Robust Optimization

دکتر امیر نجفی

عضو هیئت علمی دانشگاه صنعتی شریف

پنج‌شنبه، ۱۰ خرداد، ساعت ۲:۱۵ الی ۳ بعدازظهر
سالن آمفی‌تئاتر دانشکده مهندسی کامپیوتر (سالن دکتر ربیعی)


In this talk, I will explore the foundational concepts of machine learning, including supervised and unsupervised scenarios based on data types, generalization, and learning architectures such as neural networks. We will then dive into the critical role of optimization in training models, followed by an introduction to robust optimization and its variant, distributionally robust optimization (DRO), highlighting their significance in enhancing model reliability. Finally, I will discuss our latest research on leveraging DRO to incorporate unlabeled data, thereby improving generalization and model performance in machine learning applications.