5 accepted papers
In-bed, non-contact vital signs monitoring enables patient monitoring without the use of intrusive sensors that interfere with patients’ sleep. Accelerometers incorporated into mattresses can be used to estimate insights related to vitals and sleep quality when someone lays on the mattress. A necess…
The performance of machine learning algorithms is limited by the availability of training data. Transfer learning can alleviate this limitation by adapting models trained in data-rich domains to a data-sparse domain. In this work, we propose a method for data augmentation in a partially sampled data…
In previous work, we proposed a scalable multi-party verification scheme for expensive iterative computations on a Blockchain substrate by appropriate storage and endorsement of frames of iterates. In this work, we extend the framework to verify sets of complete computations with different unordered…
This work explores sequential Bayesian binary hypothesis testing in the social learning setup under expertise diversity. We consider a two-agent (say advisor-learner) sequential binary hypothesis test where the learner infers the hypothesis based on the decision of the advisor, a prior private signa…
We introduce a sequential Bayesian binary hypothesis testing problem under social learning, termed selfish learning, where agents work to maximize their individual rewards. In particular, each agent receives a private signal and is aware of decisions made by earlier-acting agents. Beside inferring t…