- Efficient Inference in Fully Connected CRFs with Gaussian Edge Potentials, P. Krähenbühl, V. Koltun
- Fast and Accurate k-means For Large Datasets, M. Shindler, A. Wong, A. Meyerson
- Hashing Algorithms for Large-Scale Learning, P. Li, A. Shrivastava, J. Moore, A. König
- Hogwild: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent, B. Recht, C. Re, S. Wright, F. Niu
- Generalizing from Several Related Classification Tasks to a New Unlabeled Sample, G. Blanchard, G. Lee, C. Scott
- How biased are maximum entropy models? J. Macke, I. Murray, P. Latham
- On Tracking The Partition Function, G. Desjardins, A. Courville, Y. Bengio
- Selecting Receptive Fields in Deep Networks, A. Coates, A. Ng
- Shallow vs. Deep Sum-Product Networks, O. Delalleau, Y. Bengio
- Statistical Tests for Optimization Efficiency, L. Boyles, A. Korattikara, D. Ramanan, M. Welling
Monday, November 21, 2011
Interesting papers coming up at NIPS'11
There's a number of accepted papers whose camera-ready versions have been posted already. Here are the ones I found interesting. I'll give further update on these after the conference.
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25 comments:
Yaroslav,
Message passing algorithsms are also all the rage in compressive sensing where they are reaching and even crossing over certain limits thought to be unreacable before.
http://nuit-blanche.blogspot.com/2011/11/aspics-applying-statistical-physics-to.html
Cheers,
Igor.
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