3 papers
cs.LG2021
Neural Mixture Models with Expectation-Maximization for End-to-end Deep Clustering
Dumindu Tissera, Kasun Vithanage, Rukshan Wijesinghe +4
Any clustering algorithm must synchronously learn to model the clusters and allocate data to those clusters in the absence of labels. Mixture model-based methods model clusters wit…
cs.CV2021
End-To-End Data-Dependent Routing in Multi-Path Neural Networks
Dumindu Tissera, Rukshan Wijessinghe, Kasun Vithanage +3
Neural networks are known to give better performance with increased depth due to their ability to learn more abstract features. Although the deepening of networks has been well est…
cs.AI2021
Transferring Domain Knowledge with an Adviser in Continuous Tasks
Rukshan Wijesinghe, Kasun Vithanage, Dumindu Tissera +3
Recent advances in Reinforcement Learning (RL) have surpassed human-level performance in many simulated environments. However, existing reinforcement learning techniques are incapa…