secretflow/spu
Apr 2025 – Apr 2025
1 Month active
Languages Used
BazelPython
Technical Skills
BazelDimensionality ReductionGraph AlgorithmsMachine LearningPythonSecure Multi-Party Computation (MPC)
cpz2024
PROFILE
Cpz2024
In April 2025, this developer delivered privacy-preserving graph and manifold learning modules for the secretflow/spu repository, focusing on secure analytics for enterprise environments. They implemented Dijkstra’s algorithm, Isomap, and Spectral Embedding, along with a privacy-preserving variant of Floyd-Warshall, enabling dimensionality reduction and graph analysis without compromising sensitive data. The work leveraged Python and Bazel, integrating secure multi-party computation techniques to ensure privacy guarantees. Comprehensive end-to-end tests and emulations were added to validate both correctness and privacy, demonstrating a deep understanding of secure machine learning workflows. The contribution addressed privacy requirements while maintaining performance and integration standards.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
1,531
Activity Months1
Your Network
27 peopleSame Organization
@mail.nankai.edu.cn4
Work History
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025 — Delivered privacy-preserving graph and manifold learning capabilities in secretflow/spu, with new modules for Dijkstra, Isomap, and Spectral Embedding, alongside a privacy-preserving Floyd-Warshall variant. Implemented end-to-end tests and emulations to verify privacy guarantees. Focused on enabling secure graph analytics with enterprise-grade privacy.
1 Commits • 1 Features
Apr 1, 2025April 2025 — Delivered privacy-preserving graph and manifold learning capabilities in secretflow/spu, with new modules for Dijkstra, Isomap, and Spectral Embedding, alongside a privacy-preserving Floyd-Warshall variant. Implemented end-to-end tests and emulations to verify privacy guarantees. Focused on enabling secure graph analytics with enterprise-grade privacy.
April 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance60.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
BazelPython
Technical Skills
BazelDimensionality ReductionGraph AlgorithmsMachine LearningPythonSecure Multi-Party Computation (MPC)
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