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Invited Talk 3
Sepp Hochreiter
Sat Dec 09 11:15 AM -- 11:45 AM (PST) @
Author Information
Sepp Hochreiter (LIT AI Lab / University Linz)
Head of the LIT AI Lab and Professor of bioinformatics at the University of Linz. First to identify and analyze the vanishing gradient problem, the fundamental deep learning problem, in 1991. First author of the main paper on the now widely used LSTM RNNs. He implemented 'learning how to learn' (meta-learning) networks via LSTM RNNs and applied Deep Learning and RNNs to self-driving cars, sentiment analysis, reinforcement learning, bioinformatics, and medicine.
More from the Same Authors
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2021 : Modern Hopfield Networks for Return Decomposition for Delayed Rewards »
Michael Widrich · Markus Hofmarcher · Vihang Patil · Angela Bitto · Sepp Hochreiter -
2021 : Understanding the Effects of Dataset Composition on Offline Reinforcement Learning »
Kajetan Schweighofer · Markus Hofmarcher · Marius-Constantin Dinu · Philipp Renz · Angela Bitto · Vihang Patil · Sepp Hochreiter -
2017 : Panel: Machine learning and audio signal processing: State of the art and future perspectives »
Sepp Hochreiter · Bo Li · Karen Livescu · Arindam Mandal · Oriol Nieto · Malcolm Slaney · Hendrik Purwins -
2017 Spotlight: Self-Normalizing Neural Networks »
Günter Klambauer · Thomas Unterthiner · Andreas Mayr · Sepp Hochreiter -
2017 Poster: Self-Normalizing Neural Networks »
Günter Klambauer · Thomas Unterthiner · Andreas Mayr · Sepp Hochreiter -
2017 Poster: GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium »
Martin Heusel · Hubert Ramsauer · Thomas Unterthiner · Bernhard Nessler · Sepp Hochreiter -
2016 Symposium: Recurrent Neural Networks and Other Machines that Learn Algorithms »
Jürgen Schmidhuber · Sepp Hochreiter · Alex Graves · Rupesh K Srivastava -
2015 Poster: Rectified Factor Networks »
Djork-Arné Clevert · Andreas Mayr · Thomas Unterthiner · Sepp Hochreiter