Knowledge Discovery Lab

KDLab-AILab Paper Reading Group

Next Presentation (2/3/17):

Yong Zhuang will present an overview of sequence-to-sequence neural network learning methods, culminating in the Convolutional LSTM architecture he is working with in his research project.

Semester Schedule:

Date Kevin Matthew Yong Tianyu Yahui Zihan Zheyun Tong
Fri 1/20 VGBMM
Fri 1/27 OKWDNM
Fri 2/3 CLSTM
Fri 2/10
Fri 2/17 RSCLDA
Fri 2/24  Paper
Fri 3/3 Paper
Fri 3/10  Paper
Fri 3/17
Fri 3/24  Paper
Fri 3/31 Paper
Fri 4/7  Paper
Fri 4/14 Paper
Fri 4/21  Paper
Fri 4/28  Paper
Fri 5/5  Paper
Fri 5/12  Paper
Fri 5/19  Paper

Past Presentations:

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.