261 research outputs found

    Vertex-algebraic structure of the principal subspaces of certain A_1^(1)-modules, II: higher level case

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    We give an a priori proof of the known presentations of (that is, completeness of families of relations for) the principal subspaces of all the standard A_1^(1)-modules. These presentations had been used by Capparelli, Lepowsky and Milas for the purpose of obtaining the classical Rogers-Selberg recursions for the graded dimensions of the principal subspaces. This paper generalizes our previous paper.Comment: 26 pages; v2: minor revisions, to appear in Journal of Pure and Applied Algebr

    Streaming Algorithms for Submodular Function Maximization

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    We consider the problem of maximizing a nonnegative submodular set function f:2Nā†’R+f:2^{\mathcal{N}} \rightarrow \mathbb{R}^+ subject to a pp-matchoid constraint in the single-pass streaming setting. Previous work in this context has considered streaming algorithms for modular functions and monotone submodular functions. The main result is for submodular functions that are {\em non-monotone}. We describe deterministic and randomized algorithms that obtain a Ī©(1p)\Omega(\frac{1}{p})-approximation using O(klogā”k)O(k \log k)-space, where kk is an upper bound on the cardinality of the desired set. The model assumes value oracle access to ff and membership oracles for the matroids defining the pp-matchoid constraint.Comment: 29 pages, 7 figures, extended abstract to appear in ICALP 201

    Truthful Multi-unit Procurements with Budgets

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    We study procurement games where each seller supplies multiple units of his item, with a cost per unit known only to him. The buyer can purchase any number of units from each seller, values different combinations of the items differently, and has a budget for his total payment. For a special class of procurement games, the {\em bounded knapsack} problem, we show that no universally truthful budget-feasible mechanism can approximate the optimal value of the buyer within lnā”n\ln n, where nn is the total number of units of all items available. We then construct a polynomial-time mechanism that gives a 4(1+lnā”n)4(1+\ln n)-approximation for procurement games with {\em concave additive valuations}, which include bounded knapsack as a special case. Our mechanism is thus optimal up to a constant factor. Moreover, for the bounded knapsack problem, given the well-known FPTAS, our results imply there is a provable gap between the optimization domain and the mechanism design domain. Finally, for procurement games with {\em sub-additive valuations}, we construct a universally truthful budget-feasible mechanism that gives an O(logā”2nlogā”logā”n)O(\frac{\log^2 n}{\log \log n})-approximation in polynomial time with a demand oracle.Comment: To appear at WINE 201

    Vertex-algebraic structure of the principal subspaces of certain A_1^(1)-modules, I: level one case

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    This is the first in a series of papers in which we study vertex-algebraic structure of Feigin-Stoyanovsky's principal subspaces associated to standard modules for both untwisted and twisted affine Lie algebras. A key idea is to prove suitable presentations of principal subspaces, without using bases or even ``small'' spanning sets of these spaces. In this paper we prove presentations of the principal subspaces of the basic A_1^(1)-modules. These convenient presentations were previously used in work of Capparelli-Lepowsky-Milas for the purpose of obtaining the classical Rogers-Ramanujan recursion for the graded dimensions of the principal subspaces.Comment: 20 pages. To appear in International J. of Mat

    An iterative decision-making scheme for Markov decision processes and its application to self-adaptive systems

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    Software is often governed by and thus adapts to phenomena that occur at runtime. Unlike traditional decision problems, where a decision-making model is determined for reasoning, the adaptation logic of such software is concerned with empirical data and is subject to practical constraints. We present an Iterative Decision-Making Scheme (IDMS) that infers both point and interval estimates for the undetermined transition probabilities in a Markov Decision Process (MDP) based on sampled data, and iteratively computes a confidently optimal scheduler from a given finite subset of schedulers. The most important feature of IDMS is the flexibility for adjusting the criterion of confident optimality and the sample size within the iteration, leading to a tradeoff between accuracy, data usage and computational overhead. We apply IDMS to an existing self-adaptation framework Rainbow and conduct a case study using a Rainbow system to demonstrate the flexibility of IDMS

    On k-Column Sparse Packing Programs

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    We consider the class of packing integer programs (PIPs) that are column sparse, i.e. there is a specified upper bound k on the number of constraints that each variable appears in. We give an (ek+o(k))-approximation algorithm for k-column sparse PIPs, improving on recent results of k2ā‹…2kk^2\cdot 2^k and O(k2)O(k^2). We also show that the integrality gap of our linear programming relaxation is at least 2k-1; it is known that k-column sparse PIPs are Ī©(k/logā”k)\Omega(k/ \log k)-hard to approximate. We also extend our result (at the loss of a small constant factor) to the more general case of maximizing a submodular objective over k-column sparse packing constraints.Comment: 19 pages, v3: additional detail

