Research
My long term research goal is to create a computational model of human intelligence. To this end, I am interested in:
Machine Learning: artificial neural networks (RBMs, DBNs, etc), convex/submodular optimization and active learning.
Neuroscience: neural substrates for decision making, network properties of neural systems, attentional modulation of visual recognition and long-term memory formation.
Computer Vision: invariant visual representation and video matching.
Selected Publications
Bo Chen, Jo-Anne Ting, Benjamin Marlin and Nando de Freitas. Deep Learning of Invariant Spatio-Temporal Features from Video. NIPS 2010 Deep Learning and Unsupervised Feature Learning Workshop PDF
Benjamin Marlin, Kevin Swersky, Bo Chen and Nando de Freitas. Inductive Principles for Restricted Boltzmann Machine Learning. AISTATS 2010 PDF
Talks
Deep Learning of Invariant Spatio-Temporal Features from Video, presented at MSc thesis defense and NIPS 2010 Deep Learning and Unsupervised Feature Learning Workshop, organized by Honglak Lee, Marc'Aurelio Ranzato, Yoshua Bengio, Geoff Hinton, Yan LeCun and Andrew Y. Ng [slides] [denoising video][spatial-temporal filters]
Learning Sparse Codes and Sparse Bases Jointly, presented at ICML09 Workshop on Learning Feature Hierarchies and CIFAR NCAP Summer School, 2009 [slides]
Full List of Publications
Bo Chen, Jo-Anne Ting, Benjamin Marlin and Nando de Freitas. Deep Learning of Invariant Spatio-Temporal Features from Video. NIPS 2010 Deep Learning and Unsupervised Feature Learning Workshop PDF
Benjamin Marlin, Kevin Swersky, Bo Chen and Nando de Freitas. Inductive Principles for Restricted Boltzmann Machine Learning. AISTATS 2010 PDF
Haiyang Wang, Jiangchuan Liu, Bo Chen, Ke Xu and Zhen Ma. On Tracker Selection for BitTorrent Traffic Locality. The IEEE International Conference on Peer-to-Peer Computing 2010 PDF
Bo Chen, Kevin Swersky, Benjamin Marlin and Nando de Freitas. Sparsity Priors and Boosting for Learning Localized Distributed Feature Representations. Technical Report TR-2010-04. University of British Columbia, Department of Computer Science PDF
Kevin Swersky, Bo Chen, Benjamin Marlin and Nando de Freitas. A Tutorial on Stochastic Approximation Algorithms for Training Restricted Boltzmann Machines and Deep Belief Nets. Information Theory and Applications (ITA) Workshop 2010 PDF
Bo Chen, Nhan Nyuyen and Greg Mori. Human Pose Estimation with Rotated
Geometric Blur, IEEE Workshop on Applications of Computer Vision (WACV), 2008 PDF
Bo Chen, William Pak Tun Ma, Yan Tan, Alexandra Fedorova and Greg Mori, GreenRT:
A Framework for the Design of Power-Aware Soft Real-Time Applications, Work-
shop on the Interaction between Operating Systems and Computer Architecture (WIOSCA),
2008 PDF
