Related papers: BORA: A Personalized Data Display for Large-scale …
Web browsing is the main Internet Service and every customer wants the minimum web page loading times. To satisfy this perpetual need, web browsers offer new processing engines and increased functionalities. Web developers make use of new…
In a typical Event-Based Surveillance setting, a stream of web documents is continuously monitored for disease reporting. A structured representation of the disease reporting events is extracted from the raw text, and the events are then…
Recently, pedestrian behavior research has shifted towards machine learning based methods and converged on the topic of modeling pedestrian interactions. For this, a large-scale dataset that contains rich information is needed. We propose a…
Sensors are present in various forms all around the world such as mobile phones, surveillance cameras, smart televisions, intelligent refrigerators and blood pressure monitors. Usually, most of the sensors are a part of some other system…
Digital networks, mobile devices, and the possibility of mining the ever-increasing amount of digital traces that we leave behind in our daily activities are changing the way we can approach the study of human and social interactions.…
State estimation constitutes a core task in monitoring, supervision, and control of dynamic systems. This paper proposes a data-driven framework for the design of state observers for descriptor systems. Necessary and sufficient conditions…
Embedding data visualizations in video can enhance the communication of complex information. However, this process is often labor-intensive, requiring designers to adjust visualizations frame by frame manually. In this work, we present…
Data intensive applications often involve the analysis of large datasets that require large amounts of compute and storage resources. While dedicated compute and/or storage farms offer good task/data throughput, they suffer low resource…
In the Jupyter ecosystem, data visualization is usually done with "widgets" created as notebook cell outputs. While this mechanism works well in some circumstances, it is not well-suited to presenting interfaces that are long-lived,…
Stream-based monitoring assesses the health of safety-critical systems by transforming input streams of sensor measurements into output streams that determine a verdict. These inputs are often treated as accurate representations of the…
Astronomical datasets are growing in size and diversity, posing severe technical problems. At the same time scientific goals increasingly require the analysis of very large amounts of data, and data from multiple archives. The Virtual…
The COVID-19 pandemic highlighted the need for new data infrastructure, as epidemiologists and public health workers raced to harness rapidly evolving data, analytics, and infrastructure in support of cross-sector investigations. To meet…
This work investigates the task of unsupervised model personalization, adapted to continually evolving, unlabeled local user images. We consider the practical scenario where a high capacity server interacts with a myriad of resource-limited…
Accessing data collected by federal statistical agencies is essential for public policy research and improving evidence-based decision making, such as evaluating the effectiveness of social programs, understanding demographic shifts, or…
Test-time adaptation (TTA) enables a pre-trained model to adapt online to an unlabeled test stream under distribution shift. While most TTA research focuses on the adaptation objective, practical streams also depend critically on the memory…
Self-driving laboratories offer a promising path toward reducing the labor-intensive, time-consuming, and often irreproducible workflows in the biological sciences. Yet their stringent precision requirements demand highly robust models…
We are living in the big data age: An ever increasing amount of data is being produced through data acquisition and computer simulations. While large scale analysis and simulations have received significant attention for cloud and…
In this paper, we describe the implementation of a real time visualization and feedback system for Wireless Sensor Network algorithms. The system is based on a fixed hardware testbed, which is deployed on a vertical flat surface and a…
Real-time physiological data collection and analysis play a central role in modern well-being applications. Personalized classifiers and detectors have been shown to outperform general classifiers in many contexts. However, building…
Technological advances for measuring or simulating volume data have led to large data sizes in many research areas such as biology, medicine, physics, and geoscience. Here, large data can refer to individual data sets with high spatial…