Conventional centralized optimization algorithms have challenge solving big optimization problems- at some scale, you simply can’t fit the problem on a single computer, let alone manage all of the variables. To solve this, researchers use decentralized optimization techniques to break the problem into a set of subproblems which can be rapidly solved on distributed computers or smart devices- but this exposes the optimization algorithm to cybersecurity threats from hacking these consumer-level devices. » Read More
Category Archives: Optimization
Build Your Own Support Vector Machine
Support vector machines are the canonical example of the close ties between convex optimization and machine learning. Trained on a set of labeled data (i.e. this is a supervised learning algorithm) they are algorithmically simple and can scale well to large numbers of features or data samples, » Read More
American Controls Conference Recap
Last week I attended the American Controls Conference, an academic conference focused on classical controls and optimization. While this was the first time I had attended, this is one of biggest conferences for the eCAL lab’s research, » Read More
New paper: Decentralized Microgrid Controls
Solar panels, electric vehicles, smart appliances, and storage systems are rewriting the electricity production landscape. When used intelligently, these Distributed Energy Resources (DERs) can reduce cost, improve reliability, and help fight global warming by integrating more renewable energy into the electricity grid. » Read More