Search Results for author:
Found 8 papers, 2 papers with code
Knowledge Equivalence in Digital Twins of Intelligent Systems
Maintaining such an equivalent model is challenging, especially when the physical systems being modelled are intelligent and autonomous.
Super Reinforcement Bros: Playing Super Mario Bros with Reinforcement Learning
We plan to apply and adjust some well-known reinforcement learning (RL) algorithms to train an automatic agent to play the 1985 Nintendo game Super Mario Bros under a speedrun rule.
Leveraging History for Faster Sampling of Online Social Networks
Random walk fits naturally with this problem because, for most online social networks, the only query we can issue through the interface is to retrieve the neighbors of a given node (i. e., no access to the full graph topology).
Real Time 3D Indoor Human Image Capturing Based on FMCW Radar
Compared to traditional camera-based computer vision and imaging, radio imaging based on wireless sensing does not require lighting and is friendly to privacy.
Unsupervised Machine Learning for the Discovery of Latent Disease Clusters and Patient Subgroups Using Electronic Health Records
Both unsupervised machine learning approaches could be leveraged to discover patient subgroups using EHRs but with different foci.
Understanding and Mitigating the Security Risks of Voice-Controlled Third-Party Skills on Amazon Alexa and Google Home
The significance of our findings have already been acknowledged by Amazon and Google, and further evidenced by the risky skills discovered on Alexa and Google markets by the new detection systems we built.
Cryptography and Security
Understanding IoT Security Through the Data Crystal Ball: Where We Are Now and Where We Are Going to Be
We systemize this process, by proposing a taxonomy for the IoT ecosystem and organizing IoT security into five problem areas.
Cryptography and Security
Fine-Grained Change Detection of Misaligned Scenes With Varied Illuminations
To guarantee detection sensitivity and accuracy of minute changes, in an observation, we capture a group of images under multiple illuminations, which need only to be roughly aligned to the last time lighting conditions.
