57 citations · 479 across the 53 of their papers we have counts for
Showing 2014 · cs.LGShow all
2 papers · 2 filters
cs.LG2014
No-Regret Learnability for Piecewise Linear Losses
Arthur Flajolet, Patrick Jaillet
In the convex optimization approach to online regret minimization, many methods have been developed to guarantee a bound on regret for subdifferentiable convex loss f…
cs.LG2014★ 24 cited
Parallel Gaussian Process Regression with Low-Rank Covariance Matrix Approximations
Jie Chen, Nannan Cao, Kian Hsiang Low +3
Gaussian processes (GP) are Bayesian non-parametric models that are widely used for probabilistic regression. Unfortunately, it cannot scale well with large data nor perform real-t…