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AIML Special Presentation: Convergence and Asymptotic Optimality of the Heavy Ball Method and Its Relatives
- Date: Wed, 20 Nov 2024, 2:30 pm - 3:30 pm
- Location: AIML
Abstract: In this talk we first aim to shed light on the urban legend surrounding the ‘complexity lower bound’ for the heavy ball algorithm. Second, we revisit the original heavy-ball algorithm proposed by Polyak and provide a conditions for it to be globally converging, and provide step-size rules. Then, we investigate the performance of a related algorithm dubbed the Accelerated Generalised Gradient Method and see how how it can be beneficial in the case of tracking the minimum of a time-varying function.
AIML Special Presentation: Artificial Intelligence for Autonomous Scientific Exploration
- Date: Mon, 18 Nov 2024, 10:30 am - 11:30 am
- Location: AIML
David Wettergreen creates robots that explore and conducts field experiments in polar climates, deserts, underwater caverns, and volcanic craters. He has led numerous research projects including a decade of robotic investigation of microbial life in the Atacama Desert. His work in science autonomy enables robotic explorers to detect, classify, and evaluate geologic and biologic features to autonomously interpret and act upon their scientific observations. This work applies to space exploration and to applications in agriculture, forestry, ecology, and marine science.