    Thresholded Covering Algorithms for Robust and Max-Min Optimization

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    The general problem of robust optimization is this: one of several possible scenarios will appear tomorrow, but things are more expensive tomorrow than they are today. What should you anticipatorily buy today, so that the worst-case cost (summed over both days) is minimized? Feige et al. and Khandekar et al. considered the k-robust model where the possible outcomes tomorrow are given by all demand-subsets of size k, and gave algorithms for the set cover problem, and the Steiner tree and facility location problems in this model, respectively. In this paper, we give the following simple and intuitive template for k-robust problems: "having built some anticipatory solution, if there exists a single demand whose augmentation cost is larger than some threshold, augment the anticipatory solution to cover this demand as well, and repeat". In this paper we show that this template gives us improved approximation algorithms for k-robust Steiner tree and set cover, and the first approximation algorithms for k-robust Steiner forest, minimum-cut and multicut. All our approximation ratios (except for multicut) are almost best possible. As a by-product of our techniques, we also get algorithms for max-min problems of the form: "given a covering problem instance, which k of the elements are costliest to cover?".Comment: 24 page

    Stochastic Vehicle Routing with Recourse

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    We study the classic Vehicle Routing Problem in the setting of stochastic optimization with recourse. StochVRP is a two-stage optimization problem, where demand is satisfied using two routes: fixed and recourse. The fixed route is computed using only a demand distribution. Then after observing the demand instantiations, a recourse route is computed -- but costs here become more expensive by a factor lambda. We present an O(log^2 n log(n lambda))-approximation algorithm for this stochastic routing problem, under arbitrary distributions. The main idea in this result is relating StochVRP to a special case of submodular orienteering, called knapsack rank-function orienteering. We also give a better approximation ratio for knapsack rank-function orienteering than what follows from prior work. Finally, we provide a Unique Games Conjecture based omega(1) hardness of approximation for StochVRP, even on star-like metrics on which our algorithm achieves a logarithmic approximation.Comment: 20 Pages, 1 figure Revision corrects the statement and proof of Theorem 1.

    Vertex Sparsifiers: New Results from Old Techniques

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    Given a capacitated graph G=(V,E)G = (V,E) and a set of terminals KāŠ†VK \subseteq V, how should we produce a graph HH only on the terminals KK so that every (multicommodity) flow between the terminals in GG could be supported in HH with low congestion, and vice versa? (Such a graph HH is called a flow-sparsifier for GG.) What if we want HH to be a "simple" graph? What if we allow HH to be a convex combination of simple graphs? Improving on results of Moitra [FOCS 2009] and Leighton and Moitra [STOC 2010], we give efficient algorithms for constructing: (a) a flow-sparsifier HH that maintains congestion up to a factor of O(logā”k/logā”logā”k)O(\log k/\log \log k), where k=āˆ£Kāˆ£k = |K|, (b) a convex combination of trees over the terminals KK that maintains congestion up to a factor of O(logā”k)O(\log k), and (c) for a planar graph GG, a convex combination of planar graphs that maintains congestion up to a constant factor. This requires us to give a new algorithm for the 0-extension problem, the first one in which the preimages of each terminal are connected in GG. Moreover, this result extends to minor-closed families of graphs. Our improved bounds immediately imply improved approximation guarantees for several terminal-based cut and ordering problems.Comment: An extended abstract appears in the 13th International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX), 2010. Final version to appear in SIAM J. Computin

    A rare presentation of the Klinefelter's syndrome

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    A 16 years old boy with Chronic Renal Failure (CRF) was not suspected of having Klinefelter's syndrome until he complained of painful gynecomastia. He was under haemodialysis for 2 years. At first, he was in an approximately full pubertal development (P5, G5), but he had a small and a firm testis (length 2.2cm) and some degree of facial male pattern hair. He also had a decreased upper to lower body segment ratio and despite having chronic renal failure, he was taller than his parents and siblings. His laboratory tests showed high levels of FSH and normal levels of LH and testosterone. With regards to all these findings, we suspected that there might be an occult Klinefelter's syndrome. So, we made his karyotype that showed a 47XXY pattern. Because there are only a few number of cases that have occult Klinefelter's syndrome in the basis of chronic renal failure, we decided to report this case
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