The Fourteenth Annual Bayesian Modeling Applications Workshop (BMAW 2017) will be a one-day workshop held in Sydney, Australia held in conjunction with UAI 2017.
http://bmaw2017.azurewebsites.net/ ---------------------------------------------------------------- Important Dates ---------------------------------------------------------------- * Submission Deadline: June 19th, 2017 * Acceptance Notification: June 30th, 2017 * Final Paper Due: July 28th, 2017 * Workshop Day: August 15th, 2017 ---------------------------------------------------------------- Call for papers ---------------------------------------------------------------- Continuing a successful tradition as part of the UAI conference, the Fourteenth Annual Bayesian Modeling Applications Workshop (BMAW 2017) will foster discussion on the challenges of building working applications of probabilistic methods while considering stakeholders, user interaction, tools, knowledge elicitation, learning, validation, system integration, and deployment. The practicality of sharing application development experience often comes down to sharing reusable software. With models more reliant on empirical setting of hyperparameters and training schedules, reproducing the results can be impossible without access to packaged original code, and even full detailed setups including minor details of runtime environment. For example, deep learning models are often released in full containers or virtual machines. BMAW 2017 is therefore soliciting submissions describing real-world Bayesian applications, with the desire that teams will explain what tools they adopted to facilitate their work. We hope that teams will concurrently release links to the software repositories and possibly data from their applications that can be reused. Further, we are interested in presentations on best practices and tools for sharing data, code and models in easily reproducible ways. While emphasizing the software and reproducibility aspects, we encourage submissions from a broad spectrum of new and traditional application topics, with a focus on probabilistic approaches, in distinction to the discriminative machine learning and neural network methods that have gained popularity elsewhere. ---------------------------------------------------------------- Submission instructions ---------------------------------------------------------------- Please submit your paper in UAI format, not more than 8 pages long, by the submission deadline, through easychair: https://easychair.org/conferences/?conf=bmaw2017 All papers will be peer-reviewed. Author identity may be blind or open in the submitted papers. Reviewers will be anonymous. Final workshop papers will be selected with the goal of fostering discussion of critical issues within the community of practice. Final submissions of accepted papers must be accompanied by a signed copyright release form. At least one of each paper's authors must attend the workshop and present the work. --------------------------------------------------------------- Workshop Format and Organization ---------------------------------------------------------------- BMAW 2017 will be a full-day workshop, held on Aug 15th, 2017. Exact location is to be announced after registration numbers determine space allocation. All papers accepted to the BMAW will be presented during the workshop and published in the workshop proceedings. Authors of accepted technical papers will have 20 minutes to present their work. After each presentation, 5 minutes will be allocated to questions from the audience. Questions about the Workshop should be sent to bmaw2...@easychair.org. _______________________________________________ uai mailing list uai@ENGR.ORST.EDU https://secure.engr.oregonstate.edu/mailman/listinfo/uai
