114 citations · 170 across the 17 of their papers we have counts for
17 papers
SWIFT: Scalable Wasserstein Factorization for Sparse Nonnegative Tensors
Ardavan Afshar, Kejing Yin, Sherry Yan +4
Existing tensor factorization methods assume that the input tensor follows some specific distribution (i.e. Poisson, Bernoulli, and Gaussian), and solve the factorization by minimi…
An Alternating Rank-K Nonnegative Least Squares Framework (ARkNLS) for Nonnegative Matrix Factorization
Delin Chu, Wenya Shi, Srinivas Eswar +1
Nonnegative matrix factorization (NMF) is a prominent technique for data dimensionality reduction that has been widely used for text mining, computer vision, pattern discovery, and…
Hypergraph Random Walks, Laplacians, and Clustering
Koby Hayashi, Sinan G. Aksoy, Cheong Hee Park +1
We propose a flexible framework for clustering hypergraph-structured data based on recently proposed random walks utilizing edge-dependent vertex weights. When incorporating edge-d…
TASTE: Temporal and Static Tensor Factorization for Phenotyping Electronic Health Records
Ardavan Afshar, Ioakeim Perros, Haesun Park +5
Phenotyping electronic health records (EHR) focuses on defining meaningful patient groups (e.g., heart failure group and diabetes group) and identifying the temporal evolution of p…
PLANC: Parallel Low Rank Approximation with Non-negativity Constraints
Srinivas Eswar, Koby Hayashi, Grey Ballard +3
We consider the problem of low-rank approximation of massive dense non-negative tensor data, for example to discover latent patterns in video and imaging applications. As the size…
TopicSifter: Interactive Search Space Reduction Through Targeted Topic Modeling
Hannah Kim, Dongjin Choi, Barry Drake +2
Topic modeling is commonly used to analyze and understand large document collections. However, in practice, users want to focus on specific aspects or "targets" rather than the ent…