21 citations · 60 across the 9 of their papers we have counts for
10 papers
Learning with Holographic Reduced Representations
Ashwinkumar Ganesan, Hang Gao, Sunil Gandhi +4
Holographic Reduced Representations (HRR) are a method for performing symbolic AI on top of real-valued vectors by associating each vector with an abstract concept, and providing m…
Learning a Reversible Embedding Mapping using Bi-Directional Manifold Alignment
Ashwinkumar Ganesan, Francis Ferraro, Tim Oates
We propose a Bi-Directional Manifold Alignment (BDMA) that learns a non-linear mapping between two manifolds by explicitly training it to be bijective. We demonstrate BDMA by train…
Locality Preserving Loss: Neighbors that Live together, Align together
Ashwinkumar Ganesan, Francis Ferraro, Tim Oates
We present a locality preserving loss (LPL) that improves the alignment between vector space embeddings while separating uncorrelated representations. Given two pretrained embeddin…
Determining the Scale of Impact from Denial-of-Service Attacks in Real Time Using Twitter
Chi Zhang, Bryan Wilkinson, Ashwinkumar Ganesan +1
Denial of Service (DoS) attacks are common in on-line and mobile services such as Twitter, Facebook and banking. As the scale and frequency of Distributed Denial of Service (DDoS)…
Extending Signature-based Intrusion Detection Systems WithBayesian Abductive Reasoning
Ashwinkumar Ganesan, Pooja Parameshwarappa, Akshay Peshave +2
Evolving cybersecurity threats are a persistent challenge for systemadministrators and security experts as new malwares are continu-ally released. Attackers may look for vulnerabil…
Cognitive Techniques for Early Detection of Cybersecurity Events
Sandeep Narayanan, Ashwinkumar Ganesan, Karuna Joshi +3
The early detection of cybersecurity events such as attacks is challenging given the constantly evolving threat landscape. Even with advanced monitoring, sophisticated attackers ca…
Fashioning with Networks: Neural Style Transfer to Design Clothes
Prutha Date, Ashwinkumar Ganesan, Tim Oates
Convolutional Neural Networks have been highly successful in performing a host of computer vision tasks such as object recognition, object detection, image segmentation and texture…
Identifying Spatial Relations in Images using Convolutional Neural Networks
Mandar Haldekar, Ashwinkumar Ganesan, Tim Oates
Traditional approaches to building a large scale knowledge graph have usually relied on extracting information (entities, their properties, and relations between them) from unstruc…
Finding Representative Points in Multivariate Data Using PCA
Ashwinkumar Ganesan, Tim Oates, Matt Schmill
The idea of representation has been used in various fields of study from data analysis to political science. In this paper, we define representativeness and describe a method to is…
LDAExplore: Visualizing Topic Models Generated Using Latent Dirichlet Allocation
Ashwinkumar Ganesan, Kiante Brantley, Shimei Pan +1
We present LDAExplore, a tool to visualize topic distributions in a given document corpus that are generated using Topic Modeling methods. Latent Dirichlet Allocation (LDA) is one…