Reinforcement learning defines the problem facing agents that learn to make good decisions through action and observation alone. To be effective problem solvers, such agents …
The invent of modern RDMA-enabled networks in data centers calls for a fundamental re-evaluation of how distributed data stores should be designed. Conventionally, many data …
The downside of the world becoming more digitally connected is that it is now easier for powerful adversaries to strongly discourage digital communications by conducting …
The current paradigm in health tracking research, as performed in fields such as public health, social sciences, and research initiatives like mHealth, is to find …
The analysis of the statistical properties of data is a core goal in computer science. The challenges encountered in this task have evolved through time …
Cancer is an evolutionary process where cells acquire somatic mutations over time. As a result of this process, tumors are often highly heterogeneous — containing …
Extracting and inferring valuable knowledge from raw data requires training in programming and statistics, and more importantly, domain expertise. Yet domain experts, the people who …