Distributed Computing
68 papers with code • 0 benchmarks • 1 datasets
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Scalable Agent-Based Modeling for Complex Financial Market Simulations
To the best of our knowledge, this study is the first to implement multiple assets, parallel agent decision-making, a continuous double auction mechanism, and intelligent agent types in a scalable real-time environment.
FlexModel: A Framework for Interpretability of Distributed Large Language Models
With the growth of large language models, now incorporating billions of parameters, the hardware prerequisites for their training and deployment have seen a corresponding increase.
Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training
However, our empirical study shows that traditional pruning-based solution suffers \textit{poison-coupling} effect in FL, which significantly degrades the defense performance. This paper presents Lockdown, an isolated subspace training method to mitigate the poison-coupling effect.
Lockdown: Backdoor Defense for Federated Learning with Isolated Subspace Training
However, our empirical study shows that traditional pruning-based solution suffers \textit{poison-coupling} effect in FL, which significantly degrades the defense performance. This paper presents Lockdown, an isolated subspace training method to mitigate the poison-coupling effect.
Data-Juicer: A One-Stop Data Processing System for Large Language Models
A data recipe is a mixture of data from different sources for training LLMs, which plays a vital role in LLMs' performance.
Distributed bundle adjustment with block-based sparse matrix compression for super large scale datasets
Different from them, we utilize the exact LM algorithm to conduct global bundle adjustment where the formation of the reduced camera system (RCS) is actually parallelized and executed in a distributed way.
Graph Convolution Based Efficient Re-Ranking for Visual Retrieval
In particular, the plain GCR is extended for cross-camera retrieval and an improved feature propagation formulation is presented to leverage affinity relationships across different cameras.
Architectural Vision for Quantum Computing in the Edge-Cloud Continuum
We discuss the necessity, challenges, and solution approaches for extending existing work on classical edge computing to integrate QPUs.
Cooperative Coevolution for Non-Separable Large-Scale Black-Box Optimization: Convergence Analyses and Distributed Accelerations
Given the ubiquity of non-separable optimization problems in real worlds, in this paper we analyze and extend the large-scale version of the well-known cooperative coevolution (CC), a divide-and-conquer black-box optimization framework, on non-separable functions.
fseval: A Benchmarking Framework for Feature Selection and Feature Ranking Algorithms
The package is open source and can be installed through PyPI.