We describe a new method for learning the conditional probability distribution of a binary-valued variable from labelled training examples. Our proposed Compositional Noisy-Logica...
Probabilistic frequent itemset mining in uncertain transaction databases semantically and computationally differs from traditional techniques applied to standard "certain&quo...
— The ability to detect, and track multiple moving objects like person and other robots, is an important prerequisite for mobile robots working in dynamic indoor environments. We...
Abhijit Kundu, Madhava M. Krishna, Jayanthi Sivasw...
Abstract—This paper proposes a simple non-coherent amplifyand-forward receiver for the relay channel and evaluates its diversity performance for Rayleigh fading channels. We use ...
This paper presents a framework for efficiently streaming scalable video from multiple servers over heterogeneous network paths. We propose to use rateless codes, or Fountain cod...
Jean-Paul Wagner, Jacob Chakareski, Pascal Frossar...