58 citations · 175 across the 25 of their papers we have counts for
4 papers · 1 filter
Incorporating the Barzilai-Borwein Adaptive Step Size into Sugradient Methods for Deep Network Training
Antonio Robles-Kelly, Asef Nazari
In this paper, we incorporate the Barzilai-Borwein step size into gradient descent methods used to train deep networks. This allows us to adapt the learning rate using a two-point…
Robust Neural Regression via Uncertainty Learning
Akib Mashrur, Wei Luo, Nayyar A. Zaidi +1
Deep neural networks tend to underestimate uncertainty and produce overly confident predictions. Recently proposed solutions, such as MC Dropout and SDENet, require complex trainin…
Hierarchically Fair Federated Learning
Jingfeng Zhang, Cheng Li, Antonio Robles-Kelly +1
When the federated learning is adopted among competitive agents with siloed datasets, agents are self-interested and participate only if they are fairly rewarded. To encourage the…
Discriminative Probabilistic Prototype Learning
Edwin Bonilla, Antonio Robles-Kelly
In this paper we propose a simple yet powerful method for learning representations in supervised learning scenarios where each original input datapoint is described by a set of vec…