Self-supervised learning on graphs has made large strides in achieving g...
Tensor decompositions have proven to be effective in analyzing the struc...
Many recent breakthroughs in multi-agent reinforcement learning (MARL)
r...
Tools to analyze the latent space of deep neural networks provide a step...
Graphs are one of the most efficacious structures for representing datap...
Can the look and the feel of a website give information about the
trustw...
How can we discover and succinctly summarize the concepts that a neural
...
How can we expand the tensor decomposition to reveal a hierarchical stru...
How can we get a security forum to "tell" us its activities and events o...
Node embeddings have been attracting increasing attention during the pas...
Distinguishing between misinformation and real information is one of the...
Recent studies have demonstrated that machine learning approaches like d...
How can we extract useful information from a security forum? We focus on...
Data collected at very frequent intervals is usually extremely sparse an...
Tensor decomposition on big data has attracted significant attention
rec...
Since its introduction, unsupervised representation learning has attract...
Cross-modal retrieval between visual data and natural language descripti...
Tensor decompositions are powerful tools for large data analytics as the...
Topic discovery has witnessed a significant growth as a field of data mi...
Despite their increasing popularity and success in a variety of supervis...
Graph representations have increasingly grown in popularity during the l...
The success of graph embeddings or node representation learning in a var...
Tensor decompositions are used in various data mining applications from
...
Fake news may be intentionally created to promote economic, political an...
Is it possible to extract malicious IP addresses reported in security fo...
This paper presents a new method, which we call SUSTain, that extends
re...
PARAFAC2 has demonstrated success in modeling irregular tensors, where t...
We study rank-1 L1-norm-based TUCKER2 (L1-TUCKER2) decomposition of 3-wa...
The PARAFAC tensor decomposition has enjoyed an increasing success in
ex...
Tensor decompositions are invaluable tools in analyzing multimodal datas...
In exploratory tensor mining, a common problem is how to analyze a set o...
Tensors or multi-way arrays are functions of three or more indices
(i,j...
A popular tool for unsupervised modelling and mining multi-aspect data i...
How can we correlate neural activity in the human brain as it responds t...