... 4-2 Large- Scale MPLS VPN Deployment Copyright 2000, Cisco Systems, Inc. MP-BGP Scalability Mechanisms ... discarded by the receiving router, prior to sending the information to the receiving router. 4-4 Large- Scale MPLS VPN Deployment Copyright 2000, Cisco Systems, Inc. Partitioned Route Reflectors ... Questions n Describe BGP scaling issues in a MPLS VPN network. The number of routes in a very large MPLS/VPN network may result in exceeding the resources of the PE routers. MPLS VPN uses...
... 4 Large- Scale MPLS VPN Deployment 4-2 Large- Scale MPLS VPN Deployment Copyright 2000, Cisco Systems, Inc. MP-BGP Scalability ... updates by uploading a filter to the neighbor. n Why are outbound route filters useful? 4-4 Large- Scale MPLS VPN Deployment Copyright 2000, Cisco Systems, Inc. Partitioned Route Reflectors ... Questions n Describe BGP scaling issues in a MPLS VPN network. The number of routes in a very large MPLS/VPN network may result in exceeding the resources of the PE routers. MPLS VPN uses...
... overthem. 6.1 Future WorkA large- scale web search engine is a complex system and much remains to be done. Our immediategoals are to improve search efficiency and to scale to approximately 100 ... research activities on large- scale web data. To support novel research uses, Google stores all of the actual documents it crawlsin compressed form. One of our main goals in designing Google was ... operating system robustness. In designing Google,we have considered both the rate of growth of the Web and technological changes. Google is designed to scale well to extremely large data sets. It makes...
... Conditions for Large- Scale Impulsive Dynamical Systems 24910.5 Specialization to Large- Scale Linear Impulsive DynamicalSystems 25910.6 Stability of Feedback Interconnections of Large- Scale Im-pulsive ... thermodynamic large- scale system necessarilyleads to nonconservation of ectropy and entropy. In addition, using the sys-tem ectropy as a Lyapunov function candidate, we show that our large- scale thermodynamic ... Introduction 30513.2 Hybrid Decentralized Control and Large- Scale ImpulsiveDynamical Systems 30613.3 Hybrid Decentralized Control for Large- Scale Dynamical Systems 31313.4 Interconnected Euler-Lagrange...
... Erin Duggan May 31, 2012 212-335-9400 DA VANCE: ABACUS BANK AND 19 INDIVIDUALS CHARGED IN LARGE- SCALE MORTGAGE FRAUD CONSPIRACY Employees and Managers Charged With Routinely Submitting False...
... documents into larger files when storingthem in HDFS. We found this improved Hadoop’s performance bya factor of two and helped avoid memory issues with the centralHDFS master when a large number ... are two notableprojects in this direction.3.4 Data DistributionThe conventional wisdom for large- scale databases is to alwayssend the computation to the data, rather than the other way around.In ... SQLDBMS from a major relational database vendor that stores data inA Comparison of Approaches to Large- Scale Data AnalysisAndrew Pavlo Erik Paulson Alexander RasinBrown University University of...
... presents Scribe, a large- scale event notification infrastruc-ture for topic-based publish-subscribe applications. Scribe supports large num-bers of topics, with a potentially large number of subscribers ... network can scale to an extremely large number of nodesbecause the algorithms to build and maintain the network have space and time costs of. This enables support for extremely large groups ... a large- scale and fully decentralized event notification sys-tem built on top of Pastry, a peer-to-peer object location and routing substrate overlayedon the Internet. Scribe is designed to scale...
... promise of large- scale discriminative training for SMT is to scale toarbitrary types and numbers of features and to pro-vide sufficient statistical support by parameter esti-mation on large sample ... 2005):∇lj(w) =−¯xjif w, ¯xj ≤ 0,0 else.Our baseline algorithm 1 (SDG) scales pairwiseranking to largescale scenarios. The algorithm takesan average over the final weight updates of ... features vectors grew too large tobe kept in memory.6 DiscussionWe presented an approach to scaling discrimina-tive learning for SMT not only to large featuresets but also to large sets of parallel...
... modeling. Computational Linguistics.Ming Tan, Wenli Zhou, Lei Zheng, and Shaojun Wang.2011. A largescale distributed syntactic, semanticand lexical language model for machine translation.In ... 959–968,Jeju, Republic of Korea, 8-14 July 2012.c2012 Association for Computational Linguistics Large- Scale Syntactic Language Modeling with TreeletsAdam Pauls Dan KleinComputer Science DivisionUniversity ... standard binary classification accuracy.each training sentence, we can very easily scale our model to much larger amounts of data. In Ta-ble 4, we also show the performance of the gener-ative...
... on giant corpora many orders of mag-nitude larger than previously used, they do lay outhow AL might be useful to apply to acquire datato augment a large set cheaply because they rec-ognize ... machineand it might be better to provide new training datain a more gradual manner. A sentence with large #s of unseen words is likely to get word-alignedincorrectly and then learning from that translationcould ... for a translationof only the trigger words, we expect to be able tocircumvent this problem in large part.The next section presents the results of experi-ments that show that the HNG algorithm...
... first work of building acomplex largescale distributed language model witha principled approach that is more powerful than n-grams when both trained on a very large corpus withup to a billion ... SEMANTIZER oftest document. The m-SLM performs competitivelywith its counterpart n-gram (n=m+1) on large scale corpus. In Table 3, for composite n-gram/m-SLMmodel (n = 3, m = 2 and n = 4, m = 3) trainedon ... very large corpora to train our compos-ite language model, both the data and the parameterscan’t be stored in a single machine, so we have toresort to distributed computing. The topic of large scale...
... en-tries from a large amount of dependency relationsin Web documents. To our knowledge, no one elsehas performed this type of clustering on such a large scale. Wikipedia also produced a large gazetteerof ... clustering with a vocabularythat is large enough to cover the many named entitiesrequired to improve the accuracy of NER is difficult.We enabled such large- scale clustering by paralleliz-ing ... Association for Computational LinguisticsInducing Gazetteers for Named Entity Recognitionby Large- scale Clustering of Dependency RelationsJun’ichi KazamaJapan Advanced Institute ofScience...
... many identicalsentences. We address this weakness of co-selectionEvaluation challenges in large- scale document summarizationDragomir R. RadevU. of Michiganradev@umich.eduWai LamChinese ... Michiganhqi@umich.eduElliott DrabekJohns Hopkins U.edrabek@cs.jhu.eduAbstractWe present a large- scale meta evaluationof eight evaluation measures for bothsingle-document and multi-documentsummarizers. ... summa-rization in a standard and inexpensive way is a diffi-cult task (Mani et al., 2001). Traditional large- scale evaluations are either too simplistic (using measureslike precision, recall, and percent...
... integrated these largescale linguistic resources into our natural language understanding system. Client- server architecture was used to make a large volume of lexical information and a large knowledge ... Server data with core KB (WordNet-based KB concept names from ISI see text) 984 Integration of Large- Scale Linguistic Resources in a Natural Language Understanding System Lewis M. Norton, Deborah ... acquisition is a serious bottleneck for natural language understanding systems. For this reason, large- scale linguistic resources have been compiled and made available by organizations such as the...