Recent NewsSept 08, 2015 - Two NIPS '15 papers accepted.
More details coming up soon.
Sept 01, 2015 - Two ICCV '15 papers accepted.
The paper "Semantically-Aware Aerial Reconstruction from Multi-Modal Data", by Randi Cabezas, Julian Straub and John W. Fisher III, and the paper "Highly-Expressive Spaces of Well-Behaved Transformations: Keeping it Simple", by Oren Freifeld, Søren Hauberg, Kayhan Batmanghelich and John W. Fisher III, were accepted to ICCV '15.
May 12, 2015 - A UAI '15 paper accepted.
Work by Liu, Peng, Ihler, and Fisher on "Estimating the Partition Function by Discriminance Sampling" was accepted to UAI '15.
May 06, 2015 - Fusion '15 paper accepted
Giorgos Papachristoudis' work "Efficient Information Planning in Gaussian MRFs" has been accepted to the 18th International Conference on Information Fusion (Fusion '15).
May 06, 2015 - ICML '15 paper accepted
Giorgos Papachristoudis' work "Adaptive Belief Propagation" has been accepted to the 32nd International Conference on Machine Learning (ICML '15).
Apr 30, 2015 - ICIP '15 paper accepted (Oral Presentation)
Work by Oren Freifeld, Yixin Li and John W. Fisher III proposing "A Fast Method for Inferring High-Quality Simply-Connected Superpixels" was accepted to ICIP '15.
Apr 09, 2015 - CVPR '15 Paper Accepted (Oral Presentation)
Work by Julian Straub, Trevor Campbell, Jonathan P. How and John W. Fisher III proposing two novel algorithms for "small-variance nonparametric clustering on the hypersphere" was accepted as an oral presentation at CVPR '15.
Jan 26, 2015 - AISTATS '15 Paper Accepted (Oral Presentation)
Work by Julian Straub, Jason Chang, Oren Freifeld and John W. Fisher III proposing "A Dirichlet Process Mixture Model for Spherical Data" was accepted as an oral presentation at AISTATS '15.
Jan 14, 2015 - ICASSP '15 paper accepted
Giorgos Papachristoudis' work "On the Complexity of Information Planning in Gaussian Models" has been accepted to the 40th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP '15).
About SLIOur group focuses on the analysis of complex, high-dimensional data. We combine elements of Bayesian inference, information theory, optimization, and physical sensor models to develop scalable algorithms with theoretical performance guarantees. Application areas include multi-modal data fusion, distributed inference under resource constraints, structural inference, resource management in sensor networks, and analysis of video, seismic volumes, and radar images.
Group Dinner - 05/20/2014
Left to Right: Oren Freifeld, Sue Zheng, Giorgos Papachristoudis, Guy Rosman, Christopher Dean, Jason Chang, Julian Straub, Randi Cabezas, John Fisher, Hossein Mobahi, Bonny Jain.