sigproc.bib

@incollection{NIPS2012_4824,
	title = {ImageNet Classification with Deep Convolutional Neural Networks},
	author = {Alex Krizhevsky and Sutskever, Ilya and Geoffrey E. Hinton},
	booktitle = {Advances in Neural Information Processing Systems 25},
	editor = {F. Pereira and C.J.C. Burges and L. Bottou and K.Q. Weinberger},
	pages = {1097--1105},
	year = {2012},
	publisher = {Curran Associates, Inc.},
	url = {http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf}
}

@inproceedings{deng2009imagenet,
	title={Imagenet: A large-scale hierarchical image database},
	author={Deng, Jia and Dong, Wei and Socher, Richard and Li, Li-Jia and Li, Kai and Fei-Fei, Li},
	booktitle={Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on},
	pages={248--255},
	year={2009},
	organization={IEEE}
}

@inproceedings{lowe1999object,
	title={Object recognition from local scale-invariant features},
	author={Lowe, David G},
	booktitle={Computer vision, 1999. The proceedings of the seventh IEEE international conference on},
	volume={2},
	pages={1150--1157},
	year={1999},
	organization={Ieee}
}

@article{he2015deep,
	title={Deep Residual Learning for Image Recognition},
	author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
	journal={arXiv preprint arXiv:1512.03385},
	year={2015}
}
@article{ioffe2015batch,
	title={Batch normalization: Accelerating deep network training by reducing internal covariate shift},
	author={Ioffe, Sergey and Szegedy, Christian},
	journal={arXiv preprint arXiv:1502.03167},
	year={2015}
}
@inproceedings{nair2010rectified,
	title={Rectified linear units improve restricted boltzmann machines},
	author={Nair, Vinod and Hinton, Geoffrey E},
	booktitle={Proceedings of the 27th International Conference on Machine Learning (ICML-10)},
	pages={807--814},
	year={2010}
}
@inproceedings{glorot2010understanding,
	title={Understanding the difficulty of training deep feedforward neural networks},
	author={Glorot, Xavier and Bengio, Yoshua},
	booktitle={International conference on artificial intelligence and statistics},
	pages={249--256},
	year={2010}
}
@article{srivastava2014dropout,
	title={Dropout: A simple way to prevent neural networks from overfitting},
	author={Srivastava, Nitish and Hinton, Geoffrey and Krizhevsky, Alex and Sutskever, Ilya and Salakhutdinov, Ruslan},
	journal={The Journal of Machine Learning Research},
	volume={15},
	number={1},
	pages={1929--1958},
	year={2014},
	publisher={JMLR. org}
}
@article{chapelle2014simple,
	title={Simple and scalable response prediction for display advertising},
	author={Chapelle, Olivier and Manavoglu, Eren and Rosales, Romer},
	journal={ACM Transactions on Intelligent Systems and Technology (TIST)},
	volume={5},
	number={4},
	pages={61},
	year={2014},
	publisher={ACM}
}
@inproceedings{richardson2007predicting,
	title={Predicting clicks: estimating the click-through rate for new ads},
	author={Richardson, Matthew and Dominowska, Ewa and Ragno, Robert},
	booktitle={Proceedings of the 16th international conference on World Wide Web},
	pages={521--530},
	year={2007},
	organization={ACM}
}
@inproceedings{oentaryo2014predicting,
	title={Predicting response in mobile advertising with hierarchical importance-aware factorization machine},
	author={Oentaryo, Richard J and Lim, Ee-Peng and Low, Jia-Wei and Lo, David and Finegold, Michael},
	booktitle={Proceedings of the 7th ACM international conference on Web search and data mining},
	pages={123--132},
	year={2014},
	organization={ACM}
}
@inproceedings{rendle2010factorization,
	title={Factorization machines},
	author={Rendle, Steffen},
	booktitle={Data Mining (ICDM), 2010 IEEE 10th International Conference on},
	pages={995--1000},
	year={2010},
	organization={IEEE}
}

