46,980 research outputs found
On Conceptually Simple Algorithms for Variants of Online Bipartite Matching
We present a series of results regarding conceptually simple algorithms for
bipartite matching in various online and related models. We first consider a
deterministic adversarial model. The best approximation ratio possible for a
one-pass deterministic online algorithm is , which is achieved by any
greedy algorithm. D\"urr et al. recently presented a -pass algorithm called
Category-Advice that achieves approximation ratio . We extend their
algorithm to multiple passes. We prove the exact approximation ratio for the
-pass Category-Advice algorithm for all , and show that the
approximation ratio converges to the inverse of the golden ratio
as goes to infinity. The convergence is
extremely fast --- the -pass Category-Advice algorithm is already within
of the inverse of the golden ratio.
We then consider a natural greedy algorithm in the online stochastic IID
model---MinDegree. This algorithm is an online version of a well-known and
extensively studied offline algorithm MinGreedy. We show that MinDegree cannot
achieve an approximation ratio better than , which is guaranteed by any
consistent greedy algorithm in the known IID model.
Finally, following the work in Besser and Poloczek, we depart from an
adversarial or stochastic ordering and investigate a natural randomized
algorithm (MinRanking) in the priority model. Although the priority model
allows the algorithm to choose the input ordering in a general but well defined
way, this natural algorithm cannot obtain the approximation of the Ranking
algorithm in the ROM model
A Computer Algorithm For Engineering Off-Shell Multiplets With Four Supercharges On The World Sheet
We present an adinkra-based computer algorithm implemented in a Mathematica
code and use it in a limited demonstration of how to engineer off-shell,
arbitrary N-extended world-sheet supermultiplets. Using one of the outputs from
this algorithm, we present evidence for the unexpected discovery of a
previously unknown 8 - 8 representation of N = 2 world sheet supersymmetry. As
well, we uncover a menagerie of (p, q) = (3, 1) world sheet supermultiplets.Comment: 52 pages, 64 figures, LaTeX twice, added note in proof, addition of
comments about gauge invariance for 4D vector & tensor supermultiplet
Networks of strong ties
Social networks transmitting covert or sensitive information cannot use all
ties for this purpose. Rather, they can only use a subset of ties that are
strong enough to be ``trusted''. In this paper we consider transitivity as
evidence of strong ties, requiring that each tie can only be used if the
individuals on either end also share at least one other contact in common. We
examine the effect of removing all non-transitive ties in two real social
network data sets. We observe that although some individuals become
disconnected, a giant connected component remains, with an average shortest
path only slightly longer than that of the original network. We also evaluate
the cost of forming transitive ties by deriving the conditions for the
emergence and the size of the giant component in a random graph composed
entirely of closed triads and the equivalent Erdos-Renyi random graph.Comment: 10 pages, 7 figure
Word-Entity Duet Representations for Document Ranking
This paper presents a word-entity duet framework for utilizing knowledge
bases in ad-hoc retrieval. In this work, the query and documents are modeled by
word-based representations and entity-based representations. Ranking features
are generated by the interactions between the two representations,
incorporating information from the word space, the entity space, and the
cross-space connections through the knowledge graph. To handle the
uncertainties from the automatically constructed entity representations, an
attention-based ranking model AttR-Duet is developed. With back-propagation
from ranking labels, the model learns simultaneously how to demote noisy
entities and how to rank documents with the word-entity duet. Evaluation
results on TREC Web Track ad-hoc task demonstrate that all of the four-way
interactions in the duet are useful, the attention mechanism successfully
steers the model away from noisy entities, and together they significantly
outperform both word-based and entity-based learning to rank systems
On-line planning and scheduling: an application to controlling modular printers
We present a case study of artificial intelligence techniques applied to the control of production printing equipment. Like many other real-world applications, this complex domain requires high-speed autonomous decision-making and robust continual operation. To our knowledge, this work represents the first successful industrial application of embedded domain-independent temporal planning. Our system handles execution failures and multi-objective preferences. At its heart is an on-line algorithm that combines techniques from state-space planning and partial-order scheduling. We suggest that this general architecture may prove useful in other applications as more intelligent systems operate in continual, on-line settings. Our system has been used to drive several commercial prototypes and has enabled a new product architecture for our industrial partner. When compared with state-of-the-art off-line planners, our system is hundreds of times faster and often finds better plans. Our experience demonstrates that domain-independent AI planning based on heuristic search can flexibly handle time, resources, replanning, and multiple objectives in a high-speed practical application without requiring hand-coded control knowledge
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