157 citations · 402 across the 21 of their papers we have counts for
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Uncertainty Sampling is Preconditioned Stochastic Gradient Descent on Zero-One Loss
Stephen Mussmann, Percy Liang
Uncertainty sampling, a popular active learning algorithm, is used to reduce the amount of data required to learn a classifier, but it has been observed in practice to converge to…
The price of debiasing automatic metrics in natural language evaluation
Arun Tejasvi Chaganty, Stephen Mussman, Percy Liang
For evaluating generation systems, automatic metrics such as BLEU cost nothing to run but have been shown to correlate poorly with human judgment, leading to systematic bias agains…
On the Relationship between Data Efficiency and Error for Uncertainty Sampling
Stephen Mussmann, Percy Liang
While active learning offers potential cost savings, the actual data efficiency---the reduction in amount of labeled data needed to obtain the same error rate---observed in practic…
Generalized Binary Search For Split-Neighborly Problems
Stephen Mussmann, Percy Liang
In sequential hypothesis testing, Generalized Binary Search (GBS) greedily chooses the test with the highest information gain at each step. It is known that GBS obtains the gold st…