A new polynomial-time algorithm for linear programming
Combinatorica
A mathematical view of interior-point methods in convex optimization
A mathematical view of interior-point methods in convex optimization
Convex Optimization
The Journal of Machine Learning Research
Information Theory and Network Coding
Information Theory and Network Coding
A New Alternating Minimization Algorithm for Total Variation Image Reconstruction
SIAM Journal on Imaging Sciences
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3
Adaptive alternating minimization algorithms
IEEE Transactions on Information Theory
Squeezing the Arimoto-Blahut algorithm for faster convergence
IEEE Transactions on Information Theory
Coding for channels with cost constraints
IEEE Transactions on Information Theory
The capacity-cost function of discrete additive noise channels with and without feedback
IEEE Transactions on Information Theory
Geometric programming duals of channel capacity and rate distortion
IEEE Transactions on Information Theory
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The computation of channel capacity is a classical issue in information theory. We prove that algorithms based on self-concordant functions can be used to deal with such issues, especially when constrains are included. A new algorithm to compute the channel capacity per unit cost is proposed. The same view is suited to the computation of maximum entropy. All the algorithms are of polynomial time.