1 citations · 1 across the 3 of their papers we have counts for
3 papers
Deep Sketched Output Kernel Regression for Structured Prediction
Tamim El Ahmad, Junjie Yang, Pierre Laforgue +1
By leveraging the kernel trick in the output space, kernel-induced losses provide a principled way to define structured output prediction tasks for a wide variety of output modalit…
Multitask Learning with No Regret: from Improved Confidence Bounds to Active Learning
Pier Giuseppe Sessa, Pierre Laforgue, Nicolò Cesa-Bianchi +1
Multitask learning is a powerful framework that enables one to simultaneously learn multiple related tasks by sharing information between them. Quantifying uncertainty in the estim…
Linear Bandits with Memory: from Rotting to Rising
Giulia Clerici, Pierre Laforgue, Nicolò Cesa-Bianchi
Nonstationary phenomena, such as satiation effects in recommendations, have mostly been modeled using bandits with finitely many arms. However, the richer action space provided by…