4 citations · 7 across the 6 of their papers we have counts for
6 papers
An Efficient Sparse Kernel Generator for O(3)-Equivariant Deep Networks
Vivek Bharadwaj, Austin Glover, Aydin Buluc +1
Rotation equivariant graph neural networks, i.e. networks designed to guarantee certain geometric relations between their inputs and outputs, yield state of the art performance on…
Efficient Leverage Score Sampling for Tensor Train Decomposition
Vivek Bharadwaj, Beheshteh T. Rakhshan, Osman Asif Malik +1
Tensor Train~(TT) decomposition is widely used in the machine learning and quantum physics communities as a popular tool to efficiently compress high-dimensional tensor data. In th…
Fast Exact Leverage Score Sampling from Khatri-Rao Products with Applications to Tensor Decomposition
Vivek Bharadwaj, Osman Asif Malik, Riley Murray +3
We present a data structure to randomly sample rows from the Khatri-Rao product of several matrices according to the exact distribution of its leverage scores. Our proposed sampler…
Sampling-Based Decomposition Algorithms for Arbitrary Tensor Networks
Osman Asif Malik, Vivek Bharadwaj, Riley Murray
We show how to develop sampling-based alternating least squares (ALS) algorithms for decomposition of tensors into any tensor network (TN) format. Provided the TN format satisfies…
Distributed-Memory Randomized Algorithms for Sparse Tensor CP Decomposition
Vivek Bharadwaj, Osman Asif Malik, Riley Murray +2
Candecomp / PARAFAC (CP) decomposition, a generalization of the matrix singular value decomposition to higher-dimensional tensors, is a popular tool for analyzing multidimensional…
Distributed-Memory Sparse Kernels for Machine Learning
Vivek Bharadwaj, Aydin Buluç, James Demmel
Sampled Dense Times Dense Matrix Multiplication (SDDMM) and Sparse Times Dense Matrix Multiplication (SpMM) appear in diverse settings, such as collaborative filtering, document cl…