UAI: Uncertainty in Artificial Intelligence

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Past:   Proceedings on DBLP

Future:  Post a CFP for 2019 or later   |   Invite the Organizers Email

 
 

All CFPs on WikiCFP

Event When Where Deadline
UAI 2018 The Conference on Uncertainty in Artificial Intelligence
Aug 6, 2018 - Aug 10, 2018 Monterey, California Mar 9, 2018
UAI 2017 Uncertainty in Artificial Intelligence
Aug 11, 2017 - Aug 15, 2017 Sydney, Australia Mar 1, 2017
UAI 2016 Conference on Uncertainty in Artificial Intelligence
Jun 25, 2016 - Jun 29, 2016 New York City Mar 1, 2016
UAI 2015 31st Conference on Uncertainty in Artificial Intelligence
Jul 12, 2015 - Jul 16, 2015 Amsterdam, The Netherlands Mar 3, 2015
UAI 2014 30th Conference on Uncertainty in Artificial Intelligence
Jul 23, 2014 - Jul 27, 2014 Quebec City, Quebec, Canada Mar 19, 2014
UAI 2013 29th Conference on Uncertainty in Artificial Intelligence
Jul 12, 2013 - Jul 14, 2013 Bellevue, Washington, USA Mar 1, 2013
UAI 2012 28th Conference on Uncertainty in Artificial Intelligence
Aug 15, 2012 - Aug 17, 2012 Catalina Island, USA Mar 30, 2012
UAI 2011 27th Conference on Uncertainty in Artificial Intelligence (UAI 2011)
Jul 14, 2011 - Jul 17, 2011 Barcelona, Spain Mar 18, 2011
UAI 2010 The 26th Conference on Uncertainty in Artificial Intelligence
Jul 8, 2010 - Jul 11, 2010 Catalina Island, California Mar 12, 2010
UAI 2009 The 25th Conference on Uncertainty in Artificial Intelligence
Jun 18, 2009 - Jun 21, 2009 Montreal, Canada Mar 13, 2009
UAI 2008 Uncertainty in Artificial Intelligence
Jul 9, 2008 - Jul 12, 2008 Helsinki, Finland Feb 29, 2008 (Feb 27, 2008)
 
 

Present CFP : 2018

UAI 2018 - Call for Papers
Deadline: Friday, March 9th 2018.

The Conference on Uncertainty in Artificial Intelligence (UAI) is one of the premier international conferences on research related to knowledge representation, learning, and reasoning in the presence of uncertainty. UAI 2018 will be held in Monterey, California, on August 6-10, 2018. The main conference will take place on August 7-9, with tutorials on August 6 and workshops on August 10.

Technical Areas
UAI solicits submission of papers which describe novel theories, methodology and applications related to knowledge representation, learning, and reasoning under uncertainty. A non-exclusive list of subject areas can be found below. We welcome submissions by authors who are new to the UAI conference, or on new and emerging topics. We encourage submissions on applications, especially those that inspire new methodologies.

Important dates for authors
March 9th, 2018, 11:59 pm SST (Samoa Standard Time): Paper submission deadline.
May 24th, 2018: Author notification.
July 6th, 2018: Camera ready due.
August 6th, 2018: Conference starts.

Evaluation Criteria
Submitted papers will be reviewed based on their novelty, technical quality, potential impact and clarity of writing. For papers that rely heavily on empirical evaluations, the experimental methods and results should be clear, well executed, and repeatable. Submissions that mark "applications" as the primary subject area will be reviewed according to appropriate criteria and by reviewers with appropriate backgrounds.

UAI 2018 - Subject Areas
When an author submits a paper, they will be asked to select one primary subject area, and up to 5 secondary subject areas from the sets of terms below. The terms have been grouped to provide a somewhat systematic overview of topics relevant to the UAI conference. For example, a paper about a new approximate inference algorithm for dynamic Bayesian network with applications to a problem in biology could select the combination primary = dynamic Bayesian network, secondary = [application/biology, algorithms/approximate inference] and so on.

For reference, below is the list of subject areas that will appear to authors and reviewers in the CMT conference management system:

Algorithms:
Approximate Inference
Belief Propagation
Distributed and Parallel
Exact Inference
Graph Theory
Heuristics
MCMC methods
Optimization
Software and Tools

Application:
Biology
Databases
Decision Support
Diagnosis and Reliability
Economics
Education
General
Medicine
Planning and Control
Privacy and Security
Robotics
Sensor Data
Social Network Analysis
Speech
Sustainability and Climate
Text and Web Data
User Models
Vision

Data:
Big Data
Multivariate
Relational
Spatial
Temporal or Sequential

Learning:
Active Learning
Classification
Clustering
Deep Learning
General
Nonparametric Bayes
Online and Anytime Learning
Parameter Estimation
Probabilistic Generative Models
Ranking
Recommender Systems
Regression
Reinforcement Learning
Relational Learning
Scalability
Semi-Supervised Learning
Structure Learning
Structured Prediction
Theory
Unsupervised

Methodology:
Bayesian Methods
Calibration
Elicitation
Evaluation
Human Expertise and Judgement
Probabilistic Programming

Models:
Bayesian Networks
Directed Graphical Models
Dynamic Bayesian Networks
Markov Decision Processes
Mixed Graphical Models
Topic Models
Undirected Graphical Models

Principles:
Causality
Cognitive Models
Decision Theory
Game Theory
Information Theory
Probability Theory
Statistical Theory

Representation:
Constraints
Dempster-Shafer
Fuzzy Logic
Influence Diagrams
Non-Probabilistic Frameworks
Probabilistic
 

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