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  • On the foundations of multinomial Sequence based estimation

    Resource Type:
    Conference Proceeding
    Creator:
    Oommen, B. John and Kim, Sang-Woon
    Abstract:
    This paper deals with the relatively new field of sequencebased estimation which involves utilizing both the information in the observations and in their sequence of appearance. Our intention is to obtain Maximum Likelihood estimates by “extracting” the information contained in the observations when perceived as a sequence rather than as a set. The results of [15] introduced the concepts of Sequence Based Estimation (SBE) for the Binomial distribution. This current paper generalizes these results for the multinomial “two-at-a-time” scenario. We invoke a novel phenomenon called “Occlusion” that can be described as follows: By “concealing” certain observations, we map the estimation problem onto a lower-dimensional binomial space. Once these occluded SBEs have been computed, we demonstrate how the overall Multinomial SBE (MSBE) can be obtained by mapping several lower-dimensional estimates onto the original higher-dimensional space. We formally prove and experimentally demonstrate the convergence of the corresponding estimates.
    Date Created:
    2016-01-01

  • A facility coloring problem in 1-D

    Resource Type:
    Conference Proceeding
    Creator:
    Maheshwari, Anil, Nandy, Ayan, Smid, Michiel, and Das, Sandip
    Abstract:
    Consider a line segment R consisting of n facilities. Each facility is a point on R and it needs to be assigned exactly one of the colors from a given palette of c colors. At an instant of time only the facilities of one particular color are 'active' and all other facilities are 'dormant'. For the set of facilities of a particular color, we compute the one dimensional Voronoi diagram, and find the cell, i.e, a segment of maximum length. The users are assumed to be uniformly distributed over R and they travel to the nearest among the facilities of that particular color that is active. Our objective is to assign colors to the facilities in such a way that the length of the longest cell is minimized. We solve this optimization problem for various values of n and c. We propose an optimal coloring scheme for the number of facilities n being a multiple of c as well as for the general case where n is not a multiple of c. When n is a multiple of c, we compute an optimal scheme in Θ(n) time. For the general case, we propose a coloring scheme that returns the optimal in O(n2logn) time.
    Date Created:
    2014-01-01

  • Multinomial sequence based estimation using contiguous subsequences of length three

    Resource Type:
    Conference Proceeding
    Creator:
    Kim, Sang-Woon and Oommen, B. John
    Abstract:
    The Maximum Likelihood (ML) and Bayesian estimation paradigms work within the model that the data, from which the parameters are to be estimated, is treated as a set rather than as a sequence. The pioneering paper that dealt with the field of sequence-based estimation [2] involved utilizing both the information in the observations and in their sequence of appearance. The results of [2] introduced the concepts of Sequence Based Estimation (SBE) for the Binomial distribution, where the authors derived the corresponding MLE results when the samples are taken two-at-a-time, and then extended these for the cases when they are processed three-at-a-time, four-at-a-time etc. These results were generalized for the multinomial “two-at-a-time” scenario in [3]. This paper (This paper is dedicated to the memory of Dr. Mohamed Kamel, who was a close friend of the first author.) now further generalizes the results found in [3] for the multinomial case and for subsequences of length 3. The strategy used in [3] (and also here) involves a novel phenomenon called “Occlusion” that has not been reported in the field of estimation. The phenomenon can be described as follows: By occluding (hiding or concealing) certain observations, we map the estimation problem onto a lower-dimensional space, i.e., onto a binomial space. Once these occluded SBEs have been computed, the overall Multinomial SBE (MSBE) can be obtained by combining these lower-dimensional estimates. In each case, we formally prove and experimentally demonstrate the convergence of the corresponding estimates.
    Date Created:
    2016-01-01

  • Characterizing and computing causes for query answers in databases from database repairs and repair programs

    Resource Type:
    Conference Proceeding
    Creator:
    Bertossi, Leopoldo
    Abstract:
    A correspondence between database tuples as causes for query answers in databases and tuple-based repairs of inconsistent databases with respect to denial constraints has already been established. In this work, answer-set programs that specify repairs of databases are used as a basis for solving computational and reasoning problems about causes. Here, causes are also introduced at the attribute level by appealing to a both null-based and attribute-based repair semantics. The corresponding repair programs are presented, and they are used as a basis for computation and reasoning about attribute-level causes.
    Date Created:
    2018-01-01

  • Local routing in spanners based on WSPDs

    Resource Type:
    Conference Proceeding
    Creator:
    Dujmović, Vida, De Carufel, Jean-Lou, Bose, Prosenjit, and Paradis, Frédérik
    Abstract:
    The well-separated pair decomposition (WSPD) of the complete Euclidean graph defined on points in ℝ2 (Callahan and Kosaraju [JACM, 42 (1): 67-90, 1995]) is a technique for partitioning the edges of the complete graph based on length into a linear number of sets. Among the many different applications of WSPDs, Callahan and Kosaraju proved that the sparse subgraph that results by selecting an arbitrary edge from each set (called WSPD-spanner) is a 1 + 8/(s − 4)-spanner, where s > 4 is the separation ratio used for partitioning the edges. Although competitive local-routing strategies exist for various spanners such as Yao-graphs, Θ-graphs, and variants of Delaunay graphs, few local-routing strategies are known for any WSPD-spanner. Our main contribution is a local-routing algorithm with a near-optimal competitive routing ratio of 1 + O(1/s) on a WSPD-spanner. Specifically, we present a 2-local and a 1-local routing algorithm on a WSPD-spanner with competitive routing ratios of 1+6/(s−2)+4/s and 1+6/(s−2)+ 6/s + 4/(s2 − 2s) + 8/s2respectively.
    Date Created:
    2017-01-01

