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CORR
2010
Springer
177views Education» more  CORR 2010»
14 years 10 months ago
Supervised Random Walks: Predicting and Recommending Links in Social Networks
Predicting the occurrence of links is a fundamental problem in networks. In the link prediction problem we are given a snapshot of a network and would like to infer which interact...
Lars Backstrom, Jure Leskovec
TC
2008
14 years 9 months ago
The Convergence-Guaranteed Random Walk and Its Applications in Peer-to-Peer Networks
Network structure construction and global state maintenance are expensive in large-scale, dynamic peer-to-peer (p2p) networks. With inherent topology independence and low state mai...
Ming Zhong, Kai Shen, Joel I. Seiferas
ICASSP
2011
IEEE
14 years 1 months ago
Langevin and hessian with fisher approximation stochastic sampling for parameter estimation of structured covariance
We have studied two efficient sampling methods, Langevin and Hessian adapted Metropolis Hastings (MH), applied to a parameter estimation problem of the mathematical model (Lorent...
Cornelia Vacar, Jean-François Giovannelli, ...
KDD
2010
ACM
252views Data Mining» more  KDD 2010»
15 years 1 months ago
Fast query execution for retrieval models based on path-constrained random walks
Many recommendation and retrieval tasks can be represented as proximity queries on a labeled directed graph, with typed nodes representing documents, terms, and metadata, and labe...
Ni Lao, William W. Cohen
ICML
2008
IEEE
15 years 10 months ago
Fast incremental proximity search in large graphs
In this paper we investigate two aspects of ranking problems on large graphs. First, we augment the deterministic pruning algorithm in Sarkar and Moore (2007) with sampling techni...
Purnamrita Sarkar, Andrew W. Moore, Amit Prakash