Media Summary: MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018 Instructor: Gilbert Strang ... DISC 2021 — 35th International Symposium on Distributed Computing [VLDB 2022] Theoretically and Practically Efficient Parallel Nucleus Decomposition

Parallel Efficient Clustering With Graph - Detailed Analysis & Overview

MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018 Instructor: Gilbert Strang ... DISC 2021 — 35th International Symposium on Distributed Computing [VLDB 2022] Theoretically and Practically Efficient Parallel Nucleus Decomposition Authors: Renchi Yang, Jieming Shi, Yin Yang, Keke Huang, Shiqi Zhang, Xiaokui Xiao. Table of Contents (powered by 0:00:00 [Talk: Authors: Kengo Nakajima (the University of Tokyo), Balazs Gerofi (RIKEN R-CCS), Yutaka Ishikawa (RIKEN R-CCS), Masashi ...

James Lewis, Systap This demonstration will demonstrate our work on scalable and high performance BFS on GPU A 5 minute talk on my paper with Peter and Gregory for ICML 2026. I'll add links to the ICML page and Github repo once they are ... In this video from PASC18, Tristan Konolige from the University of Colorado Boulder presents: A

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Parallel Efficient Clustering with Graph-Based Approximate Nearest Neighbor Search
PAKDD-2020 Fast Clustering With Graph Sparsification
35. Finding Clusters in Graphs
Massively Parallel Correlation Clustering in Bounded Arboricity Graphs
[SIGMOD 2021]Parallel Index Based Structural Graph Clustering and Its Approximation
[VLDB 2022] Theoretically and Practically Efficient Parallel Nucleus Decomposition
Fast Parallel Algorithms for Euclidean MST and Hierarchical Spatial Clustering (SIGMOD'21)
Pruned Pivot: Correlation Clustering Algorithm for Dynamic, Parallel, andLocal Computation Models
Effective and Scalable Clustering on Massive Attributed Graphs
Effective and Efficient Clustering Methods for Correlated Probabilistic Graphs
511 Efficient Structural Clustering in Large Uncertain Graphs
PA_10:  Guest Lecture by Julian Shun - Parallel Algorithms for Density-Based + Structural Clustering
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Parallel Efficient Clustering with Graph-Based Approximate Nearest Neighbor Search

Parallel Efficient Clustering with Graph-Based Approximate Nearest Neighbor Search

Julian Shun (MIT) https://simons.berkeley.edu/talks/julian-shun-mit-2025-10-20 Managing

PAKDD-2020 Fast Clustering With Graph Sparsification

PAKDD-2020 Fast Clustering With Graph Sparsification

Are you interested in spectral

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35. Finding Clusters in Graphs

35. Finding Clusters in Graphs

MIT 18.065 Matrix Methods in Data Analysis, Signal Processing, and Machine Learning, Spring 2018 Instructor: Gilbert Strang ...

Massively Parallel Correlation Clustering in Bounded Arboricity Graphs

Massively Parallel Correlation Clustering in Bounded Arboricity Graphs

DISC 2021 — 35th International Symposium on Distributed Computing http://www.disc-conference.org/wp/disc2021/

[SIGMOD 2021]Parallel Index Based Structural Graph Clustering and Its Approximation

[SIGMOD 2021]Parallel Index Based Structural Graph Clustering and Its Approximation

SIGMOD 2021.

Sponsored
[VLDB 2022] Theoretically and Practically Efficient Parallel Nucleus Decomposition

[VLDB 2022] Theoretically and Practically Efficient Parallel Nucleus Decomposition

[VLDB 2022] Theoretically and Practically Efficient Parallel Nucleus Decomposition

Fast Parallel Algorithms for Euclidean MST and Hierarchical Spatial Clustering (SIGMOD'21)

Fast Parallel Algorithms for Euclidean MST and Hierarchical Spatial Clustering (SIGMOD'21)

Paper: https://arxiv.org/pdf/2104.01126.pdf This paper presents new

Pruned Pivot: Correlation Clustering Algorithm for Dynamic, Parallel, andLocal Computation Models

Pruned Pivot: Correlation Clustering Algorithm for Dynamic, Parallel, andLocal Computation Models

Given a

Effective and Scalable Clustering on Massive Attributed Graphs

Effective and Scalable Clustering on Massive Attributed Graphs

Authors: Renchi Yang, Jieming Shi, Yin Yang, Keke Huang, Shiqi Zhang, Xiaokui Xiao.

Effective and Efficient Clustering Methods for Correlated Probabilistic Graphs

Effective and Efficient Clustering Methods for Correlated Probabilistic Graphs

Recently, probabilistic

511 Efficient Structural Clustering in Large Uncertain Graphs

511 Efficient Structural Clustering in Large Uncertain Graphs

Table of Contents (powered by https://videoken.com) 0:00:00 [Talk:

PA_10:  Guest Lecture by Julian Shun - Parallel Algorithms for Density-Based + Structural Clustering

PA_10: Guest Lecture by Julian Shun - Parallel Algorithms for Density-Based + Structural Clustering

... about directly

Efficient Data-Parallel Computing on Small Heterogeneous Clusters

Efficient Data-Parallel Computing on Small Heterogeneous Clusters

Cluster

Efficient Parallel Multigrid Method on Intel Xeon Phi Clusters

Efficient Parallel Multigrid Method on Intel Xeon Phi Clusters

Authors: Kengo Nakajima (the University of Tokyo), Balazs Gerofi (RIKEN R-CCS), Yutaka Ishikawa (RIKEN R-CCS), Masashi ...

Using MVAPICH for Multi-GPU Data Parallel Graph Analytics

Using MVAPICH for Multi-GPU Data Parallel Graph Analytics

James Lewis, Systap This demonstration will demonstrate our work on scalable and high performance BFS on GPU

Dynamic Coreset Spectral Clustering (ICML 2026)

Dynamic Coreset Spectral Clustering (ICML 2026)

A 5 minute talk on my paper with Peter and Gregory for ICML 2026. I'll add links to the ICML page and Github repo once they are ...

BID23 - Efficiently Processing Massive Graphs using Commodity Multicore Machines, Laxman Dhulipala

BID23 - Efficiently Processing Massive Graphs using Commodity Multicore Machines, Laxman Dhulipala

Processing large

A Parallel Solver for Graph Laplacians

A Parallel Solver for Graph Laplacians

In this video from PASC18, Tristan Konolige from the University of Colorado Boulder presents: A

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