2009 |
12 | EE | Sadaf Abdul-Rauf,
Holger Schwenk:
On the Use of Comparable Corpora to Improve SMT performance.
EACL 2009: 16-23 |
2008 |
11 | EE | Evgeny Matusov,
Gregor Leusch,
Rafael E. Banchs,
Nicola Bertoldi,
Daniel Dechelotte,
M. Federico,
M. Kolss,
Young-Suk Lee,
José B. Mariño,
M. Paulik,
Salim Roukos,
Holger Schwenk,
Hermann Ney:
System Combination for Machine Translation of Spoken and Written Language.
IEEE Transactions on Audio, Speech & Language Processing 16(7): 1222-1237 (2008) |
2007 |
10 | EE | Holger Schwenk:
Continuous space language models.
Computer Speech & Language 21(3): 492-518 (2007) |
2006 |
9 | EE | Holger Schwenk,
Daniel Dechelotte,
Jean-Luc Gauvain:
Continuous Space Language Models for Statistical Machine Translation.
ACL 2006 |
8 | EE | Lori Lamel,
Eric Bilinski,
Gilles Adda,
Jean-Luc Gauvain,
Holger Schwenk:
The LIMSI RT06s Lecture Transcription System.
MLMI 2006: 457-468 |
7 | EE | Spyridon Matsoukas,
Jean-Luc Gauvain,
Gilles Adda,
T. Colthurst,
Chia-Lin Kao,
Owen Kimball,
Lori Lamel,
Fabrice Lefevre,
J. Z. Ma,
John Makhoul,
Long Nguyen,
Rohit Prasad,
Richard M. Schwartz,
Holger Schwenk,
Bing Xiang:
Advances in transcription of broadcast news and conversational telephone speech within the combined EARS BBN/LIMSI system.
IEEE Transactions on Audio, Speech & Language Processing 14(5): 1541-1556 (2006) |
2005 |
6 | EE | Holger Schwenk,
Jean-Luc Gauvain:
Training Neural Network Language Models on Very Large Corpora.
HLT/EMNLP 2005 |
2000 |
5 | | Holger Schwenk,
Yoshua Bengio:
Boosting Neural Networks.
Neural Computation 12(8): 1869-1887 (2000) |
1998 |
4 | | Holger Schwenk:
The Diabolo Classifier.
Neural Computation 10(8): 2175-2200 (1998) |
1997 |
3 | | Holger Schwenk,
Yoshua Bengio:
AdaBoosting Neural Networks: Application to on-line Character Recognition.
ICANN 1997: 967-972 |
2 | | Holger Schwenk,
Yoshua Bengio:
Training Methods for Adaptive Boosting of Neural Networks.
NIPS 1997 |
1994 |
1 | EE | Holger Schwenk,
Maurice Milgram:
Transformation Invariant Autoassociation with Application to Handwritten Character Recognition.
NIPS 1994: 992-998 |