410 citations · 713 across the 33 of their papers we have counts for
5 papers · 1 filter
Tensor-Tensor Products for Optimal Representation and Compression
Misha Kilmer, Lior Horesh, Haim Avron +1
In this era of big data, data analytics and machine learning, it is imperative to find ways to compress large data sets such that intrinsic features necessary for subsequent analys…
An Inner-Outer Iterative Method for Edge Preservation in Image Restoration and Reconstruction
Silvia Gazzola, Misha E. Kilmer, James G. Nagy +2
We present a new inner-outer iterative algorithm for edge enhancement in imaging problems. At each outer iteration, we formulate a Tikhonov-regularized problem where the penalizati…
Dynamic Graph Convolutional Networks Using the Tensor M-Product
Osman Asif Malik, Shashanka Ubaru, Lior Horesh +2
Many irregular domains such as social networks, financial transactions, neuron connections, and natural language constructs are represented using graph structures. In recent years,…
Non-negative Tensor Patch Dictionary Approaches for Image Compression and Deblurring Applications
Elizabeth Newman, Misha E. Kilmer
In recent work (Soltani, Kilmer, Hansen, BIT 2016), an algorithm for non-negative tensor patch dictionary learning in the context of X-ray CT imaging and based on a tensor-tensor p…
Randomized algorithms for low-rank tensor decompositions in the Tucker format
Rachel Minster, Arvind K. Saibaba, Misha E. Kilmer
Many applications in data science and scientific computing involve large-scale datasets that are expensive to store and compute with, but can be efficiently compressed and stored i…