— We propose a new probabilistic temporal logic iLTL which captures properties of systems whose state can be represented by probability mass functions (pmf’s). Using iLTL, we c...
In this paper we focus on an interpretation of Gaussian radial basis functions (GRBF) which motivates extensions and learning strategies. Specifically, we show that GRBF regressio...
While many devices today increasingly have the ability to predict human activities, it is still difficult to build accurate personalized machine learning models. As users today wi...
In this paper, we present a reinforcement learning approach for mapping natural language instructions to sequences of executable actions. We assume access to a reward function tha...
S. R. K. Branavan, Harr Chen, Luke S. Zettlemoyer,...
State-of-the-art approaches for detecting filament-like
structures in noisy images rely on filters optimized for signals
of a particular shape, such as an ideal edge or ridge.
W...