In this paper, we propose a stochastic model to describe how search service providers charge client companies based on users' queries for the keywords related to these compan...
This paper proposes Twin Vector Machine (TVM), a constant space and sublinear time Support Vector Machine (SVM) algorithm for online learning. TVM achieves its favorable scaling b...
The kernel Perceptron is an appealing online learning algorithm that has a drawback: whenever it makes an error it must increase its support set, which slows training and testing ...
We explore the problem of assigning heterogeneous tasks to workers with different, unknown skill sets in crowdsourcing markets such as Amazon Mechanical Turk. We first formalize ...
In this paper, we explore the feasibility and performance optimization problems for real-time systems that must remain functional during an operation/mission with a fixed, initial...