Abstract. Belief propagation (BP) is the calculation method which enables us to obtain the marginal probabilities with a tractable computational cost. BP is known to provide true m...
In this paper, we address the issue of learning nonlinearly separable concepts with a kernel classifier in the situation where the data at hand are altered by a uniform classific...
We propose a novel bound on single-variable marginal probability distributions in factor graphs with discrete variables. The bound is obtained by propagating local bounds (convex ...
Mobile robots often rely upon systems that render sensor data and perceptual features into costs that can be used in a planner. The behavior that a designer wishes the planner to ...
Nathan D. Ratliff, J. Andrew Bagnell, Martin Zinke...
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...
ErHeng Zhong, Wei Fan, Jing Peng, Kun Zhang, Jiang...