithms first construct the skeleton of a DAG (directed acyclic graph) by MB (Markov blanket) or PC (parents and children) each variable data set, then orient edges skeleton. However, existing methods are often computationally expensive especially with large-sized B...