36 citations · 122 across the 12 of their papers we have counts for
10 papers · 1 filter
What killed the Convex Booster ?
Yishay Mansour, Richard Nock, Robert C. Williamson
A landmark negative result of Long and Servedio established a worst-case spectacular failure of a supervised learning trio (loss, algorithm, model) otherwise praised for its high p…
PAC-Bayesian Bound for the Conditional Value at Risk
Zakaria Mhammedi, Benjamin Guedj, Robert C. Williamson
Conditional Value at Risk (CVaR) is a family of "coherent risk measures" which generalize the traditional mathematical expectation. Widely used in mathematical finance, it is garne…
Fairness risk measures
Robert C. Williamson, Aditya Krishna Menon
Ensuring that classifiers are non-discriminatory or fair with respect to a sensitive feature (e.g., race or gender) is a topical problem. Progress in this task requires fixing a de…
Exp-Concavity of Proper Composite Losses
Parameswaran Kamalaruban, Robert C. Williamson, Xinhua Zhang
The goal of online prediction with expert advice is to find a decision strategy which will perform almost as well as the best expert in a given pool of experts, on any sequence of…
Minimax Lower Bounds for Cost Sensitive Classification
Parameswaran Kamalaruban, Robert C. Williamson
The cost-sensitive classification problem plays a crucial role in mission-critical machine learning applications, and differs with traditional classification by taking the misclass…
Constant Regret, Generalized Mixability, and Mirror Descent
Zakaria Mhammedi, Robert C. Williamson
We consider the setting of prediction with expert advice; a learner makes predictions by aggregating those of a group of experts. Under this setting, and for the right choice of lo…