9,440 research outputs found
G-Rank: Unsupervised Continuous Learn-to-Rank for Edge Devices in a P2P Network
No full textRanking algorithms in traditional search engines are powered by enormous training data sets that are meticulously engineered and curated by a centralized entity. Decentralized peer-to-peer (p2p) networks such as torrenting applications and Web3 protocols deliberately eschew centralized databases and computational architectures when designing services and features. As such, robust search-and-rank algorithms designed for such domains must be engineered specifically for decentralized networks, and must be lightweight enough to operate on consumer-grade personal devices such as a smartphone or laptop computer. We introduce G-Rank, an unsupervised ranking algorithm designed exclusively for decentralized networks. We demonstrate that accurate, relevant ranking results can be achieved in fully decentralized networks without any centralized data aggregation, feature engineering, or model training. Furthermore, we show that such results are obtainable with minimal data preprocessing and computational overhead, and can still return highly relevant results even when a user’s device is disconnected from the network. G-Rank is highly modular in design, is not limited to categorical data, and can be implemented in a variety of domains with minimal modification. The results herein show that unsupervised ranking models designed for decentralized p2p networks are not only viable, but worthy of further research.https://github.com/awrgold/G-RankComputer Scienc
A solver for clustered low-rank SDPs arising from multivariate polynomial (matrix) programs
No full textIn this thesis, we give a primal-dual interior point method specialized to clustered low-rank semidefinite programs. We introduce multivariate polynomial matrix programs, and we reduce these to clustered low-rank semidefinite programs. This extends the work of Simmons-Duffin [J. High Energ. Phys. 1506, no. 174 (2015)] from univariate to multivariate polynomial matrix programs, and to more general clustered low-rank semidefinite programs. Clustered low-rank semidefinite programs are programs with low-rank constraint matrices where the positive semidefinite variables are only used within clusters of constraints. The free variables can be used in any constraint, and can be used to connect clusters. The solver uses this structure to speed up the computations in two ways. First, the low rank structure is used to reduce matrix products to products of the form uT M v, where M is a matrix and u and v are vectors, as already suggested by Löfberg and Parrilo in [43rd IEEE CDC (2004)]. Second, an additional block-diagonal structure is introduced due to the clusters. This gives the possibility to do operations such as the Cholesky decomposition block-wise. We apply this to sphere packing and spherical cap packing. For sphere packing, the speed of the solver is compared to the often used arbitrary precision solver SDPA-GMP, showing the theoretical speedup in time complexity. We give a new three-point bound for the maximum density when packing spherical caps of sizes on the unit sphere. https://github.com/nanleij/Clustered-Low-Rank-SDP-solver Repository link Github repository with the Julia code of the solverApplied Mathematics | Optimizatio
Pool Adjacent Violators Based Biometric Rank Level Fusion
No full textWe propose a new method in rank level fusion for biometric identification. Our method is based on the pool adjacent violators (PAV) algorithm after the ranks have been transformed to the approximated scores.We then show that our method outperforms various approaches that commonly used in biometric rank level fusion on NIST BSSR1 multimodal database
Reduced-rank adaptive least bit-error-rate detection in hybrid direct-sequence time-hopping ultrawide bandwidth systems
No full textDesign of high-efficiency low-complexity detection schemes for ultrawide bandwidth (UWB) systems is highly challenging. This contribution proposes a reduced-rank adaptive multiuser detection (MUD) scheme operated in least bit-errorrate (LBER) principles for the hybrid direct-sequence timehopping UWB (DS-TH UWB) systems. The principal component analysis (PCA)-assisted rank-reduction technique is employed to obtain a detection subspace, where the reduced-rank adaptive LBER-MUD is carried out. The reduced-rank adaptive LBERMUD is free from channel estimation and does not require the knowledge about the number of resolvable multipaths as well as the knowledge about the multipaths’ strength. In this contribution, the BER performance of the hybrid DS-TH UWB systems using the proposed detection scheme is investigated, when assuming communications over UWB channels modeled by the Saleh-Valenzuela (S-V) channel model. Our studies and performance results show that, given a reasonable rank of the detection subspace, the reduced-rank adaptive LBER-MUD is capable of efficiently mitigating the multiuser interference (MUI) and inter-symbol interference (ISI), and achieving the diversity gain promised by the UWB systems
