15 citations · 15 across the 2 of their papers we have counts for
4 papers
Reward Prediction Error as an Exploration Objective in Deep RL
Riley Simmons-Edler, Ben Eisner, Daniel Yang +4
A major challenge in reinforcement learning is exploration, when local dithering methods such as epsilon-greedy sampling are insufficient to solve a given task. Many recent methods…
Q-Learning for Continuous Actions with Cross-Entropy Guided Policies
Riley Simmons-Edler, Ben Eisner, Eric Mitchell +2
Off-Policy reinforcement learning (RL) is an important class of methods for many problem domains, such as robotics, where the cost of collecting data is high and on-policy methods…
Learning Metric Graphs for Neuron Segmentation In Electron Microscopy Images
Kyle Luther, H. Sebastian Seung
In the deep metric learning approach to image segmentation, a convolutional net densely generates feature vectors at the pixels of an image. Pairs of feature vectors are trained to…
Program Synthesis Through Reinforcement Learning Guided Tree Search
Riley Simmons-Edler, Anders Miltner, Sebastian Seung
Program Synthesis is the task of generating a program from a provided specification. Traditionally, this has been treated as a search problem by the programming languages (PL) comm…