The ability to see and navigate is a critical operational requirement for robots and autonomous systems. For example, consider autonomous rescue robots that are required to maneuver and navigate in challenging physical environments that humans cannot safely access. Similarly, building AI agents that can efficiently and…
In machine learning, adversarial examples usually refer to natural inputs plus small, specially crafted perturbations that can fool the model into making mistakes. In recent years, adversarial examples have been repeatedly discovered in deep learning applications, causing public concerns about AI safety. An illustration of…
The 2020 EMEA and Latin America PhD Award recipients are undertaking research central to advancing today’s technology—training artificial agents to learn faster in new situations, designing new scalable machine learning algorithms for continual and federated learning, and several other compelling projects. Not only is the…
The amount of visual data we accumulate around the world is mind boggling. However, not all the images are captured by high-end DSLR cameras, and very often they suffer from imperfections. It is of tremendous benefit to save those degraded images so that users can…
Since AlexNet was invented in 2012, there has been rapid development in convolutional neural network architectures in computer vision. Representative architectures (Figure 1) include GoogleNet (2014), VGGNet (2014), ResNet (2015), and DenseNet (2016), which are developed initially from image classification. It’s a golden rule that…
This year marks the fourth year of the Microsoft Research Dissertation Grant, which offers grants of up to $25,000 to support the research of students nearing the completion of doctoral degrees at North American universities who are underrepresented in the field of computing. This was…
In computer vision, one key property we expect of an intelligent artificial model, agent, or algorithm is that it should be able to correctly recognize the type, or class, of objects it encounters. This is critical in numerous important real-world scenarios—from biomedicine, where an intelligent…
Editor’s Note: The author would like to give special thanks to his collaborators, Ardalan Amiri Sani, Professor of Computer Science at UC Irvine, Sung Eun (Summer) Kim, Professor of Law at UC Irvine, and UC Irvine students Saeed Mirzamohammadi, Yuxin (Myles) Liu, and Tianmei Ann…
What we can teach a model to do with natural language is dictated by the availability of data. Currently, we have a lot of labeled data for very few languages, making it difficult to train models to accomplish question answering, text summarization, and other tasks…
It’s a big day for you. Back-to-back meetings are scheduled with critical customers and partners, and a parent-teacher conference is sandwiched in there as well. As you’re headed toward the last meeting, suddenly you cannot remember the key talking points. Who sent you the pre-read…
As technology has advanced, the way we accomplish things in our lives has shifted. While new tech is influencing such basic human activities as communication, for instance, encouraging us to reconsider what it means to connect with one another, technological innovations are also changing approaches…
At the 2005 Conference on Neural Information Processing Systems, researcher Hanna Wallach found herself in a unique position—sharing a hotel room with another woman. Actually, three other women to be exact. In the previous years she had attended, that had never been an option because…
