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05/19/2020
Self-Updating Models with Error Remediation
Many environments currently employ machine learning models for data proc...
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05/04/2020
Mind the Gap: On Bridging the Semantic Gap between Machine Learning and Information Security
Despite the potential of Machine learning (ML) to learn the behavior of ...
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11/10/2017
Dynamic Analysis of Executables to Detect and Characterize Malware
It is needed to ensure the integrity of systems that process sensitive i...
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03/21/2017
A Digital Neuromorphic Architecture Efficiently Facilitating Complex Synaptic Response Functions Applied to Liquid State Machines
Information in neural networks is represented as weighted connections, o...
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07/31/2015
A Minimal Architecture for General Cognition
A minimalistic cognitive architecture called MANIC is presented. The MAN...
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10/17/2014
A Hierarchical Multi-Output Nearest Neighbor Model for Multi-Output Dependence Learning
Multi-Output Dependence (MOD) learning is a generalization of standard c...
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07/07/2014
Recommending Learning Algorithms and Their Associated Hyperparameters
The success of machine learning on a given task dependson, among other t...
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06/09/2014
A Hybrid Latent Variable Neural Network Model for Item Recommendation
Collaborative filtering is used to recommend items to a user without req...
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05/28/2014
An Easy to Use Repository for Comparing and Improving Machine Learning Algorithm Usage
The results from most machine learning experiments are used for a specif...
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03/13/2014
The Potential Benefits of Filtering Versus Hyper-Parameter Optimization
The quality of an induced model by a learning algorithm is dependent on ...
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03/07/2014
Becoming More Robust to Label Noise with Classifier Diversity
It is widely known in the machine learning community that class noise ca...
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12/19/2013
Missing Value Imputation With Unsupervised Backpropagation
Many data mining and data analysis techniques operate on dense matrices ...
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12/13/2013