Page Summary: [VLDB 2022] Theoretically and Practically Efficient Parallel Nucleus Decomposition [VLDB 2021] Scalable Community Detection via Parallel Correlation Clustering

Vldb 2022 Theoretically And Practically Efficient Parallel Nucleus Decomposition -

[VLDB 2022] Theoretically and Practically Efficient Parallel Nucleus Decomposition [VLDB 2021] Scalable Community Detection via Parallel Correlation Clustering UDO is the Swiss Army knife of database optimizer tools: it optimizes index selections, tunes system parameters, and picks ...

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  • [VLDB 2022] Theoretically and Practically Efficient Parallel Nucleus Decomposition
  • [VLDB 2021] Scalable Community Detection via Parallel Correlation Clustering
  • UDO is the Swiss Army knife of database optimizer tools: it optimizes index selections, tunes system parameters, and picks ...
  • The Systems Group at ETH Channel presents the Systems Group research through various short research profile videos.

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[VLDB 2022] Theoretically and Practically Efficient Parallel Nucleus Decomposition
Jessica Shi - MIT - Theoretically and Practically Efficient Parallel Nucleus Decomposition
VLDB 2022 - Correlation Detective
[ICDE 2022]Nucleus Decomposition in Probabilistic Graphs: Hardness and Algorithms
The Prefix Filter: Practically and Theoretically Better Than Bloom. VLDB 2022
Modin Talk, VLDB'22
VLDB 2022: Modularis: Modular Relational Analytics over Heterogeneous Distributed Platforms
[VLDB 2021] Scalable Community Detection via Parallel Correlation Clustering
VLDB 2022 Sydney:  Dynamic Spanning Trees for Connectivity Queries onFully-dynamic Undirected Graphs
UDO: Universal Database Optimizer (VLDB'22)
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[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

Jessica Shi - MIT - Theoretically and Practically Efficient Parallel Nucleus Decomposition

Jessica Shi - MIT - Theoretically and Practically Efficient Parallel Nucleus Decomposition

Read more details and related context about Jessica Shi - MIT - Theoretically and Practically Efficient Parallel Nucleus Decomposition.

VLDB 2022 - Correlation Detective

VLDB 2022 - Correlation Detective

Read more details and related context about VLDB 2022 - Correlation Detective.

[ICDE 2022]Nucleus Decomposition in Probabilistic Graphs: Hardness and Algorithms

[ICDE 2022]Nucleus Decomposition in Probabilistic Graphs: Hardness and Algorithms

Read more details and related context about [ICDE 2022]Nucleus Decomposition in Probabilistic Graphs: Hardness and Algorithms.

The Prefix Filter: Practically and Theoretically Better Than Bloom. VLDB 2022

The Prefix Filter: Practically and Theoretically Better Than Bloom. VLDB 2022

Short talk by Tomer Even about the Prefix Filter. Joint work with Guy Even and Adam Morrison. This paper was presented in

Modin Talk, VLDB'22

Modin Talk, VLDB'22

Read more details and related context about Modin Talk, VLDB'22.

VLDB 2022: Modularis: Modular Relational Analytics over Heterogeneous Distributed Platforms

VLDB 2022: Modularis: Modular Relational Analytics over Heterogeneous Distributed Platforms

The Systems Group at ETH Channel presents the Systems Group research through various short research profile videos.

[VLDB 2021] Scalable Community Detection via Parallel Correlation Clustering

[VLDB 2021] Scalable Community Detection via Parallel Correlation Clustering

[VLDB 2021] Scalable Community Detection via Parallel Correlation Clustering

VLDB 2022 Sydney:  Dynamic Spanning Trees for Connectivity Queries onFully-dynamic Undirected Graphs

VLDB 2022 Sydney: Dynamic Spanning Trees for Connectivity Queries onFully-dynamic Undirected Graphs

Read more details and related context about VLDB 2022 Sydney: Dynamic Spanning Trees for Connectivity Queries onFully-dynamic Undirected Graphs.

UDO: Universal Database Optimizer (VLDB'22)

UDO: Universal Database Optimizer (VLDB'22)

UDO is the Swiss Army knife of database optimizer tools: it optimizes index selections, tunes system parameters, and picks ...