Recent NewsMay 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).
Nov 21, 2014 - AAAI'15 Paper Accepted (Oral Presentation)
Hossein Mobahi's paper on "A Theoretical Analysis of Optimization by Gaussian Continuation" accepted to 29th Conference on Artificial Intelligence (AAAI-15).
Oct 20, 2014 - Two Papers Accepted to EMMCVPR'2015
Hossein's papers titled "On the Link Between Gaussian Homotopy Continuation and Convex Envelopes" and "Coarse-to-Fine Minimization of Some Common Nonconvexities" are accepted to EMMCVPR'2015.
Oct 04, 2014 - NIPS '14 Papers Accepted
Jason Chang's work on "MCMC Sampling in HDPs using Sub-Clusters" and Guy Rosman's work on "Coresets for k-Segmentation of Streaming Data" have been accepted to the annual Neural Information Processing Systems (NIPS '14) conference.
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.