Datasets often incorporate various functional patterns related to different aspects or regimes, which are typically not equally present throughout the dataset. We propose a novel partitioning ...
The art of finding patterns or communities plays a central role in the analysis of structured data such as networks. Community detection in graphs has become a field on its own. Real-world networks, ...
Differential privacy (DP) stands as the gold standard for protecting user information in large-scale machine learning and data analytics. A critical task within DP is partition selection—the process ...
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BingoCGN employs cross-partition message quantization to summarize inter-partition message flow, which eliminates the need for irregular off-chip memory access and utilizes a fine-grained structured ...
Genomics is playing an important role in transforming healthcare. Genetic data, however, is being produced at a rate that far outpaces Moore’s Law. Many efforts have been made to accelerate genomics ...
Dynamic programming (DP), first introduced by Richard Bellman in the 1950s, is a fundamental algorithmic technique in computer science with broad applicability across numerous domains. In ...
Abstract: As the processing of large-scale graphs on a single device is infeasible without partitioning, graph partitioning algorithms are essential for various algorithms and distributed computing ...