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Found 11 papers, 5 papers with code
The Metaverse Data Deluge: What Can We Do About It?
In the Metaverse, the physical space and the virtual space co-exist, and interact simultaneously.
Enhancing Balanced Graph Edge Partition with Effective Local Search
The graph edge partition problem, which is to split the edge set into multiple balanced parts to minimize the total number of copied vertices, has been widely studied from the view of optimization and algorithms.
Efficient Sampling Algorithms for Approximate Temporal Motif Counting (Extended Version)
We first propose a generic edge sampling (ES) algorithm for estimating the number of instances of any temporal motif.
GRMR: Generalized Regret-Minimizing Representatives
Extracting a small subset of representative tuples from a large database is an important task in multi-criteria decision making.
Data Structures and Algorithms Databases
A Fully Dynamic Algorithm for k-Regret Minimizing Sets
Selecting a small set of representatives from a large database is important in many applications such as multi-criteria decision making, web search, and recommendation.
Databases Data Structures and Algorithms
Database Meets Deep Learning: Challenges and Opportunities
Deep learning has recently become very popular on account of its incredible success in many complex data-driven applications, such as image classification and speech recognition.
Coresets for Minimum Enclosing Balls over Sliding Windows
This paper investigates the problem of maintaining a coreset to preserve the minimum enclosing ball (MEB) for a sliding window of points that are continuously updated in a data stream.
Efficient Representative Subset Selection over Sliding Windows
By keeping much fewer checkpoints, KW$^{+}$ achieves higher efficiency than KW while still guaranteeing a $\frac{1-\varepsilon'}{2+2d}$-approximate solution for SMDK.
BLOCKBENCH: A Framework for Analyzing Private Blockchains
However, there is a clear lack of a systematic framework with which different systems can be analyzed and compared against each other.
Databases Cryptography and Security Distributed, Parallel, and Cluster Computing
Real-Time Influence Maximization on Dynamic Social Streams
Influence maximization (IM), which selects a set of $k$ users (called seeds) to maximize the influence spread over a social network, is a fundamental problem in a wide range of applications such as viral marketing and network monitoring.
Social and Information Networks Data Structures and Algorithms
Deep Learning At Scale and At Ease
The other is scalability, that is the deep learning system must be able to provision for a huge demand of computing resources for training large models with massive datasets.
