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Active Face Frontalization using Commodity Unmanned Aerial Vehicles
The system is implemented using an off-the-shelf hardware and software components and can be easily transfered to any ROS enabled UAVs.
Entropy-Isomap: Manifold Learning for High-dimensional Dynamic Processes
Scientific and engineering processes deliver massive high-dimensional data sets that are generated as non-linear transformations of an initial state and few process parameters.
Error Metrics for Learning Reliable Manifolds from Streaming Data
In this paper, we argue that a stable manifold can be learned using only a fraction of the stream, and the remaining stream can be mapped to the manifold in a significantly less costly manner.
On Optimality Conditions for Auto-Encoder Signal Recovery
Auto-Encoders are unsupervised models that aim to learn patterns from observed data by minimizing a reconstruction cost.
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