5 citations · 6 across the 4 of their papers we have counts for
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stat.ML2019
The Bias-Expressivity Trade-off
Julius Lauw, Dominique Macias, Akshay Trikha +2
Learning algorithms need bias to generalize and perform better than random guessing. We examine the flexibility (expressivity) of biased algorithms. An expressive algorithm can ada…
cs.LG2019
The Futility of Bias-Free Learning and Search
George D. Montanez, Jonathan Hayase, Julius Lauw +3
Building on the view of machine learning as search, we demonstrate the necessity of bias in learning, quantifying the role of bias (measured relative to a collection of possible da…