Aggregation and Other Biases in the Calculation of Consumer Elasticities for Models of Arbitrary Rank
No full textConsumer-related policy decisions often require analysis of aggregate responses or mean elasticities. However, in practice these mean elasticities are seldom used. Mean elasticities can be approximated using aggregate data, but that introduces aggregation bias for full and compensated price elasticities, though interestingly not for expenditure elasticities. The biases corresponding to incorrect approximations of mean elasticities depend on the type of data (micro or aggregate), the type and rank of the model, and generalized measures of income inequality. These biases are distinct from the biases (already noted in the literature) when using aggregate data to estimate micro elasticites at mean income.Aggregate price and expenditure elasticities, aggregation bias, consumer demand, generalized measures of income inequality, income distribution
SMM906590 Supplemental Material - Supplemental material for An improved one-sample log-rank test
No full textSupplemental material, SMM906590 Supplemental Material for An improved one-sample log-rank test by Laura Kerschke, Andreas Faldum and Rene Schmidt in Statistical Methods in Medical Research</p
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Integer-empty polytopes in the 0/1-cube with maximal Gomory–Chvátal rank
No full textWe provide a complete characterization of all polytopes P⊆[0,1]nP⊆[0,1][superscript n] with empty integer hulls, whose Gomory–Chvátal rank is n (and, therefore, maximal). In particular, we show that the first Gomory–Chvátal closure of all these polytopes is identical
Matrix semigroups with commutable rank
No full textWe focus on matrix semigroups (and algebras) on which rank is commutable [rank(AB) = rank(BA)]. It is shown that in a number of cases (for example, in dimensions less than 6), but not always, commutativity of rank entails permutability of rank [rank(A(1)A(2)...A(n)) = rank(A(sigma(1))A(sigma(2))... A(sigma(n)))]. It is shown that a commutable-rank semigroup has a natural decomposition as a semi-lattice of semigroups that have a simpler structure. While it is still unknown whether commutativity of rank entails permutability of rank for algebras, the question is reduced to the case of algebras of nilpotents.PT: J; CR: ANDERSON FW, 1992, GRADUATE TEXTS MATH ANDO T, 1987, LINEAR ALGEBRA APPL, V90, P165 GANTMACHER FR, 1937, COMPOS MATH, P445 HORN RA, 1990, MATRIX ANAL LEVITZKI J, 1931, MATH ANN, V105, P620 LIVSHITS L, 1998, J OPERAT THEOR, V40, P35 OKNINSKI J, 1998, SERIES ALGEBRA, V6 PRASOLOV VV, 1994, PROBLEMS THEOREMS LI RADJAVI H, 2000, SIMULTANEOUS TRIANGU WHITNEY AM, 1952, J ANAL MATH, V2, P88; NR: 10; TC: 1; J9: SEMIGROUP FORUM; PG: 29; GA: 698NQSource type: Electronic(1
Management of chronic immune thrombocytopenic purpura: targeting insufficient megakaryopoiesis as a novel therapeutic principle
No full textAndreas Rank, Oliver Weigert, Helmut OstermannMedizinische Klinik III &ndash; Grosshadern, Klinikum der Ludwig Maximilians-Universitaet Munich, Munich, GermanyAbstract: Traditionally, anti-platelet autoantibodies accelerating platelet clearance from the peripheral circulation have been recognized as the primary pathopysiological mechanism in chronic immune thrombocytopenia (ITP). Recently, increasing evidence supports the co-existence of insufficient megakaryopoiesis. Inadequate low thrombopoietin (TPO) levels are associated with insufficient proliferation and differentiation of megakaryocytes, decreased proplatelet formation, and subsequent platelet release. Recently two novel activators of TPO receptors have been made available: romiplostim and eltrombopag. In several phase III studies, both agents demonstrated increase of platelet counts in about 80% of chronic ITP patients within 2 to 3 weeks. These agents substantially broaden the therapeutic options for patients with chronic ITP although long-term results are still pending. This review will provide an update on the current conception of underlying mechanisms in ITP and novel, pathophysiologically based treatment options.Keywords: immune thrombocytopenia, romiplostim, eltrombopag, megakaryopoiesi
- …
