24 citations · 80 across the 13 of their papers we have counts for
4 papers · 1 filter
SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning
Albert Zhao, Tong He, Yitao Liang +3
We describe a policy learning approach to map visual inputs to driving controls conditioned on turning command that leverages side tasks on semantics and object affordances via a l…
On Tractable Computation of Expected Predictions
Pasha Khosravi, YooJung Choi, Yitao Liang +2
Computing expected predictions of discriminative models is a fundamental task in machine learning that appears in many interesting applications such as fairness, handling missing v…
What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features
Pasha Khosravi, Yitao Liang, YooJung Choi +1
While discriminative classifiers often yield strong predictive performance, missing feature values at prediction time can still be a challenge. Classifiers may not behave as expect…
Learning Logistic Circuits
Yitao Liang, Guy Van den Broeck
This paper proposes a new classification model called logistic circuits. On MNIST and Fashion datasets, our learning algorithm outperforms neural networks that have an order of mag…