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06/28/2023
cuSLINK: Single-linkage Agglomerative Clustering on the GPU
In this paper, we propose cuSLINK, a novel and state-of-the-art reformul...
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05/31/2023
Recasting Self-Attention with Holographic Reduced Representations
In recent years, self-attention has become the dominant paradigm for seq...
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02/13/2023
RFC-Net: Learning High Resolution Global Features for Medical Image Segmentation on a Computational Budget
Learning High-Resolution representations is essential for semantic segme...
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12/15/2022
Backdoor Attack Detection in Computer Vision by Applying Matrix Factorization on the Weights of Deep Networks
The increasing importance of both deep neural networks (DNNs) and cloud ...
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11/23/2022
Lempel-Ziv Networks
Sequence processing has long been a central area of machine learning res...
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10/16/2022
Towards an Interpretable Hierarchical Agent Framework using Semantic Goals
Learning to solve long horizon temporally extended tasks with reinforcem...
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06/13/2022
Deploying Convolutional Networks on Untrusted Platforms Using 2D Holographic Reduced Representations
Due to the computational cost of running inference for a neural network,...
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11/07/2021
Automatic Goal Generation using Dynamical Distance Learning
Reinforcement Learning (RL) agents can learn to solve complex sequential...
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10/09/2021
Interactive Hierarchical Guidance using Language
Reinforcement learning has been successful in many tasks ranging from ro...
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09/30/2021
Determining Standard Occupational Classification Codes from Job Descriptions in Immigration Petitions
Accurate specification of standard occupational classification (SOC) cod...
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09/05/2021
Learning with Holographic Reduced Representations
Holographic Reduced Representations (HRR) are a method for performing sy...
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06/30/2021
Learning a Reversible Embedding Mapping using Bi-Directional Manifold Alignment
We propose a Bi-Directional Manifold Alignment (BDMA) that learns a non-...
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04/13/2021
Semiring Primitives for Sparse Neighborhood Methods on the GPU
High-performance primitives for mathematical operations on sparse vector...
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09/29/2020
Immigration Document Classification and Automated Response Generation
In this paper, we consider the problem of organizing supporting document...
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08/01/2020
Bringing UMAP Closer to the Speed of Light with GPU Acceleration
The Uniform Manifold Approximation and Projection (UMAP) algorithm has b...
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04/07/2020
Locality Preserving Loss to Align Vector Spaces
We present a locality preserving loss (LPL)that improves the alignment b...
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10/10/2019
Using Neural Networks for Programming by Demonstration
Agent-based modeling is a paradigm of modeling dynamic systems of intera...
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10/10/2019
Universal Adversarial Perturbation for Text Classification
Given a state-of-the-art deep neural network text classifier, we show th...
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09/29/2019
Learning from Observations Using a Single Video Demonstration and Human Feedback
In this paper, we present a method for learning from video demonstration...
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09/12/2019
Determining the Scale of Impact from Denial-of-Service Attacks in Real Time Using Twitter
Denial of Service (DoS) attacks are common in on-line and mobile service...
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08/08/2019
Graph Node Embeddings using Domain-Aware Biased Random Walks
The recent proliferation of publicly available graph-structured data has...
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04/18/2019
Hybrid Mortality Prediction using Multiple Source Systems
The use of artificial intelligence in clinical care to improve decision ...
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03/28/2019
Extending Signature-based Intrusion Detection Systems WithBayesian Abductive Reasoning
Evolving cybersecurity threats are a persistent challenge for systemadmi...
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03/25/2019
On the use of Deep Autoencoders for Efficient Embedded Reinforcement Learning
In autonomous embedded systems, it is often vital to reduce the amount o...
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08/01/2018
Cognitive Techniques for Early Detection of Cybersecurity Events
The early detection of cybersecurity events such as attacks is challengi...
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09/13/2017
Automated Cloud Provisioning on AWS using Deep Reinforcement Learning
As the use of cloud computing continues to rise, controlling cost become...
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08/28/2017
Deep Belief Networks used on High Resolution Multichannel Electroencephalography Data for Seizure Detection
Ubiquitous bio-sensing for personalized health monitoring is slowly beco...
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07/31/2017
Fashioning with Networks: Neural Style Transfer to Design Clothes
Convolutional Neural Networks have been highly successful in performing ...
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06/13/2017
Identifying Spatial Relations in Images using Convolutional Neural Networks
Traditional approaches to building a large scale knowledge graph have us...
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11/20/2016
Time Series Classification from Scratch with Deep Neural Networks: A Strong Baseline
We propose a simple but strong baseline for time series classification f...
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08/09/2016
Neuroevolution-Based Inverse Reinforcement Learning
The problem of Learning from Demonstration is targeted at learning to pe...
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10/13/2015
Adopting Robustness and Optimality in Fitting and Learning
We generalized a modified exponentialized estimator by pushing the robus...
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06/08/2015
Adaptive Normalized Risk-Averting Training For Deep Neural Networks
This paper proposes a set of new error criteria and learning approaches,...
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06/01/2015
Imaging Time-Series to Improve Classification and Imputation
Inspired by recent successes of deep learning in computer vision, we pro...
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12/19/2014
Detecting Epileptic Seizures from EEG Data using Neural Networks
We explore the use of neural networks trained with dropout in predicting...
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12/12/2012