Background Accurate estimation of parameters of biochemical models is required to
characterize the dynamics of molecular processes. This problem is intimately linked to …

As machine learning methods are utilized in more and more real-world applications
involving constraints on computational budgets, the systematic integration of such …

When acquiring consumer data for marketing or new business initiatives, it is important to
decide what attributes or features of potential customers should be acquired. We study a …

The cost of data acquisition limits the amount of labeled data available for machine learning
algorithms, both at the training and the testing phase. This problem is further exacerbated in …

With the rapid growth of real-time machine learning applications, the process of feature
selection and model optimization requires to integrate with the constraints on computational …

The performance of a machine learning algorithm is dependent on the quality of the
available data for model development. However, in practical situations, the availability of the …

The goal of active class selection (ACS) is to optimize the class proportions in newly
acquired data; a classifier trained from that data should exhibit maximum performance …

Abstract Systems Biology aims at elucidating the high-level functions of the cell from their
biochemical basis at the molecular level. A lot of work has been done for collecting genomic …

Abstract Siamese Neural Networks (SNNs) are deep metric learners that use paired
instance comparisons to learn similarity. The neural feature maps learnt in this way provide …

Robots hold the promise of becoming an integral part of human life by helping us in our
homes, out on farms and in our factories. However, current robots lack the motor skills …