37 citations · 138 across the 12 of their papers we have counts for
7 papers · 1 filter
Iterative Teaching by Data Hallucination
Zeju Qiu, Weiyang Liu, Tim Z. Xiao +5
We consider the problem of iterative machine teaching, where a teacher sequentially provides examples based on the status of a learner under a discrete input space (i.e., a pool of…
Learning Counterfactually Invariant Predictors
Francesco Quinzan, Cecilia Casolo, Krikamol Muandet +2
Notions of counterfactual invariance (CI) have proven essential for predictors that are fair, robust, and generalizable in the real world. We propose graphical criteria that yield…
SUMO: Unbiased Estimation of Log Marginal Probability for Latent Variable Models
Yucen Luo, Alex Beatson, Mohammad Norouzi +4
Standard variational lower bounds used to train latent variable models produce biased estimates of most quantities of interest. We introduce an unbiased estimator of the log margin…
Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structure
Zhijie Deng, Yucen Luo, Jun Zhu +1
Bayesian neural networks (BNNs) augment deep networks with uncertainty quantification by Bayesian treatment of the network weights. However, such models face the challenge of Bayes…
A Simple yet Effective Baseline for Robust Deep Learning with Noisy Labels
Yucen Luo, Jun Zhu, Tomas Pfister
Recently deep neural networks have shown their capacity to memorize training data, even with noisy labels, which hurts generalization performance. To mitigate this issue, we provid…
Smooth Neighbors on Teacher Graphs for Semi-supervised Learning
Yucen Luo, Jun Zhu, Mengxi Li +2
The recently proposed self-ensembling methods have achieved promising results in deep semi-supervised learning, which penalize inconsistent predictions of unlabeled data under diff…
Conditional Generative Moment-Matching Networks
Yong Ren, Jialian Li, Yucen Luo +1
Maximum mean discrepancy (MMD) has been successfully applied to learn deep generative models for characterizing a joint distribution of variables via kernel mean embedding. In this…