  • Pro-active strategies for the frugal feeding problem in wireless sensor networks

    Resource Type:
    Conference Proceeding
    Creator:
    Lanthier, Mark, Velazquez, Elio, and Santoro, Nicola
    Abstract:
    This paper proposes a pro-active solution to the Frugal Feeding Problem (FFP) in Wireless Sensor Networks. The FFP attempts to find energy-efficient routes for a mobile service entity to rendezvous with each member of a team of mobile robots. Although the complexity of the FFP is similar to the Traveling Salesman Problem (TSP), we propose an efficient solution, completely distributed and localized for the case of a fixed rendezvous location (i.e., service facility with limited number of docking ports) and mobile capable entities (sensors). Our pro-active solution reduces the FFP to finding energy-efficient routes in a dynamic Compass Directed unit Graph (CDG). The proposed CDG incorporates ideas from forward progress routing and the directionality of compass routing in an energy-aware unit sub-graph. Navigating the CDG guarantees that each sensor will reach the rendezvous location in a finite number of steps. The ultimate goal of our solution is to achieve energy equilibrium (i.e., no further sensor losses due to energy starvation) by optimizing the use of the shared resource (recharge station). We also examine the impact of critical parameters such as transmission range, cost of mobility and sensor knowledge in the overall performance.
    Date Created:
    2011-11-14

  • Bi-directional representation learning for multi-label classification

    Resource Type:
    Conference Proceeding
    Creator:
    Guo, Yuhong and Li, Xin
    Abstract:
    Multi-label classification is a central problem in many application domains. In this paper, we present a novel supervised bi-directional model that learns a low-dimensional mid-level representation for multi-label classification. Unlike traditional multi-label learning methods which identify intermediate representations from either the input space or the output space but not both, the mid-level representation in our model has two complementary parts that capture intrinsic information of the input data and the output labels respectively under the autoencoder principle while augmenting each other for the target output label prediction. The resulting optimization problem can be solved efficiently using an iterative procedure with alternating steps, while closed-form solutions exist for one major step. Our experiments conducted on a variety of multi-label data sets demonstrate the efficacy of the proposed bi-directional representation learning model for multi-label classification.
    Date Created:
    2014-01-01

  • The impact of naive agents in heterogeneous trust-aware societies

    Resource Type:
    Conference Proceeding
    Creator:
    White, Anthony and Salehi-Abari, Amirali
    Abstract:
    Autonomous agents require trust and reputation concepts in order to identify communities of agents with which to interact reliably in ways analogous to humans. Agent societies are invariably heterogeneous, with multiple decision making policies and actions governing their behaviour. Through the introduction of naive agents, this paper shows empirically that while learning agents can identify malicious agents through direct interaction, naive agents compromise utility through their inability to discern malicious agents. Moreover, the impact of the proportion of naive agents on the society is analyzed. The paper demonstrates that there is a need for witness interaction trust to detect naive agents in addition to the need for direct interaction trust to detect malicious agents. By proposing a set of policies, the paper demonstrates how learning agents can isolate themselves from naive and malicious agents.
    Date Created:
    2010-07-20

  • Coarse grained parallel algorithms for detecting convex bipartite graphs

    Resource Type:
    Conference Proceeding
    Creator:
    Prencipe, Giuseppe, Cáceres, Edson, Chan, Albert, and Dehne, Frank
    Abstract:
    In this paper, we present parallel algorithms for the coarse grained multicomputer (CGM) and the bulk synchronous parallel computer (BSP) for solving two well known graph problems: (1) determining whether a graph G is bipartite, and (2) determining whether a bipartite graph G is convex. Our algorithms require O(log p) and O(log2 p) communication rounds, respectively, and linear sequential work per round on a CGM with p processors and N/p local memory per processor, N=|G|. The algorithms assume that N/ p ≥ p€ for some fixed€ > 0, which is true for all commercially available multiprocessors. Our results imply BSP algorithms with O(log p) and O(log2 p) supersteps, respectively, O(g log(p) N p) communication time, and O(log(p) N p) local computation time. Our algorithm for determining whether a bipartite graph is convex includes a novel, coarse grained parallel, version of the PQ tree data structure introduced by Booth and Lueker. Hence, our algorithm also solves, with the same time complexity as indicated above, the problem of testing the consecutive-ones property for (0, 1) matrices as well as the chordal graph recognition problem. These, in turn, have numerous applications in graph theory, DNA sequence assembly, database theory, and other areas.
    Date Created:
    2000-01-01

  • External memory algorithms for outerplanar graphs

    Resource Type:
    Conference Proceeding
    Creator:
    Maheshwari, Anil and Zeh, Norbert
    Abstract:
    We present external memory algorithms for outerplanarity testing, embedding outerplanar graphs, breadth-first search (BFS) and depth-first search (DFS) in outerplanar graphs, and finding a2-separator of size 2 for a given outerplanar graph. Our algorithms take O(sort(N)) I/Os and can easily be improved to take O (perm (N)) I/Os, as all these problems have linear time solutions in internal memory. For BFS, DFS, and outerplanar embedding we show matching lower bounds.
    Date Created:
    1999-01-01