Srinivas M. Aji and Robert J. McEliece. The generalized distributive law. IEEE Transactions on Information Theory, 46(2):325--343, 2000. Home/Search Document Not in Database Summary Related Articles Check |
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Embedded Trees: Estimation of Gaussian Processes on.. - Sudderth, Wainwright, .. (2002) (3 citations) (Correct)
....to exactly compute p (x s y) in ) operations. For example, when the potentials are specified by a state space model, a standard Kalman filter may be combined with a complementary reverse time recursion [6] These algorithms may be directly generalized to any graph which contains no cycles [8, 14, 19, 20]. We refer to such graphs as tree structured. Tree based inference algorithms use a series of local message passing operations to exchange statistical information between neighboring nodes. One of the most popular such methods is known as the sum product [19] or belief propagation (BP) 14] ....
S. M. Aji and R. J. McEliece. The generalized distributive law. IEEE Transactions on Information Theory, 46(2):325--343, March 2000.
Correctness of belief propagation in Gaussian graphical.. - Weiss, Freeman (1999) (32 citations) (Correct)
....an undirected graph with pairwise cliques [24] For particular graphs with particular settings of the potentials, Equs. 4 5 yield other well known Bayesian inference algorithms, such as the forward backward algorithm in Hidden Markov Models, the Kalman Filter and even the Fast Fourier Transform [1, 13]. A related algorithm, max product , changes the integration in equation 4 to a maximization. This message passing is equivalent to Pearl s belief revision algorithm in directed graphs. For particular graphs with particular settings of the potentials, the max product algorithm is equivalent to ....
S. M. Aji and R.J. McEliece. The generalized distributive law. IEEE Transactions on Information Theory, 1999. to appear.
A Computational Taxonomy and Survey of Neural Network Models - Sima, Orponen (2001) (1 citation) (Correct)
.... has been shown that there are on the average asymptotically 1:05 2 0:2874s many stable states in a binary Hop eld net of size s whose feedbacks and biases are zero (w jj = w j0 = 0 for j 2 V ) and whose other weights are independent identically distributed zero mean Gaussian random variables [84], 131] For a particular binary symmetric network, however, the issue of deciding whether there are e.g. at least one (when negative feedback weights are allowed) 24] two [66] or three [24] stable states, is NP complete. Indeed, the problem of determining the exact number of stable states for ....
R.J. McEliece, E.C. Posner, E.R. Rodemich, and S.S. Venkatesh, The capacity of the Hopeld associative memory, IEEE Transactions on Information Theory 33 (4) (1987) 461-482.
The Computational Theory of Neural Networks - Sima (2000) (Correct)
....memory, is important. It has been shown that in average there are asymptotically 1:05 2 0:2874s many stable states in binary Hop eld nets of size s, with zero feedbacks and biases (w jj = w j0 = 0 for j 2 V ) whose other weights are independent identically zero mean Gaussian random variables [82, 126]. For a particular binary symmetric network, however, the issue of deciding whether there are e.g. at least one (when negative feedback weights are allowed) 23] two [64] or three [23] stable states, is NP complete. Indeed, the problem of determining the exact number of stable states for a given ....
R.J. McEliece, E.C. Posner, E.R. Rodemich, and S.S. Venkatesh, The capacity of the Hopeld associative memory, IEEE Transactions on Information Theory 33 (4) (1987) 461-482.
Correctness of belief propagation in Gaussian graphical.. - Weiss, Freeman (1999) (32 citations) (Correct)
....an undirected graph with pairwise cliques [24] For particular graphs with particular settings of the potentials, Equs. 4 5 yield other well known Bayesian inference algorithms, such as the forward backward algorithm in Hidden Markov Models, the Kalman Filter and even the Fast Fourier Transform [1, 13]. A related algorithm, max product , changes the integration in equation 4 to a maximization. This message passing is equivalent to Pearl s belief revision algorithm in directed graphs. For particular graphs with particular settings of the potentials, the max product algorithm is equivalent to ....
S. M. Aji and R.J. McEliece. The generalized distributive law. IEEE Transactions on Information Theory, 1999. to appear.
Scalable Inference in Hierarchical Generative Models - Dean (2005) (Correct)
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Srinivas M. Aji and Robert J. McEliece. The generalized distributive law. IEEE Transactions on Information Theory, 46(2):325--343, 2000.
A Robust Architecture for - Distributed Inference In (Correct)
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Aji, S. M., and McEliece, R. J. The generalized distributive law. IEEE Transactions on Information Theory 46 (March 2000), 325--343.
Exact Bayesian Structure Discovery in Bayesian Networks - Koivisto, Sood (2004) (1 citation) (Correct)
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S. M. Aji and R. J. McEliece. The generalized distributive law. IEEE Transactions on Information Theory, 46(2):325--343, 2000.
Merl A Mitsubishi Electric Research Laboratory - Http Www Merl (1999) (Correct)
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References #1# S. M. Aji and R.J. McEliece. The generalized distributivelaw. IEEE Transactions on Information Theory, 2000. in press. #2# S.M. Aji, G.B. Horn, and R.J. McEliece. On the convergence of iterative decoding on graphs with a single cycle. In Proc. 1998 ISIT, 1998.
Scalable Inference in Hierarchical Generative Models - Dean (Correct)
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Srinivas M. Aji and Robert J. McEliece. The generalized distributive law. IEEE Transactions on Information Theory, 46(2):325--343, 2000.
A Robust Architecture for Distributed Inference in Sensor.. - Paskin, Guestrin (2003) (2 citations) (Correct)
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Aji, S. M., and McEliece, R. J. The generalized distributive law. IEEE Transactions on Information Theory 46 (March 2000), 325--343.
A Robust Architecture for Distributed Inference in Sensor.. - Paskin, Guestrin (2003) (2 citations) (Correct)
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Aji, S. M., and McEliece, R. J. The generalized distributive law. IEEE Transactions on Information Theory 46 (March 2000), 325--343.
Codes and Iterative Receivers for Wireless Communication Systems - Worthen (2001) (2 citations) (Correct)
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S. M. Aji and R. J. McEliece, \The generalized distributive law," IEEE Transactions on Information Theory, vol. 46, no. 2, pp. 325-349, March 2000.
Extended Message Passing Algorithm for Inference in Loopy.. - Plarre, Kumar (2002) (6 citations) (Correct)
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S. M. Aji, J. McEliece, The generalized distributive law, IEEE Transactions on Information Theory 46 (1999) 325-343.
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