Widely adapted locally interpretable methods such as LIME [20] and SHAP [12] fail to capture the underlying causal relationships between the variables. They merely capture the linear and non-linear associations. These ...

Distributed machine learning (ML) workloads, particularly the training of deep neural networks (DNNs) and large language models (LLMs), rely heavily on efficient network communication to achieve scalability. However, network ...

With the increase in demand for enterprise wi- , there is a growing need to understand the functioning of these networks. Large scale Wi-Fi deployment is a challenging task. There is a need to diagnose network related ...

The COVID-19 crisis has made it clear that even for developed economies, like the USA, severe nancial disruptions can drag down the whole economy. It is considered the worst nancial crisis since the Great Depression. As ...

While progress in graph representation learning has often been model-centric: focusing on the design of more powerful architectures, this thesis presents a data-centric lens: a framework viewing the graph not as a static ...

This study investigates the link between the oral and gut microbiome, two highly diverse microbial communities with established connections to human health. We per formed meta-analysis on across those studies containing ...

In buildings, air conditioning consumes a significant proportion of the aggregate electricity bill. Specifically, in residential and small-scale commercial buildings, people prefer to use room-level ACs (AC stands for Air ...

The cryo-electron microscopy (cryo-EM) technique captures 2D projections of biological structures, revealing their inherent Heterogeneity arising from structural flexibility, conformational changes, and distinct functional ...

Education is now often regarded as the most important contributor to a country’s economic prosperity and stability. Digitalization plays a key part in the development and progress of every area in today’s world. The education ...

Current wireless applications such as autonomous driving, UAVs, IOT devices, etc. generate massive amounts of data that can be utilized to train machine learning models for decision making. Privacy, security and bandwidth ...