159 citations · 392 across the 32 of their papers we have counts for
Showing 2018Show all
3 papers · 1 filter
cs.LG2018★ 43 cited
Are All Training Examples Created Equal? An Empirical Study
Kailas Vodrahalli, Ke Li, Jitendra Malik
Modern computer vision algorithms often rely on very large training datasets. However, it is conceivable that a carefully selected subsample of the dataset is sufficient for traini…
cs.LG2018★ 59 cited
Implicit Maximum Likelihood Estimation
Ke Li, Jitendra Malik
Implicit probabilistic models are models defined naturally in terms of a sampling procedure and often induces a likelihood function that cannot be expressed explicitly. We develop…
cs.CV2018★ 1 cited
Universal Perceptual Grouping
Ke Li, Kaiyue Pang, Jifei Song +4
In this work we aim to develop a universal sketch grouper. That is, a grouper that can be applied to sketches of any category in any domain to group constituent strokes/segments in…