Abstract— This paper proposes a simulation-based active policy learning algorithm for finite-horizon, partially-observed sequential decision processes. The algorithm is tested i...
Ruben Martinez-Cantin, Nando de Freitas, Arnaud Do...
We recently proposed a new algorithm to perform acoustic model adaptation to noisy environments called Linear Spline Interpolation (LSI). In this method, the nonlinear relationshi...
Michael L. Seltzer, Alex Acero, Kaustubh Kalgaonka...
In this paper we present a novel approach for estimating featurespace maximum likelihood linear regression (fMLLR) transforms for full-covariance Gaussian models by directly maxim...
Arnab Ghoshal, Daniel Povey, Mohit Agarwal, Pinar ...
Using a directed acyclic graph (dag) model of algorithms, we solve a problem related to precedenceconstrained multiprocessor schedules for array computations: Given a sequence of ...
The development of accurate models and efficient algorithms for the analysis of multivariate categorical data are important and longstanding problems in machine learning and compu...
Mohammad Emtiyaz Khan, Shakir Mohamed, Benjamin M....