3 papers
cs.LG2025
DistShap: Scalable GNN Explanations with Distributed Shapley Values
Selahattin Akkas, Aditya Devarakonda, Ariful Azad
With the growing adoption of graph neural networks (GNNs), explaining their predictions has become increasingly important. However, attributing predictions to specific edges or fea…
cs.DC2025
Communication-Efficient, 2D Parallel Stochastic Gradient Descent for Distributed-Memory Optimization
Aditya Devarakonda, Ramakrishnan Kannan
Distributed-memory implementations of numerical optimization algorithm, such as stochastic gradient descent (SGD), require interprocessor communication at every iteration of the al…
cs.DC2023
Sequential and Shared-Memory Parallel Algorithms for Partitioned Local Depths
Aditya Devarakonda, Grey Ballard
In this work, we design, analyze, and optimize sequential and shared-memory parallel algorithms for partitioned local depths (PaLD). Given a set of data points and pairwise distanc…