Algorithms
Artificial Social Intelligence
Breakthroughs in Artificial Intelligence (AI) have typically shown that AI systems are good at solving specific tasks that have a well-defined goal, such as Speech Recognition, Image Captioning, Games like Poker/Go/Jeopardy, among others. However, as…
Fast Quantification of Uncertainty and Robustness with Variational Bayes
In Bayesian analysis, the posterior follows from the data and a choice of a prior and a likelihood. These choices may be somewhat subjective and reasonably vary over some range. Thus, we wish to measure…
Resource Efficient Driving Policy
When attacking the problem of Autonomous Driving, one must take into account strict computational constraints, posed by the desired low cost of sensors and processors, and by the required real-time performance. Specifically, when considering Driving…
Trading-Off Cost of Deployment Versus Accuracy for Predictive Models
Predictive models are finding an increasing number of applications in many industries. As a result, a practical means for trading-off the cost of deploying a model versus its effectiveness is needed. Our work is motivated…
Small Deep Neural Networks – Their Advantages, and Their Design
Deep neural networks (DNNs) have led to significant improvements to the accuracy of machine-learning applications. For many problems, such as object classification and object detection, DNNs have led to levels of accuracy that are acceptable…
On-Device Machine Intelligence with Neural Projections
Deep neural networks and other machine learning models have been transformative for building intelligent systems capable of visual recognition, speech and language understanding. While recent advances have led to progress for machine intelligence applications running…
