266 citations · 370 across the 5 of their papers we have counts for
5 papers
Field-aware Factorization Machines in a Real-world Online Advertising System
Yuchin Juan, Damien Lefortier, Olivier Chapelle
Predicting user response is one of the core machine learning tasks in computational advertising. Field-aware Factorization Machines (FFM) have recently been established as a state-…
Cost-sensitive Learning for Utility Optimization in Online Advertising Auctions
Flavian Vasile, Damien Lefortier, Olivier Chapelle
One of the most challenging problems in computational advertising is the prediction of click-through and conversion rates for bidding in online advertising auctions. An unaddressed…
Distance Metric Learning for Kernel Machines
Zhixiang Xu, Kilian Q. Weinberger, Olivier Chapelle
Recent work in metric learning has significantly improved the state-of-the-art in k-nearest neighbor classification. Support vector machines (SVM), particularly with RBF kernels, a…
The Greedy Miser: Learning under Test-time Budgets
Zhixiang Xu, Kilian Weinberger, Olivier Chapelle
As machine learning algorithms enter applications in industrial settings, there is increased interest in controlling their cpu-time during testing. The cpu-time consists of the run…
A Reliable Effective Terascale Linear Learning System
Alekh Agarwal, Olivier Chapelle, Miroslav Dudik +1
We present a system and a set of techniques for learning linear predictors with convex losses on terascale datasets, with trillions of features, {The number of features here refers…