information theory, cryptography, and empirical machine learning research. Grading will be based on 6 homework assignments, class participation, a small class project, and a take-home final (worth ...

Catalog description: Presents the underlying theory behind machine learning in proofs-based format. Answers fundamental questions about what learning means and what can be learned via formal models of ...

School 2025 is part of the Research Semester Programme "Control Theory and Reinforcement Learning: Connections and Challenges ...

In this online data science specialization, you will apply machine learning algorithms to real-world data, learn when to use which model and why, and improve the performance of your models. Beginning ...

Move beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge field In Game Theory and Machine Learning for Cyber Security, a team of ...

Deep neural networks (DNNs) have revolutionized machine learning, yet their success defies classical expectations. They ...

This program is a Python implementation of theory and (some of the) applications developed in the paper Machine Learning for Evaluating and Improving Theories by Fudenberg and Liang, available here.

The increasing types of model and data enhance the complexity of machine learning. In this paper, we propose a mathematical structure based on category theory as a combination of machine learning that ...

The Poisson distribution is widely used in artificial intelligence (AI) and machine learning. In Bayesian inference, ...

Michael Kearns is a computer scientist who has made fundamental contributions to the theory of machine learning, algorithmic game theory, computational social science, and quantitative finance. Kearns ...

In November 2024, Manoj Bhoyar was also honoured with the prestigious Global Recognition Award for his remarkable contributions to financial technology. To explore the journey behind his ...

Course description: This seminar class will focus on new results and directions in machine learning theory. Machine learning theory concerns questions such as: What kinds of guarantees can we prove ...