Dear Colleague, [Apologies for multiple postings.]
We are pleased to announce that the deadline for submitting solvers to the 2016 UAI Probabilistic Inference Evaluation has been extended to October 31, 2016. In this evaluation, we will evaluate inference algorithms for discrete probabilistic graphical models. The evaluation/competition has been held every two years over the past 10 years at UAI, starting in 2006. Details about how to submit inference solvers/software, input and output formats can be found on the evaluation webpage given below: http://www.hlt.utdallas.edu/~vgogate/uai16-evaluation/ The evaluation is already underway and you can see the initial results below: http://www.hlt.utdallas.edu/~vgogate/uai16-evaluation/tuning.html This year we will evaluate solvers for the following tasks: (1) Probability of Evidence or Partition Function Computation (PR task or sum-product task) (2) Marginal Probability Estimation (MAR task or ratio-sum-product task) (3) Maximum a Posteriori Estimation (MAP task or max-product task) (4) Marginal Maximum a Posteriori Estimation (MMAP task or max-sum-product task) New this year. This year we are introducing two additional file formats that allow specification of sparse graphical models in addition to the conventional UAI format: (1) Sparse UAI format (see http://www.hlt.utdallas.edu/~vgogate/uai16-evaluation/sparseformat.html) (2) Binary Clausal format (see http://www.hlt.utdallas.edu/~vgogate/uai16-evaluation/binaryformat.html) Thus, we will have 12 evaluation categories (4 tasks x 3 formats). Notable features of the evaluation: * You have the option of keeping your solver name(s) anonymous. Since this is an evaluation and not a competition, there will be no winners and/or losers. However, if your solver/software is a top performer on a number of benchmark categories, we will contact you and disclose your identity if you give consent. * We strongly encourage submission of solvers having strong theoretical guarantees (e.g., relative-error guarantee, lower bound guarantee, epsilon-delta relative error guarantee, etc.). We will categorize such solvers appropriately. * We have divided the benchmark graphical models into two sets: training/tuning instances and test instances. The setup is such that you will be able to see the results of your solver on the training/tuning instances within 24-72 hours. Results on the test instances will be made public only after the submission deadline (October 31). Important dates/deadlines: Solver submission deadline *NEW*: OCTOBER 31, 2016 For more information and questions, please contact me, Vibhav Gogate ([email protected]<mailto:[email protected]>). Cheers, Vibhav Gogate Assistant Professor The University of Texas at Dallas http://www.hlt.utdallas.edu/~vgogate/index.html
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