1.7k citations · 1.8k across the 76 of their papers we have counts for
10 papers · 2 filters
The core consistency of a compressed tensor
Georgios Tsitsikas, Evangelos E. Papalexakis
Tensor decomposition on big data has attracted significant attention recently. Among the most popular methods is a class of algorithms that leverages compression in order to reduce…
Representation Learning by Reconstructing Neighborhoods
Chin-Chia Michael Yeh, Yan Zhu, Evangelos E. Papalexakis +2
Since its introduction, unsupervised representation learning has attracted a lot of attention from the research community, as it is demonstrated to be highly effective and easy-to-…
OCTen: Online Compression-based Tensor Decomposition
Ekta Gujral, Ravdeep Pasricha, Tianxiong Yang +1
Tensor decompositions are powerful tools for large data analytics as they jointly model multiple aspects of data into one framework and enable the discovery of the latent structure…
A Peek Into the Hidden Layers of a Convolutional Neural Network Through a Factorization Lens
Uday Singh Saini, Evangelos E. Papalexakis
Despite their increasing popularity and success in a variety of supervised learning problems, deep neural networks are extremely hard to interpret and debug: Given and already trai…
t-PINE: Tensor-based Predictable and Interpretable Node Embeddings
Saba A. Al-Sayouri, Ekta Gujral, Danai Koutra +2
Graph representations have increasingly grown in popularity during the last years. Existing representation learning approaches explicitly encode network structure. Despite their go…
RECS: Robust Graph Embedding Using Connection Subgraphs
Saba A. Al-Sayouri, Danai Koutra, Evangelos E. Papalexakis +1
The success of graph embeddings or node representation learning in a variety of downstream tasks, such as node classification, link prediction, and recommendation systems, has led…