Uncertainty in Artificial Intelligence
First Name   Last Name   Password   Forgot Password   Log in!
    Proceedings         Authors   Author's Info   Article details         Search    
Cumulative distribution networks and the derivative-sum-product algorithm
Jim Huang, Brendan Frey
Abstract:
We introduce a new type of graphical model called a "cumulative distribution network" (CDN), which expresses a joint cumulative distribution as a product of local functions. Each local function can be viewed as providing evidence about possible orderings, or rankings, of variables. Interestingly, we find that the conditional independence properties of CDNs are quite different from other graphical models. We also describe a messagepassing algorithm that efficiently computes conditional cumulative distributions. Due to the unique independence properties of the CDN, these messages do not in general have a one-to-one correspondence with messages exchanged in standard algorithms, such as belief propagation. We demonstrate the application of CDNs for structured ranking learning using a previously-studied multi-player gaming dataset.
Keywords:
Pages: 290-297
PS Link:
PDF Link: /papers/08/p290-huang.pdf
BibTex:
@INPROCEEDINGS{Huang08,
AUTHOR = "Jim Huang and Brendan Frey",
TITLE = "Cumulative distribution networks and the derivative-sum-product algorithm",
BOOKTITLE = "Proceedings of the Twenty-Fourth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-08)",
PUBLISHER = "AUAI Press",
ADDRESS = "Corvallis, Oregon",
YEAR = "2008",
PAGES = "290--297"
}


hosted by DSL   •   site info   •   help