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Model adaptation and unsupervised learning with non-stationary batch data under smooth concept drift
In this paper, we consider the scenario of a gradual concept drift due to the underlying non-stationarity of the data source.
Efficient Approximate Solutions to Mutual Information Based Global Feature Selection
Estimating the MI for a subset of features is often intractable.
Multiresolution Match Kernels for Gesture Video Classification
The emergence of depth imaging technologies like the Microsoft Kinect has renewed interest in computational methods for gesture classification based on videos.
Coupled Support Vector Machines for Supervised Domain Adaptation
Popular domain adaptation (DA) techniques learn a classifier for the target domain by sampling relevant data points from the source and combining it with the target data.
Causal Discovery for Manufacturing Domains
Specifically, the goal of this work is to learn interpretable causal models from observational data produced by manufacturing lines.
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