@inproceedings{azimi2012impact,
	title={The impact of visual appearance on user response in online display advertising},
	author={Azimi, Javad and Zhang, Ruofei and Zhou, Yang and Navalpakkam, Vidhya and Mao, Jianchang and Fern, Xiaoli},
	booktitle={Proceedings of the 21st international conference companion on World Wide Web},
	pages={457--458},
	year={2012},
	organization={ACM}
}
@inproceedings{cheng2012multimedia,
	title={Multimedia features for click prediction of new ads in display advertising},
	author={Cheng, Haibin and Zwol, Roelof van and Azimi, Javad and Manavoglu, Eren and Zhang, Ruofei and Zhou, Yang and Navalpakkam, Vidhya},
	booktitle={Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining},
	pages={777--785},
	year={2012},
	organization={ACM}
}
@inproceedings{Mo:2015:IFL:2832747.2832769,
	author = {Mo, Kaixiang and Liu, Bo and Xiao, Lei and Li, Yong and Jiang, Jie},
	title = {Image Feature Learning for Cold Start Problem in Display Advertising},
	booktitle = {Proceedings of the 24th International Conference on Artificial Intelligence},
	series = {IJCAI'15},
	year = {2015},
	isbn = {978-1-57735-738-4},
	location = {Buenos Aires, Argentina},
	pages = {3728--3734},
	numpages = {7},
	url = {http://dl.acm.org/citation.cfm?id=2832747.2832769},
	acmid = {2832769},
	publisher = {AAAI Press},
} 
@inproceedings{he2014practical,
	title={Practical lessons from predicting clicks on ads at facebook},
	author={He, Xinran and Pan, Junfeng and Jin, Ou and Xu and others},
	booktitle={Proceedings of 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining},
	pages={1--9},
	year={2014},
	organization={ACM}
}
@article{hinton2012deep,
	title={Deep neural networks for acoustic modeling in speech recognition: The shared views of four research groups},
	author={Hinton, Geoffrey and Deng, Li and Yu, Dong and Dahl, George E and Mohamed and others},
	journal={Signal Processing Magazine, IEEE},
	volume={29},
	number={6},
	pages={82--97},
	year={2012},
	publisher={IEEE}
}
@inproceedings{jia2014caffe,
	title={Caffe: Convolutional architecture for fast feature embedding},
	author={Jia, Yangqing and Shelhamer, Evan and Donahue, Jeff and Karayev, Sergey and Long, Jonathan and Girshick, Ross and Guadarrama, Sergio and Darrell, Trevor},
	booktitle={Proceedings of the ACM International Conference on Multimedia},
	pages={675--678},
	year={2014},
	organization={ACM}
}
@article{he2015delving,
	title={Delving deep into rectifiers: Surpassing human-level performance on imagenet classification},
	author={He, Kaiming and Zhang, Xiangyu and Ren, Shaoqing and Sun, Jian},
	journal={arXiv preprint arXiv:1502.01852},
	year={2015}
}
@incollection{zeiler2014visualizing,
	title={Visualizing and understanding convolutional networks},
	author={Zeiler, Matthew D and Fergus, Rob},
	booktitle={Computer Vision--ECCV 2014},
	pages={818--833},
	year={2014},
	publisher={Springer}
}
@article{simonyan2014very,
	title={Very deep convolutional networks for large-scale image recognition},
	author={Simonyan, Karen and Zisserman, Andrew},
	journal={arXiv preprint arXiv:1409.1556},
	year={2014}
}

