Recovering latent time-series from their observed sums: network tomography with particle filters.

No abstract is available for this paper.

• Publication year

  2004

• Venue

  Knowledge Discovery and Data Mining

• Publication date

  2004-08-22

• Fields of study

  Computer Science, Engineering

• Identifiers
  DOI 10.1145/1014052.1014059
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Monte Carlo Statistical Methods

  2005cited by this paper
• Monte Carlo Statistical Methods

  2004cited by this paper
• Real-time problem determination in distributed systems using active probing

  2004cited by this paper
• Advances in Network Tomography

  2003influential reference
• Physical topology discovery for large multisubnet networks

  2003cited by this paper
• An information-theoretic approach to traffic matrix estimation

  2003cited by this paper
• Fast accurate computation of large-scale IP traffic matrices from link loads

  2003cited by this paper
• Monte Carlo Strategies in Scientific Computing

  2002cited by this paper
• Continuous-time hidden Markov models for network performance evaluation

  2002cited by this paper
• Iterative Bayesian estimation of network traffic matrices in the case of bursty flows

  2002cited by this paper
• Traffic matrix estimation: existing techniques and new directions

  2002cited by this paper
• Accuracy vs. efficiency trade-offs in probabilistic diagnosis

  2002cited by this paper
• Following a moving target—Monte Carlo inference for dynamic Bayesian models

  2001cited by this paper
• Self organizing Time Series Model

  2001cited by this paper
• Sequential Monte Carlo Methods in Practice

  2001cited by this paper
• The "DGX" distribution for mining massive, skewed data

  2001cited by this paper
• Monte Carlo strategies in scientific computing

  2001cited by this paper
• Time-varying network tomography: router link data

  2000cited by this paper
• An EM Approach to OD Matrix Estimation

  1998cited by this paper
• Bayesian Inference on Network Traffic Using Link Count Data

  1998cited by this paper
• Bayesian Inference on Network Traffic Using Link Count Data: Rejoinder

  1998cited by this paper
• Network Tomography: Estimating Source-Destination Traffic Intensities from Link Data

  1996cited by this paper
• The Geometry of a Two by Two Contingency Table

  1970cited by this paper
• The Geometry of an $r \times c$ Contingency Table

  1968cited by this paper

• Geometrically aware dynamic Markov bases for statistical linear inverse problems

  2020cites this paper
• Predicting traffic volumes and estimating the effects of shocks in massive transportation systems

  2015cites this paper
• Discovering Conservation Rules

  2014cites this paper
• Origin-Destination Estimator Based on Hidden Markov Models for Adaptive Traffic Control

  2012cites this paper
• Scalable Similarity Matching in Streaming Time Series

  2012influential citation
• Estimating Latent Processes on a Network From Indirect Measurements

  2012cites this paper
• Discovering Conservation Rules

  2012cites this paper
• Deconvolution of mixing time series on a graph

  2011cites this paper
• Polytope samplers for inference in ill-posed inverse problems

  2011cites this paper
• A fast approximation strategy for summarizing a set of streaming time series

  2010cites this paper
• Topology Inference Based on Network Tomography

  2010cites this paper
• Extraction de motifs séquentiels dans les flux de données. (Sequential patterns mining from data streams)

  2009cites this paper
• Extraction de motifs séquentiels dans les flux de données. (Sequential patterns mining from data streams)

  2009cites this paper
• Discovery of Latent Patterns with Hierarchical Bayesian Mixed-Membership Models and the Issue of Model Choice

  2008cites this paper
• A Recurrent Neural Network approach to traffic matrix tracking using partial measurements

  2008cites this paper
• Data Mining Patterns: New Methods and Applications

  2007cites this paper
• Hierarchical Bayesian Mixed-Membership Models and Latent Pattern Discovery

  2006cites this paper
• Bayesian mixed-membership models of complex and evolving networks

  2006cites this paper
• Discovering Latent Patterns with Hierarchical Bayesian Mixed-Membership Models

  2006cites this paper