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06/12/2023
CARL-G: Clustering-Accelerated Representation Learning on Graphs
Self-supervised learning on graphs has made large strides in achieving g...
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06/19/2022
FRAPPE: Fast Rank Approximation with Explainable Features for Tensors
Tensor decompositions have proven to be effective in analyzing the struc...
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05/25/2022
MAVIPER: Learning Decision Tree Policies for Interpretable Multi-Agent Reinforcement Learning
Many recent breakthroughs in multi-agent reinforcement learning (MARL) r...
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07/02/2021
Subspace Clustering Based Analysis of Neural Networks
Tools to analyze the latent space of deep neural networks provide a step...
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02/15/2021
KNH: Multi-View Modeling with K-Nearest Hyperplanes Graph for Misinformation Detection
Graphs are one of the most efficacious structures for representing datap...
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02/15/2021
Identifying Misinformation from Website Screenshots
Can the look and the feel of a website give information about the trustw...
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12/23/2020
Analyzing Representations inside Convolutional Neural Networks
How can we discover and succinctly summarize the concepts that a neural ...
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11/14/2020
RecTen: A Recursive Hierarchical Low Rank Tensor Factorization Method to Discover Hierarchical Patterns in Multi-modal Data
How can we expand the tensor decomposition to reveal a hierarchical stru...
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11/14/2020
TenFor: A Tensor-Based Tool to Extract Interesting Events from Security Forums
How can we get a security forum to "tell" us its activities and events o...
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08/17/2020
Ensemble Node Embeddings using Tensor Decomposition: A Case-Study on DeepWalk
Node embeddings have been attracting increasing attention during the pas...
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05/08/2020
HiJoD: Semi-Supervised Multi-aspect Detection of Misinformation using Hierarchical Joint Decomposition
Distinguishing between misinformation and real information is one of the...
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02/18/2020
TensorShield: Tensor-based Defense Against Adversarial Attacks on Images
Recent studies have demonstrated that machine learning approaches like d...
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01/08/2020
REST: A thread embedding approach for identifying and classifying user-specified information in security forums
How can we extract useful information from a security forum? We focus on...
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12/19/2019
Adaptive Granularity in Tensors: A Quest for Interpretable Structure
Data collected at very frequent intervals is usually extremely sparse an...
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11/18/2018
The core consistency of a compressed tensor
Tensor decomposition on big data has attracted significant attention rec...
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11/05/2018
Representation Learning by Reconstructing Neighborhoods
Since its introduction, unsupervised representation learning has attract...
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08/23/2018
Webly Supervised Joint Embedding for Cross-Modal Image-Text Retrieval
Cross-modal retrieval between visual data and natural language descripti...
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07/03/2018
OCTen: Online Compression-based Tensor Decomposition
Tensor decompositions are powerful tools for large data analytics as the...
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06/30/2018
A Constrained Coupled Matrix-Tensor Factorization for Learning Time-evolving and Emerging Topics
Topic discovery has witnessed a significant growth as a field of data mi...
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06/06/2018
A Peek Into the Hidden Layers of a Convolutional Neural Network Through a Factorization Lens
Despite their increasing popularity and success in a variety of supervis...
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05/03/2018
t-PINE: Tensor-based Predictable and Interpretable Node Embeddings
Graph representations have increasingly grown in popularity during the l...
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05/03/2018
SURREAL: SUbgraph Robust REpresentAtion Learning
The success of graph embeddings or node representation learning in a var...
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04/25/2018
Identifying and Alleviating Concept Drift in Streaming Tensor Decomposition
Tensor decompositions are used in various data mining applications from ...
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04/24/2018
Semi-supervised Content-based Detection of Misinformation via Tensor Embeddings
Fake news may be intentionally created to promote economic, political an...
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04/13/2018
RIPEx: Extracting malicious IP addresses from security forums using cross-forum learning
Is it possible to extract malicious IP addresses reported in security fo...
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03/14/2018
SUSTain: Scalable Unsupervised Scoring for Tensors and its Application to Phenotyping
This paper presents a new method, which we call SUSTain, that extends re...
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03/12/2018
COPA: Constrained PARAFAC2 for Sparse & Large Datasets
PARAFAC2 has demonstrated success in modeling irregular tensors, where t...
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10/31/2017
The Exact Solution to Rank-1 L1-norm TUCKER2 Decomposition
We study rank-1 L1-norm-based TUCKER2 (L1-TUCKER2) decomposition of 3-wa...
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09/04/2017
Balancing Interpretability and Predictive Accuracy for Unsupervised Tensor Mining
The PARAFAC tensor decomposition has enjoyed an increasing success in ex...
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09/03/2017
SamBaTen: Sampling-based Batch Incremental Tensor Decomposition
Tensor decompositions are invaluable tools in analyzing multimodal datas...
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03/13/2017
SPARTan: Scalable PARAFAC2 for Large & Sparse Data
In exploratory tensor mining, a common problem is how to analyze a set o...
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07/06/2016
Tensor Decomposition for Signal Processing and Machine Learning
Tensors or multi-way arrays are functions of three or more indices (i,j...
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03/11/2015
Automatic Unsupervised Tensor Mining with Quality Assessment
A popular tool for unsupervised modelling and mining multi-aspect data i...
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02/28/2013
