Abstract: We propose new greedy algorithms for learning the structure of a graphical model of a probability distribution, given samples drawn from the distribution. While structure learning of ...

COMP 272 or an equivalent data-structures course. Knowledge and skills in Java, C/C++, or Python programming. Knowledge of high school mathematics (MATH 30 level) is assumed. Course start date: If you ...

Abstract: Controlling units in real-time strategy (RTS) games is a challenging problem in Artificial Intelligence (AI) as these games are fast-paced with simultaneous moves and massive branching ...

A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool ...

Mastering DSA is essential for improving coding efficiency and cracking technical interviews. The right DSA books provide structured learning, real-world examples, and hands-on practice. Books like ...

I am a PhD student at Carnegie Mellon University supervised by Taylor Berg-Kirkpatrick and Graham Neubig. I also collaborate with Kevin Gimpel at the Toyota Technological Institute at the University ...