Scaling mathematical discovery of new optimization methods with a robust pipeline for tuning and testing LLM-generated optimization code on dynamically generated test functions.
Energy, Learning, and Optimization
Scaling mathematical discovery of new optimization methods with a robust pipeline for tuning and testing LLM-generated optimization code on dynamically generated test functions.
Machine learning has exploded as companies find ways to draw actionable insights from the data which consumers feed them. However, the efficacy of artificial intelligence algorithms is dependent on the size of the data pool- giving big companies like Facebook and Google a formidable advantage over small scrappy startups. » Read More
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
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
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
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