Learning a Better Negative Sampling Policy with Deep Neural Networks for Search.

Daniel Cohen|Scott M. Jordan|W. Bruce Croft


Anthology ID:DBLP:conf/ictir/CohenJC19
Volume:Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval, ICTIR 2019, Santa Clara, CA, USA, October 2-5, 2019.
Year:2019
Venue:International Conference on the Theory of Information Retrieval (ICTIR)
Publisher:ACM
Pages:19-26
URL:https://doi.org/10.1145/3341981.3344220
DOI:https://doi.org/10.1145/3341981.3344220
DBLP:conf/ictir/CohenJC19
BibTeX:
@inproceedings{cohen-2019-learning, author = {Daniel Cohen and Scott M. Jordan and W. Bruce Croft}, editor = {Yi Fang and Yi Zhang and James Allan and Krisztian Balog and Ben Carterette and Jiafeng Guo}, title = {{Learning a Better Negative Sampling Policy with Deep Neural Networks for Search}}, booktitle = {{Proceedings of the 2019 ACM SIGIR International Conference on Theory of Information Retrieval, ICTIR 2019, Santa Clara, CA, USA, October 2-5, 2019}}, pages = {19--26}, publisher = {ACM}, year = {2019}, url = {https://doi.org/10.1145/3341981.3344220}, doi = {https://doi.org/10.1145/3341981.3344220} }