44 citations · 60 across the 12 of their papers we have counts for
4 papers · 1 filter
Renormalized Sparse Neural Network Pruning
Michael G. Rawson
Large neural networks are heavily over-parameterized. This is done because it improves training to optimality. However once the network is trained, this means many parameters can b…
Top-K Ranking Deep Contextual Bandits for Information Selection Systems
Jade Freeman, Michael Rawson
In today's technology environment, information is abundant, dynamic, and heterogeneous in nature. Automated filtering and prioritization of information is based on the distinction…
Convergence Guarantees for Deep Epsilon Greedy Policy Learning
Michael Rawson, Radu Balan
Policy learning is a quickly growing area. As robotics and computers control day-to-day life, their error rate needs to be minimized and controlled. There are many policy learning…
Deep Upper Confidence Bound Algorithm for Contextual Bandit Ranking of Information Selection
Michael Rawson, Jade Freeman
Contextual multi-armed bandits (CMAB) have been widely used for learning to filter and prioritize information according to a user's interest. In this work, we analyze top-K ranking…