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10 papers · 2 filters
Angular Visual Hardness
Beidi Chen, Weiyang Liu, Zhiding Yu +4
Recent convolutional neural networks (CNNs) have led to impressive performance but often suffer from poor calibration. They tend to be overconfident, with the model confidence not…
MANGA: Method Agnostic Neural-policy Generalization and Adaptation
Homanga Bharadhwaj, Shoichiro Yamaguchi, Shin-ichi Maeda
In this paper we target the problem of transferring policies across multiple environments with different dynamics parameters and motor noise variations, by introducing a framework…
A Programmable Approach to Neural Network Compression
Vinu Joseph, Saurav Muralidharan, Animesh Garg +2
Deep neural networks (DNNs) frequently contain far more weights, represented at a higher precision, than are required for the specific task which they are trained to perform. Conse…
Quantum Optical Experiments Modeled by Long Short-Term Memory
Thomas Adler, Manuel Erhard, Mario Krenn +3
We demonstrate how machine learning is able to model experiments in quantum physics. Quantum entanglement is a cornerstone for upcoming quantum technologies such as quantum computa…
Causal Modeling for Fairness in Dynamical Systems
Elliot Creager, David Madras, Toniann Pitassi +1
In many application areas---lending, education, and online recommenders, for example---fairness and equity concerns emerge when a machine learning system interacts with a dynamical…
Towards Realistic Individual Recourse and Actionable Explanations in Black-Box Decision Making Systems
Shalmali Joshi, Oluwasanmi Koyejo, Warut Vijitbenjaronk +2
Machine learning based decision making systems are increasingly affecting humans. An individual can suffer an undesirable outcome under such decision making systems (e.g. denied cr…