15 citations · 18 across the 4 of their papers we have counts for
4 papers
Smoothed Q-learning
David Barber
In Reinforcement Learning the Q-learning algorithm provably converges to the optimal solution. However, as others have demonstrated, Q-learning can also overestimate the values and…
Integrated Weak Learning
Peter Hayes, Mingtian Zhang, Raza Habib +3
We introduce Integrated Weak Learning, a principled framework that integrates weak supervision into the training process of machine learning models. Our approach jointly trains the…
Addressing Catastrophic Forgetting in Few-Shot Problems
Pauching Yap, Hippolyt Ritter, David Barber
Neural networks are known to suffer from catastrophic forgetting when trained on sequential datasets. While there have been numerous attempts to solve this problem in large-scale s…
Optimal Spike-Timing Dependent Plasticity for Precise Action Potential Firing
Jean-Pascal Pfister, Taro Toyoizumi, David Barber +1
In timing-based neural codes, neurons have to emit action potentials at precise moments in time. We use a supervised learning paradigm to derive a synaptic update rule that optimiz…