Timezone: »
Poster
Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples
Haw-Shiuan Chang · Erik Learned-Miller · Andrew McCallum
Self-paced learning and hard example mining re-weight training instances to improve learning accuracy. This paper presents two improved alternatives based on lightweight estimates of sample uncertainty in stochastic gradient descent (SGD): the variance in predicted probability of the correct class across iterations of mini-batch SGD, and the proximity of the correct class probability to the decision threshold. Extensive experimental results on six datasets show that our methods reliably improve accuracy in various network architectures, including additional gains on top of other popular training techniques, such as residual learning, momentum, ADAM, batch normalization, dropout, and distillation.
Author Information
Haw-Shiuan Chang (UMass, Amherst)
Erik Learned-Miller (UMass Amherst)
Andrew McCallum (UMass Amherst)
More from the Same Authors
-
2020 Poster: Improving Local Identifiability in Probabilistic Box Embeddings »
Shib Dasgupta · Michael Boratko · Dongxu Zhang · Luke Vilnis · Xiang Li · Andrew McCallum -
2019 Workshop: Sets and Partitions »
Nicholas Monath · Manzil Zaheer · Andrew McCallum · Ari Kobren · Junier Oliva · Barnabas Poczos · Ruslan Salakhutdinov -
2019 Poster: Search-Guided, Lightly-Supervised Training of Structured Prediction Energy Networks »
Amirmohammad Rooshenas · Dongxu Zhang · Gopal Sharma · Andrew McCallum -
2018 Poster: Compact Representation of Uncertainty in Clustering »
Craig Greenberg · Nicholas Monath · Ari Kobren · Patrick Flaherty · Andrew McGregor · Andrew McCallum -
2014 Workshop: 4th Workshop on Automated Knowledge Base Construction (AKBC) »
Sameer Singh · Fabian M Suchanek · Sebastian Riedel · Partha Pratim Talukdar · Kevin P Murphy · Christopher RĂ© · William Cohen · Tom Mitchell · Andrew McCallum · Jason E Weston · Ramanathan Guha · Boyan Onyshkevych · Hoifung Poon · Oren Etzioni · Ari Kobren · Arvind Neelakantan · Peter Clark -
2012 Poster: Learning to Align from Scratch »
Gary B Huang · Marwan A Mattar · Honglak Lee · Erik Learned-Miller -
2012 Poster: MAP Inference in Chains using Column Generation »
David Belanger · Alexandre T Passos · Sebastian Riedel · Andrew McCallum -
2011 Workshop: Big Learning: Algorithms, Systems, and Tools for Learning at Scale »
Joseph E Gonzalez · Sameer Singh · Graham Taylor · James Bergstra · Alice Zheng · Misha Bilenko · Yucheng Low · Yoshua Bengio · Michael Franklin · Carlos Guestrin · Andrew McCallum · Alexander Smola · Michael Jordan · Sugato Basu -
2011 Poster: Query-Aware MCMC »
Michael Wick · Andrew McCallum -
2009 Poster: FACTORIE: Probabilistic Programming via Imperatively Defined Factor Graphs »
Andrew McCallum · Karl Schultz · Sameer Singh -
2009 Poster: Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference »
Michael Wick · Khashayar Rohanimanesh · Sameer Singh · Andrew McCallum -
2009 Spotlight: Training Factor Graphs with Reinforcement Learning for Efficient MAP Inference »
Michael Wick · Khashayar Rohanimanesh · Sameer Singh · Andrew McCallum -
2009 Poster: Rethinking LDA: Why Priors Matter »
Hanna Wallach · David Mimno · Andrew McCallum -
2009 Spotlight: Rethinking LDA: Why Priors Matter »
Hanna Wallach · David Mimno · Andrew McCallum