Distributed Computing
70 papers with code • 0 benchmarks • 1 datasets
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Libraries
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MNIST-8M
Latest papers
Trust Dynamics and Market Behavior in Cryptocurrency: A Comparative Study of Centralized and Decentralized Exchanges
In the evolving landscape of digital finance, the transition from centralized to decentralized trust mechanisms, primarily driven by blockchain technology, plays a critical role in shaping the cryptocurrency ecosystem.
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional Systems
The use of local messages in a graphical model structure ensures that the approach can efficiently handle complex dependence structures.
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
vectorinstitute/flex_model
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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
git-disl/lockdown
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NeurIPS 2023
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
WesleyZhang1991/GCN_rerank
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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.
