Zobrazeno 1 - 10
of 11
pro vyhledávání: '"Yann N. Dauphin"'
Autor:
Charvi Rastogi, Ivan Stelmakh, Alina Beygelzimer, Yann N Dauphin, Percy Liang, Jennifer Wortman Vaughan, Zhenyu Xue, Hal Daumé Iii, Emma Pierson, Nihar B Shah
Publikováno v:
PLoS ONE, Vol 19, Iss 4, p e0300710 (2024)
How do author perceptions match up to the outcomes of the peer-review process and perceptions of others? In a top-tier computer science conference (NeurIPS 2021) with more than 23,000 submitting authors and 9,000 submitted papers, we surveyed the aut
Externí odkaz:
https://doaj.org/article/71cb7dcdf65a420d86a4fd1696eb9441
Publikováno v:
Computer Vision – ECCV 2020 ISBN: 9783030585259
ECCV (29)
ECCV (29)
Memorization in over-parameterized neural networks could severely hurt generalization in the presence of mislabeled examples. However, mislabeled examples are hard to avoid in extremely large datasets collected with weak supervision. We address this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0ac097ee890f1a2c7683226569929ac6
https://doi.org/10.1007/978-3-030-58526-6_33
https://doi.org/10.1007/978-3-030-58526-6_33
Publikováno v:
ACL (1)
Writers often rely on plans or sketches to write long stories, but most current language models generate word by word from left to right. We explore coarse-to-fine models for creating narrative texts of several hundred words, and introduce new models
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::236182242b3252f933b3349d08c4c57a
https://doi.org/10.18653/v1/p19-1254
https://doi.org/10.18653/v1/p19-1254
Publikováno v:
EMNLP/IJCNLP (1)
Previous work on neural noisy channel modeling relied on latent variable models that incrementally process the source and target sentence. This makes decoding decisions based on partial source prefixes even though the full source is available. We pur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e28244aeea12947a80f0dfba6436e88a
https://doi.org/10.18653/v1/d19-1571
https://doi.org/10.18653/v1/d19-1571
Publikováno v:
ACL (1)
We explore story generation: creative systems that can build coherent and fluent passages of text about a topic. We collect a large dataset of 300K human-written stories paired with writing prompts from an online forum. Our dataset enables hierarchic
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::afd950e78c95236ef91655c2e45b20fa
https://doi.org/10.18653/v1/p18-1082
https://doi.org/10.18653/v1/p18-1082
Autor:
Grégoire Mesnil, Li Deng, Dilek Hakkani-Tur, Gokhan Tur, Yann N. Dauphin, Geoffrey Zweig, Yoshua Bengio, Kaisheng Yao, Xiaodong He, Larry Heck, Dong Yu
Publikováno v:
IEEE/ACM Transactions on Audio, Speech, and Language Processing. 23:530-539
Semantic slot filling is one of the most challenging problems in spoken language understanding (SLU). In this paper, we propose to use recurrent neural networks (RNNs) for this task, and present several novel architectures designed to efficiently mod
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2b0c50a8e9351d076f44c0adab5f7717
https://doi.org/10.1109/taslp.2014.2383614
https://doi.org/10.1109/taslp.2014.2383614
Publikováno v:
EMNLP
Much of human dialogue occurs in semi-cooperative settings, where agents with different goals attempt to agree on common decisions. Negotiations require complex communication and reasoning skills, but success is easy to measure, making this an intere
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e4219eada52f68afc1e38ee6a560053
https://doi.org/10.18653/v1/d17-1259
https://doi.org/10.18653/v1/d17-1259
Publikováno v:
ACL (1)
The prevalent approach to neural machine translation relies on bi-directional LSTMs to encode the source sentence. In this paper we present a faster and simpler architecture based on a succession of convolutional layers. This allows to encode the ent
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::438b6ce2caa4f45bf394a3ac73b73b61
https://doi.org/10.18653/v1/p17-1012
https://doi.org/10.18653/v1/p17-1012
Autor:
Pascal Lamblin, Mehdi Mirza, Xavier Bouthillier, Pascal Vincent, Chris Pal, Caglar Gulcehre, Samira Ebrahimi Kahou, Pierre Froumenty, Kishore Konda, Vincent Michalski, Roland Memisevic, Raul Chandias Ferrari, Yoshua Bengio, David Warde-Farley, Nicolas Boulanger-Lewandowski, Sébastien Jean, Yann N. Dauphin, Aaron Courville
The task of the Emotion Recognition in the Wild (EmotiW) Challenge is to assign one of seven emotions to short video clips extracted from Hollywood style movies. The videos depict acted-out emotions under realistic conditions with a large degree of v
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::89ca1774c18a7a90585b043e11e57323
Autor:
Pascal Vincent, Jeremie Zumer, Sébastien Jean, Zhenzhou Wu, Jean-Philippe Raymond, Samira Ebrahimi Kahou, Roland Memisevic, Atousa Torabi, Yann N. Dauphin, Arjun Sharma, Myriam Côté, Aaron Courville, Guillaume Desjardins, Pierre Froumenty, Chris Pal, Pierre Luc Carrier, Kishore Konda, Raul Chandias Ferrari, Abhishek Aggarwal, David Warde-Farley, Yoshua Bengio, Emmanuel Bengio, Xavier Bouthillier, Pascal Lamblin, Nicolas Boulanger-Lewandowski, Razvan Pascanu, Mehdi Mirza, Caglar Gulcehre
Publikováno v:
ICMI
In this paper we present the techniques used for the University of Montreal's team submissions to the 2013 Emotion Recognition in the Wild Challenge. The challenge is to classify the emotions expressed by the primary human subject in short video clip
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::71d0622749d5e0b987be4e5b0b3e35ce
https://doi.org/10.1145/2522848.2531745
https://doi.org/10.1145/2522848.2531745