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Fall 2019

Joulani, Pooria

We study three problems in the application, design, and analysis of online optimization algorithms for machine learning. First, we consider speeding-up the common task of k-fold cross-validation of online algorithms, and provide TreeCV, an algorithm that reduces the time penalty of k-fold...

Fall 2018

Sweileh, Belal

Parents often show disempowerment in relation to supporting their children with schoolwork (Hoover-Dempsey et al., 2005; Hornby & Lafaele, 2011; Peña, 2000; Thomsen, 2011). In the case of Arabic learning, parents typically cannot involve themselves in their children’s Arabic learning due to...

Spring 2013

Zolghadr, Navid

This work introduces the “online probing” problem: In each round, the learner is able to purchase the values of a subset of features for the current instance. After the learner uses this information to produce a prediction for this instance, it then has the option of paying for seeing the full...

Fall 2020

D'Orazio, Ryan

Computing a Nash equilibrium in zero-sum games, or more generally saddle point optimization, is a fundamental problem in game theory and machine learning, with applications spanning across a wide variety of domains, from generative modeling and computer vision to super-human AI in imperfect...

Spring 2016

Morrill, Dustin R

Game theoretic solution concepts, such as Nash equilibrium strategies that are optimal against worst case opponents, provide guidance in finding desirable autonomous agent behaviour. In particular, we wish to approximate solutions to complex, dynamic tasks, such as negotiation or bidding in...