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Start Date |
End Date |
Papers Due |
Notification Date |
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| ICANN 2008 |
2008-09-03 |
2008-09-06 |
2008-03-03 |
2008-05-12 |
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Prague, Czech Republic
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International Conference on Artificial Neural Networks is an annual conference organized since 1998 by the ENNS - European Neural Network Society in co-operation with the International Neural Network Society and the Japanese Neural Network Society, and is a premier event in all topics related to neural networks. |
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| ALT 2008 |
2008-10-13 |
2008-10-16 |
2008-05-18 |
2008-06-22 |
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Budapest, Hungary
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The 19th International Conference on Algorithmic Learning Theory focuses on the theoretical foundations of machine learning. Topics of interest include the comparison, design, and evaluation of learning models, the analysis of the theoretical properties of existing algorithms, and the definition and analysis of new learning models. |
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| The 10th Pacific Rim International Conference on Artificial Intelligence (PRICAI-08) |
2008-12-15 |
2008-12-19 |
2008-05-26 |
2008-07-25 |
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Hanoi, Vietnam
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The 10th Pacific Rim International Conference on Artificial Intelligence (PRICAI-08) will provide an international forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences which concentrate on AI technologies and their applications in areas of social and economic importance for countries in the Pacific Rim. |
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| NIPS 2008 |
2008-12-08 |
2008-12-11 |
2008-06-06 |
2008-12-08 |
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Vancouver, Canada
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The Neural Information Processing Systems Conference features a single track program, with contributions from a large number of intellectual communities. Presentation topics include: Algorithms and Architectures; Applications; Brain Imaging; Cognitive Science and Artificial Intelligence; Control and Reinforcement Learning; Emerging Technologies; Learning Theory; Neuroscience; Speech and Signal Processing; and Visual Processing. All papers are rigorously reviewed. |
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| ICMLA 2008 |
2008-12-11 |
2008-12-13 |
2008-06-15 |
2008-09-01 |
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San Diego, United States
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The 7th International Conference on Machine Learning and Applications aims to bring together researchers and practitioners to present the latest achievements and innovations in the area of machine learning (ML). The conference provides a leading international forum for the dissemination of original research in ML, with emphasis on applications, novel algorithms, software and systems. Following the success of previous ICMLA conferences, it attracts researchers and application developers from a wide range of ML related areas such as statistical, probabilistic, fuzzy, evolutionary, inductive, and other kinds of learning, data mining, knowledge discovery, pattern recognition, knowledge acquisition and retrieval, databases, data warehousing and visualization, knowledge-based systems and high performance computing. The main goal of the conference is to advance the state-of-the-art in ML via promotion of high quality and novel research. |
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Start Date |
End Date |
Papers Due |
Notification Date |
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| SEAL'08 |
2008-12-07 |
2008-12-10 |
2008-06-30 |
2008-08-18 |
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Melbourne, Australia
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Evolution and learning are two fundamental forms of adaptation. SEAL'08 is the seventh biennial conference in the highly successful series that aims at exploring these two forms of adaptation and their roles and interactions in adaptive systems. Cross-fertilisation between evolutionary learning and other machine learning approaches, such as neural network learning, reinforcement learning, decision tree learning, fuzzy system learning, etc., will be strongly encouraged by the conference. |
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| IROS2008 |
2008-09-22 |
2008-09-22 |
2008-07-21 |
2008-07-28 |
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Nice, France
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IEEE RAS Workshop on Robot Learning: There is an increasing interest in machine learning and statistics within the robotics community. At the same time, there has been a growth in the learning community in using robots as motivating applications for new algorithms and formalisms. Rapid progress requires researchers from both disciplines to come together and agree on the challenges, problem formulations, and solution techniques. Contributions are sought in the following areas: learning models of robots, tasks or environments, learning plans and control policies by imitation and reinforcement learning, representations which facilitate learning, such as low-dimensional embeddings of movements, learning representations and task abstractions by unsupervised learning, probabilistic inference of task parameters from multi-modal sensory information, and integration of learning into control architectures. |
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| ICIS 2008 |
2008-12-24 |
2008-12-26 |
2008-08-31 |
2008-09-10 |
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Bangkok, Thailand
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The International Conference on Intelligent Systems is the premier forum for the presentation of technological advances and research results in the fields of theoretical, experimental, and applied Intelligent Systems. |
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| LION 3 |
2009-01-14 |
2009-01-18 |
2008-10-15 |
2008-11-22 |
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Trento, Italy
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The Learning and Intelligent OptimizatioN conference is aimed at exploring the boundaries and uncharted territories between machine learning, artificial intelligence, mathematical programming and algorithms for hard optimization problems. The main purpose of the event is to bring together experts from these areas to discuss new ideas and methods, challenges and opportunities in various application areas, general trends and specific developments. |
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| ADPRL 09 |
2009-03-30 |
2009-04-02 |
2008-10-31 |
2008-11-30 |
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Nashville, United States
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The IEEE International Symposium on Adaptive Dynamic Programming and Reinforcement Learning is part of IEEE SSCI 2009 and includes topics such as convergence and performance bounds of ADP, complexity issues in RL and ADP, statistical learning and RL, PAC bounds for RL, direct policy search, actor-critic methods, adaptive feature search, POMDPs, distributed intelligent systems, multi-agent RL systems, applications of ADP and RL, and more! |
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Start Date |
End Date |
Papers Due |
Notification Date |
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| Autonomous Robots |
2009-10-01 |
2009-10-01 |
2008-11-08 |
2009-03-01 |
|
Journal,
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In this Autonomous Robots Special Issue on Robot Learning, we intend to outline recent successes in the application of domain-driven
machine learning methods to robotics. Examples of topics of interest include, but are not limited to: learning models of robots, task or environments, learning deep hierarchies or levels of representations from sensor
& motor representations to task abstractions, learning plans and control policies by imitation, apprenticeship and reinforcement learning, finding low-dimensional embeddings of movement as implicit generative models, integrating learning with control architectures, methods for probabilistic inference from multi-modal sensory information (e.g., proprioceptive, tactile, vision), structured spatio-temporal representations designed for robot
learning, probabilistic inference in non-linear, non-Gaussian stochastic systems (e.g., for planning as well as for optimal or adaptive
control). |
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the university of tennessee
