Michael Tschannen

According to our database1, Michael Tschannen authored at least 33 papers between 2012 and 2018.

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Bibliography

2018
Noisy Subspace Clustering via Matching Pursuits.
IEEE Trans. Information Theory, 2018

Deep Generative Models for Distribution-Preserving Lossy Compression.
CoRR, 2018

Born Again Neural Networks.
CoRR, 2018

Generative Adversarial Networks for Extreme Learned Image Compression.
CoRR, 2018

Towards Image Understanding from Deep Compression without Decoding.
CoRR, 2018

Conditional Probability Models for Deep Image Compression.
CoRR, 2018

StrassenNets: Deep Learning with a Multiplication Budget.
Proceedings of the 35th International Conference on Machine Learning, 2018

Born-Again Neural Networks.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
StrassenNets: Deep learning with a multiplication budget.
CoRR, 2017

Convolutional Recurrent Neural Networks for Electrocardiogram Classification.
CoRR, 2017

Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees.
CoRR, 2017

A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe.
CoRR, 2017

Soft-to-Hard Vector Quantization for End-to-End Learned Compression of Images and Neural Networks.
CoRR, 2017

Greedy Algorithms for Cone Constrained Optimization with Convergence Guarantees.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Soft-to-Hard Vector Quantization for End-to-End Learning Compressible Representations.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Deep structured features for semantic segmentation.
Proceedings of the 25th European Signal Processing Conference, 2017

Convolutional Recurrent Neural Networks for Electrocardiogram Classification.
CinC, 2017

A Unified Optimization View on Generalized Matching Pursuit and Frank-Wolfe.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Regression forest-based automatic estimation of the articular margin plane for shoulder prosthesis planning.
Medical Image Analysis, 2016

Discrete Deep Feature Extraction: A Theory and New Architectures.
CoRR, 2016

Deep Structured Features for Semantic Segmentation.
CoRR, 2016

Noisy subspace clustering via matching pursuits.
CoRR, 2016

Robust nonparametric nearest neighbor random process clustering.
CoRR, 2016

Pursuits in Structured Non-Convex Matrix Factorizations.
CoRR, 2016

Discrete Deep Feature Extraction: A Theory and New Architectures.
Proceedings of the 33nd International Conference on Machine Learning, 2016

Heart Sound Classification Using Deep Structured Features.
Proceedings of the Computing in Cardiology, CinC 2016, Vancouver, 2016

2015
Nonparametric Nearest Neighbor Random Process Clustering.
CoRR, 2015

Dimensionality-reduced subspace clustering.
CoRR, 2015

Nonparametric nearest neighbor random process clustering.
Proceedings of the IEEE International Symposium on Information Theory, 2015

2014
Subspace clustering of dimensionality-reduced data.
CoRR, 2014

Subspace clustering of dimensionality-reduced data.
Proceedings of the 2014 IEEE International Symposium on Information Theory, Honolulu, HI, USA, June 29, 2014

2013
A Learning-Based Approach for Fast and Robust Vessel Tracking in Long Ultrasound Sequences.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013

2012
Single Marker Localization for Automatic Patient Registration in Interventional Radiology.
Proceedings of the 11. Jahrestagung der Deutschen Gesellschaft für Computer- und Roboterassistierte Chirurgie, 2012


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