Personal data is under constant threat in the modern world --- from corporations looking to profit from over-collection and sale of personal data, to criminal …
In recent years, there has been a renewed interest in near-memory processing (NMP) architectures as a workaround for the performance and energy issues of frequent …
Coreference Resolution is a fundamental natural language processing (NLP) problem, as it attempts to resolve which underlying discourse objects refer to one another. Further, it …
Grassroots organizing is a process by which people work from within marginalized communities to effect social, political, economic, and environmental change. People who engage in …
This dissertation studies the canonical tasks of database compression and similarity search, and demonstrates how advanced deep learning models can be used to develop effective …
Eye tracking, the process of capturing the gaze location within a display, is extensively used in usability studies, psychology, human-computer interaction, and marketing. The setup …
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 …
Over the last decade, Python emerged as the language of choice for data processing and model building. Yet, the developer productivity of Python comes at …
At present, there are many blockchains, each competing with the others to gain market share and dominance. It is expected that multiple blockchains will continue …
Reusing knowledge allows intelligent systems to learn solutions to complex tasks more quicker by avoiding re-learning the components of the solution from scratch. Recent advances …
In the era of big data, distributed data stores have become an indispensable necessity. Almost all these data stores store sensitive data such as our …
In the era of big data, distributed data stores have become an indispensable necessity. Almost all these data stores store sensitive data such as our …
In today's age of blockchain and cloud-computing, we are constantly in search of tools that offer accountability without compromising privacy. A class of predominantly used …
Students often tackle programming problems with a flawed understanding of what the problem is asking. Some pedagogies attempt to address this by encouraging students to …
Machine learning models, or algorithms trained on historical data, can be harmful when they are used to make decisions about people. From underfitting to overfitting, …
Reinforcement learning (RL) techniques have led to remarkable results in challenging domains such as Atari games, Go, and Starcraft, suggesting that practical applications lie just …
With few exceptions, robots today are unable to quickly acquire new manipulation skills in the real world. The modern data-driven approach to skill learning is …
The adoption of cloud services is on the rise, with both personal and corporate data being stored on third-party server databases. In order to protect …
Combinatorial and algebraic topology have both provided useful mathematical tools to the field of distributed computing, giving researchers a rigorous mathematical model in which one …
