120 citations · 347 across the 16 of their papers we have counts for
5 papers · 1 filter
Ensemble Elastic DQN: A Step Dependent Ensemble Approach for Reducing Overestimation in Deep Value-Based Reinforcement Learning
Adrian Ly, Richard Dazeley, Peter Vamplew +2
Deep Q-Networks (DQN) can suffer from overestimation bias because bootstrapped targets use a maximisation operation over noisy value estimates. Ensemble-based methods and multi-ste…
Elastic Step DQN: A novel multi-step algorithm to alleviate overestimation in Deep QNetworks
Adrian Ly, Richard Dazeley, Peter Vamplew +2
Deep Q-Networks algorithm (DQN) was the first reinforcement learning algorithm using deep neural network to successfully surpass human level performance in a number of Atari learni…
A Comprehensive Survey on Outlying Aspect Mining Methods
Durgesh Samariya, Jiangang Ma, Sunil Aryal
In recent years, researchers have become increasingly interested in outlying aspect mining. Outlying aspect mining is the task of finding a set of feature(s), where a given data ob…
A new effective and efficient measure for outlying aspect mining
Durgesh Samariya, Sunil Aryal, Kai Ming Ting
Outlying Aspect Mining (OAM) aims to find the subspaces (a.k.a. aspects) in which a given query is an outlier with respect to a given dataset. Existing OAM algorithms use tradition…
Improved histogram-based anomaly detector with the extended principal component features
Sunil Aryal, Arbind Agrahari Baniya, KC Santosh
In this era of big data, databases are growing rapidly in terms of the number of records. Fast automatic detection of anomalous records in these massive databases is a challenging…