@inproceedings{cheng2012multimedia,
	title={Multimedia features for click prediction of new ads in display advertising},
	author={Cheng, Haibin and Zwol, Roelof van and Azimi, Javad and Manavoglu, Ruofei and Zhou, Yang and Navalpakkam, Vidhya},
	booktitle={Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining},
	pages={777--785},
	year={2012},
	organization={ACM}
}
@inproceedings{chakrabarti2008contextual,
	title={Contextual advertising by combining relevance with click feedback},
	author={Chakrabarti, Deepayan and Agarwal, Deepak and Josifovski, Vanja},
	booktitle={Proceedings of the 17th international conference on World Wide Web},
	pages={417--426},
	year={2008},
	organization={ACM}
}
@inproceedings{dave2010learning,
	title={Learning the click-through rate for rare/new ads from similar ads},
	author={Dave, Kushal S and Varma, Vasudeva},
	booktitle={Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval},
	pages={897--898},
	year={2010},
	organization={ACM}
}

@article{zhang2016deep,
	title={Deep Learning over Multi-field Categorical Data: A Case Study on User Response Prediction},
	author={Zhang, Weinan and Du, Tianming and Wang, Jun},
	journal={arXiv preprint arXiv:1601.02376},
	year={2016}
}
@article{rendle2012factorization,
	title={Factorization machines with libFM},
	author={Rendle, Steffen},
	journal={ACM Transactions on Intelligent Systems and Technology (TIST)},
	volume={3},
	number={3},
	pages={57},
	year={2012},
	publisher={ACM}
}

@article{simonyan2013deep,
	title={Deep inside convolutional networks: Visualising image classification models and saliency maps},
	author={Simonyan, Karen and Vedaldi, Andrea and Zisserman, Andrew},
	journal={arXiv preprint arXiv:1312.6034},
	year={2013}
}

@inproceedings{ren2015faster,
	title={Faster R-CNN: Towards real-time object detection with region proposal networks},
	author={Ren, Shaoqing and He, Kaiming and Girshick, Ross and Sun, Jian},
	booktitle={Advances in Neural Information Processing Systems},
	pages={91--99},
	year={2015}
}

@inproceedings{simonyan2014two,
	title={Two-stream convolutional networks for action recognition in videos},
	author={Simonyan, Karen and Zisserman, Andrew},
	booktitle={Advances in Neural Information Processing Systems},
	pages={568--576},
	year={2014}
}

@inproceedings{weinberger2009feature,
	title={Feature hashing for large scale multitask learning},
	author={Weinberger, Kilian and Dasgupta, Anirban and Langford, John and Smola, Alex and Attenberg, Josh},
	booktitle={Proceedings of the 26th Annual International Conference on Machine Learning},
	pages={1113--1120},
	year={2009},
	organization={ACM}
}

@inproceedings{mcmahan2013ad,
	title={Ad click prediction: a view from the trenches},
	author={McMahan, H Brendan and Holt, Gary and Sculley, David and Young, Michael and Ebner, Dietmar and Grady, Julian and Nie, Lan and Phillips, Todd and Davydov, Eugene and Golovin, Daniel and others},
	booktitle={Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining},
	pages={1222--1230},
	year={2013},
	organization={ACM}
}

@inproceedings{mahdian2007pay,
	title={Pay-per-action model for online advertising},
	author={Mahdian, Mohammad and Tomak, Kerem},
	booktitle={Proceedings of the 1st international workshop on Data mining and audience intelligence for advertising},
	pages={1--6},
	year={2007},
	organization={ACM}
}

@inproceedings{mei2011internet,
	title={Internet multimedia advertising: techniques and technologies},
	author={Mei, Tao and Zhang, Ruofei and Hua, Xian-Sheng},
	booktitle={Proceedings of the 19th ACM international conference on Multimedia},
	pages={627--628},
	year={2011},
	organization={ACM}
}

@inproceedings{yan2014coupled,
	title={Coupled group lasso for web-scale ctr prediction in display advertising},
	author={Yan, Ling and Li, Wu-jun and Xue, Gui-Rong and Han, Dingyi},
	booktitle={Proceedings of the 31st International Conference on Machine Learning (ICML-14)},
	pages={802--810},
	year={2014}
}