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Jason K. Johnson
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2010 – 2019
- 2016
- [j5]Jason K. Johnson, Diane Oyen, Michael Chertkov, Praneeth Netrapalli:
Learning Planar Ising Models. J. Mach. Learn. Res. 17: 215:1-215:26 (2016) - 2013
- [c10]Shrinivas Kudekar, Jason K. Johnson, Misha Chertkov
:
Improved linear programming decoding using frustrated cycles. ISIT 2013: 1496-1500 - 2011
- [c9]Shrinivas Kudekar, Jason K. Johnson, Michael Chertkov
:
Linear programming based detectors for two-dimensional intersymbol interference channels. ISIT 2011: 2999-3003 - [i6]Shrinivas Kudekar, Jason K. Johnson, Michael Chertkov:
Linear Programming based Detectors for Two-Dimensional Intersymbol Interference Channels. CoRR abs/1102.5386 (2011) - [i5]Shrinivas Kudekar, Jason K. Johnson, Michael Chertkov:
Improved Linear Programming Decoding using Frustrated Cycles. CoRR abs/1105.4665 (2011) - 2010
- [c8]Jason K. Johnson, Michael Chertkov
:
A majorization-minimization approach to design of power transmission networks. CDC 2010: 3996-4003 - [i4]Jason K. Johnson, Michael Chertkov:
A Majorization-Minimization Approach to Design of Power Transmission Networks. CoRR abs/1004.2285 (2010) - [i3]Jason K. Johnson, Praneeth Netrapalli, Michael Chertkov:
Learning Planar Ising Models. CoRR abs/1011.3494 (2010)
2000 – 2009
- 2009
- [c7]Jason K. Johnson, Vladimir Y. Chernyak, Michael Chertkov
:
Orbit-product representation and correction of Gaussian belief propagation. ICML 2009: 473-480 - [c6]Danny Dolev, Danny Bickson, Jason K. Johnson:
Fixing convergence of Gaussian belief propagation. ISIT 2009: 1674-1678 - [i2]Jason K. Johnson, Danny Bickson, Danny Dolev:
Fixing Convergence of Gaussian Belief Propagation. CoRR abs/0901.4192 (2009) - 2008
- [b1]Jason K. Johnson:
Convex relaxation methods for graphical models: Lagrangian and maximum entropy approaches. Massachusetts Institute of Technology, Cambridge, MA, USA, 2008 - [j4]Jason K. Johnson, Alan S. Willsky:
A Recursive Model-Reduction Method for Approximate Inference in Gaussian Markov Random Fields. IEEE Trans. Image Process. 17(1): 70-83 (2008) - [j3]Venkat Chandrasekaran, Jason K. Johnson, Alan S. Willsky:
Estimation in Gaussian Graphical Models Using Tractable Subgraphs: A Walk-Sum Analysis. IEEE Trans. Signal Process. 56(5): 1916-1930 (2008) - [j2]Dmitry M. Malioutov, Jason K. Johnson, Myung Jin Choi, Alan S. Willsky:
Low-Rank Variance Approximation in GMRF Models: Single and Multiscale Approaches. IEEE Trans. Signal Process. 56(10-1): 4621-4634 (2008) - 2007
- [c5]Dmitry M. Malioutov, Jason K. Johnson, Alan S. Willsky:
GMRF Variance Approximation using Splicedwavelet Bases. ICASSP (3) 2007: 1101-1104 - [c4]Venkat Chandrasekaran, Jason K. Johnson, Alan S. Willsky:
Adaptive Embedded Subgraph Algorithms using Walk-Sum Analysis. NIPS 2007: 249-256 - [c3]Jason K. Johnson, Venkat Chandrasekaran, Alan S. Willsky:
Learning Markov Structure by Maximum Entropy Relaxation. AISTATS 2007: 203-210 - [i1]Jason K. Johnson, Dmitry M. Malioutov, Alan S. Willsky:
Lagrangian Relaxation for MAP Estimation in Graphical Models. CoRR abs/0710.0013 (2007) - 2006
- [j1]Dmitry M. Malioutov, Jason K. Johnson, Alan S. Willsky:
Walk-Sums and Belief Propagation in Gaussian Graphical Models. J. Mach. Learn. Res. 7: 2031-2064 (2006) - [c2]Dmitry M. Malioutov, Jason K. Johnson, Alan S. Willsky:
Low-Rank Variance Estimation in Large-Scale Gmrf Models. ICASSP (3) 2006: 676-679 - 2005
- [c1]Jason K. Johnson, Dmitry M. Malioutov, Alan S. Willsky:
Walk-Sum Interpretation and Analysis of Gaussian Belief Propagation. NIPS 2005: 579-586
Coauthor Index

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