Seuraa
Andrew L. Maas
Andrew L. Maas
Vahvistettu sähköpostiosoite verkkotunnuksessa cs.stanford.edu - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
Rectifier nonlinearities improve neural network acoustic models
AL Maas, AY Hannun, AY Ng
Proc. icml 30 (1), 3, 2013
88932013
Learning word vectors for sentiment analysis
A Maas, RE Daly, PT Pham, D Huang, AY Ng, C Potts
Proceedings of the 49th annual meeting of the association for computational …, 2011
54472011
Maximum entropy inverse reinforcement learning.
BD Ziebart, AL Maas, JA Bagnell, AK Dey
Aaai 8, 1433-1438, 2008
32552008
Recurrent neural networks for noise reduction in robust ASR
A Maas, QV Le, TM O’neil, O Vinyals, P Nguyen, AY Ng
4172012
Navigate like a cabbie: Probabilistic reasoning from observed context-aware behavior
BD Ziebart, AL Maas, AK Dey, JA Bagnell
Proceedings of the 10th international conference on Ubiquitous computing …, 2008
3962008
First-pass large vocabulary continuous speech recognition using bi-directional recurrent dnns
AY Hannun, AL Maas, D Jurafsky, AY Ng
arXiv preprint arXiv:1408.2873, 2014
2012014
Lexicon-Free Conversational Speech Recognition with Neural Networks
AL Maas, Z Xie, D Jurafsky, AY Ng
North American Chapter of the Association for Computational Linguistics (NAACL), 2015
1802015
Building DNN acoustic models for large vocabulary speech recognition
AL Maas, P Qi, Z Xie, AY Hannun, CT Lengerich, D Jurafsky, AY Ng
Computer Speech & Language 41, 195-213, 2017
1782017
Human Behavior Modeling with Maximum Entropy Inverse Optimal Control.
BD Ziebart, AL Maas, JA Bagnell, AK Dey
AAAI Spring Symposium: Human Behavior Modeling 92, 2009
792009
Methods, apparatus and systems for annotation of text documents
C Potts, E Lin, A Maas, A Itharaju, K Reschke, J Vincent
US Patent 11,263,391, 2022
742022
A probabilistic model for semantic word vectors
AL Maas, AY Ng
NIPS Workshop on Deep Learning and Unsupervised Feature Learning, 1-8, 2010
682010
Offering verified credentials in massive open online courses: Moocs and technology to advance learning and learning research (ubiquity symposium)
A Maas, C Heather, C Do, R Brandman, D Koller, A Ng
Ubiquity 2014 (May), 1-11, 2014
552014
Spectral chinese restaurant processes: Nonparametric clustering based on similarities
R Socher, A Maas, C Manning
Proceedings of the Fourteenth International Conference on Artificial …, 2011
542011
Retrofitting distributional embeddings to knowledge graphs with functional relations
BJ Lengerich, AL Maas, C Potts
arXiv preprint arXiv:1708.00112, 2017
372017
Sentiment expression conditioned by affective transitions and social forces
M Sudhof, A Goméz Emilsson, AL Maas, C Potts
Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014
362014
Word-level acoustic modeling with convolutional vector regression
AL Maas, SD Miller, TM O’neil, AY Ng, P Nguyen
Proc. ICML Workshop Representation Learn, 2012
362012
Unsupervised feature learning and deep learning
A Ng, J Ngiam, CY Foo, Y Mai, C Suen, A Coates, A Maas, A Hannun, ...
Technical report, Stanford University, 2013
322013
Recurrent neural network feature enhancement: The 2nd CHiME challenge
AL Maas, TM O’Neil, AY Hannun, AY Ng
Proceedings The 2nd CHiME Workshop on Machine Listening in Multisource …, 2013
302013
Sequence to sequence transformations for speech synthesis via recurrent neural networks
DLW Hall, D Klein, D Roth, L Gillick, A Maas, S Wegmann
US Patent App. 15/792,236, 2018
212018
One-shot learning with bayesian networks
A Maas, C Kemp
Carnegie Mellon University, 2009
202009
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Artikkelit 1–20