Knowledge Discovery Lab

KDLab-AILab Paper Reading Group

Next Presentation:

Kevin Amaral.

Semester Schedule

Date Presenter
3/30/18 Zihan Li
4/6/18 Kevin Amaral
4/13/18 Yong Zhuang
4/20/18 Olga Andreeva
4/27/18 Chengjie Zheng
5/4/18 Matthew Almeida
5/11/18 Hefei Qiu
5/18/18 Hamid Reza Mohebbi

Past Presentations:

Thanks to Zihan Li for presenting Understanding Black-Box Predictions via Influence Functions on 3/30/18.

Thanks to Olga Andreeva and Kaixun Hua for presenting on 12/8. Olga's slides on Scalable Gaussian Processes are available here.

Thanks to Hamidreza Mohebbi for presenting research on Semi-supervised GAN on 10/13/17.

Thanks to Yong Zhuang for his presentation on WGAN on 10/6/17. His slides are available here.

Thanks, Carl Fakhry, for presenting original research on Distance Learning on 9/8/17.

Thanks to Matthew Almeida for presenting on Deep Convolutional and LSTM Recurrent Neural Networks for Multimodal Wearable Activity Recognition on 6/30/17.

Thanks to Yong Zhuang for presenting research on spacio-temporal RNN model methods. Slides

Thanks to Kevin Amaral for presenting his research on Mars crater detection on 6/16/17. Slides

Thanks to Matthew Almeida for presenting Overcoming Key Weaknesses of Distance-based Neighborhood Methods using a Data-Dependent Dissimilarity Measure on 1/27/17.

Thanks to Kevin Amaral for presenting his methods on the activity recognition project and an introduction to gaussian mixture models on 1/20/17

Thanks to Yahui Di and Zihan Li for presenting "Statistical approach to normalization of feature vectors and clustering of mixed datasets", by Mariam Suarez-Alvarez, Duc-Truong Pham, Mikhaily Prostov, and Yuriyi Prostov on 1/13/17.

Thank you, Tianyu Kang, for presenting "Why Should I Trust You?" Explaining the Results of Any Classifier, by Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin.

Thanks to Tong Wang for presenting Neural Machine Translation by Jointly Learning to Align and Translate, by Dzmitry Bahdanau, KyungHyun Cho, and Yoshua Bengio.

Many thanks to Carl Fakhry for his 10/7/16 presentation of a very interesting NIPS paper, Top-K Multiclass SVM, by
Maksim Lapin, Matthias Hein and Bernt Schiele.

Recommended Conferences in Machine Learning and Data Mining:

Data Mining ACM SIGKDD 17-Feb A+
Machine Learning ICML 24-Feb A+
NIPS 19-May A+
ICLR 14-Nov
AI AAAI 9-Sep A+
IJCAI 16-Feb A+
UAI 31-Mar A+
Knowledge Management SIGIR 17-Jan A+
CIKM 16-May A
NLP ACL 6-Feb A+
EMNLP 14-Apr A
Computer Vision ICCV 17-Mar A+
CVPR 15-Nov A