43 citations · 130 across the 4 of their papers we have counts for
4 papers
Large-Scale User Modeling with Recurrent Neural Networks for Music Discovery on Multiple Time Scales
Cedric De Boom, Rohan Agrawal, Samantha Hansen +5
The amount of content on online music streaming platforms is immense, and most users only access a tiny fraction of this content. Recommender systems are the application of choice…
Using Deep Q-Learning to Control Optimization Hyperparameters
Samantha Hansen
We present a novel definition of the reinforcement learning state, actions and reward function that allows a deep Q-network (DQN) to learn to control an optimization hyperparameter…
A Stochastic Quasi-Newton Method for Large-Scale Optimization
R. H. Byrd, S. L. Hansen, J. Nocedal +1
The question of how to incorporate curvature information in stochastic approximation methods is challenging. The direct application of classical quasi- Newton updating techniques f…
Newton-Based Optimization for Kullback-Leibler Nonnegative Tensor Factorizations
Samantha Hansen, Todd Plantenga, Tamara G. Kolda
Tensor factorizations with nonnegative constraints have found application in analyzing data from cyber traffic, social networks, and other areas. We consider application data best…