A lot of people are learning English around the world and take assessments every year. With the rise of candidates taking these assessments and the shortage of qualified experts rating these assessments, there is a need ...

Correlation Filter based visual trackers have demonstrated tremendous progress in object tracking. These trackers primarily use hierarchical features learned from multiple layers of a deep network. However, issues related ...

The report provides an overview of the motivation behind using reinforcement learning in network survivability and routing, modulation and spectrum allocation. The reinforcement learning algorithms that were explored ...

Given a question on a crowd sourced Q&A platform, we tried to gauge the difficulty of the question. Earlier, we tried various NLP based techniques for this purpose. Now, we tried various graph models in order to model ...

Counting Bloom filters are highly space-efficient with a small probability of false positives. Concurrent access to a Counting bloom filter can greatly increase its insertion and query throughput.

We propose a platform that connects Doctors, Insurance and Patients and in doing so provides them value that won’t be possible otherwise. We use the platform to store the longitudinal health record of the patient (with ...

Conventional data warehouse systems are implemented either on a multi-dimensional database or a relational database. While the earlier supports MOLAP operations, the other supports ROLAP operations. In this work, we used ...

Resource allocation is a problem that requires complex decision making. Our focus is to solve this problem in the healthcare sector using Reinforcement Learning. We propose an RL pipeline that starts with a sequential ...

Real-time systems are becoming more complex and open, thus increasing their development and verification costs. Although several static verification tools have been proposed over the last decades, they suffer from scalability ...