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Title: Artificial Intelligence/Academic Departments - Carnegie Mellon University - Machine Learning Group Information on research, projects, and publications related to Machine Learning.
Dartmouth_College_-_AgentTCL_Group Interests in agents. Overview of research, list of people, software distribution, list of job openings, and tutorials.

Delft_University_-_Man-Machine_Interfaces_Research_Group Artificial Intelligence research with emphasis on human-computer interaction.

Free_University_of_Brussels_-_AI_Laboratory Research and publications related to artificial intelligence.

The_German_Research_Center_for_Artificial_Intelligence_GmbH Nonprofit research institute in the artificial-intelligence field. Includes information, news, and research.

Groningen_University_-_AI_Institute Information on courses and research.

Hong_Kong_Baptist_University_-_Artificial_Intelligence_Group Research on autonomous multi-agent systems and autonomy oriented computation systems.


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CMU Machine Learning Groupthe Computer Science Department

CMU CS Machine Learning Group

The Machine Learning Group is part of the Center for Automated Learning and Discovery (CALD), an interdisciplinary center that pursues research on learning, data analysis and discovery.Machine learning is concerned with design and the analysis of computer programs that improve with experience. ``Ever since computers were invented, it has been natural to wonder whether they might be made to learn. If we could understand how to program them to learn the impact would be dramatic. The practice of computer programming would be revolutionized as many tedious hand-coding tasks would be replaced by automatic learning methods. And a successful understanding of how to make computers learn would most likely yield a better understanding of human learning abilities and disabilities as well.'' (from Tom Mitchell's new book ``Machine Learning'')group pictureFacultyAvrim BlumInterested in machine learning theory, algorithm design and analysis.See his papers.Jaime CarbonellInterested in integrated intelligent systems(seamless integration of machine learning, planning, problem-solving,execution monitoring and communication), and in multi-lingual naturallanguage processing.Scott FahlmanInterested in artificial neural networks, software developmentenvironments (Gwydion/Dylan), and high-performance processing of biomedicalimages.Tom MitchellInterested in machine learning, with applications to robotics, information retrieval and database mining.John LaffertyInterested in speech and natural language processing, statistical learning algorithms, probability and information theory.Andrew W. MooreInterested in machine learning applications to robots, factoriesand other complex control systems.Reid SimmonsInterested in mobile robot planning and task-level control, probabilistic planning and reasoning intelligent agents.Katia SycaraInterested in distributed coordination of intelligent software agents, case-based reasoning and learning, and constraint-directed reasoning.Sebastian ThrunInterested in machine learning applications to robotics,learning architectures, reinforcement learning,and the integration of symbolic and neural computation.See his papers.Dave TouretzkyInterested in representation and processing of information in the brain.Raul Valdes-PerezScientific discovery and computers, e.g., interactive programs to carry out scientific reasoning at its highest levels.Practical deployment of tools as scientist's assistants.Implications for future organization of science. Manuela VelosoInterested in planning and learning, machinelearning applied to signal understanding, experience-based autonomousagents with high-level and low-level task reasoning, collaborative andadversarial planning and learning in dynamic domains.Alex WaibelInterested in speech, language, speech translation,multimodal interfaces, neural nets and machine learning.Michael WitbrockPostdocsMichael CoxInterested in case-based learning, derivational analogy, multistrategy learning, rationale capture and replay in planning, memory (especially forgetting), introspection. Jeff SchneiderGraduate StudentsDeb BakerDouglas BeefermanJim BlytheJustin BoyanAaron CourvileScott Davies Nathaniel DawFrank DellaertKan DengRujith DeSilvaRobert DriskillEugene FinkDayne FreitagMark FuhsMatthew GlickmanRich GoodwinGeoffrey GordonKaren HaighAngela KennedySven KoenigKen LangShyjan MahamudDaniel NikovskiScott ReillyHenry RowleySean SlatteryYury SmirnovPeter StoneJoseph O'SullivanEric "Astro" TellerBelinda ThomJames ThomasWilliam UtherSantosh VempalaVisitorsThorsten JoachimsStefan WaldherrOther visitors: please send me mailProjectsLearning from Text and the WebSee Text Learning Lab HomepageLearning noisy linear separatorsContact Avrim BlumAlgorithms for focusing on relevant featuresContact Avrim BlumCRAWLA computational theory of rodent navigation, including neuralrepresentations of spatial information and the learning of new environmentsby exploration. Contact Dave Touretzky or Mark FuhsXAVIER and AMELIAAutonomous mobile robots that learnThe Skinnerbots projectA theory of operant conditioning with application to trainable robots. Contact Dave Touretzky, Aaron Courvile, or Nathaniel Daw WebWatcherA tour guide for the World Wide WebPRODIGYA high-speed planning and learning architectureDetection of faces and other objects in images, using neural network-based techniquesSee the on-line demoVarious projects related to speech, language,speech translation, and multimodal interfacesAUTON Planning and Learning by Analogical/Case-Based ReasoningPlanning and Search Algorithms Minds for Robots: Agents that Plan, Execute, and LearnCollaborative and Adversarial Planning and Learning: RoboSoccer and Bolo Machine Learning for Signal Understanding Rationale Capture and Reuse in Mixed-Initiative Planning CoursesMachine LearningMachine Learning TheoryIntroduction to Artificial Neural Networks Computational Models of Neural Systems.Introduction to Artificial IntelligenceInformation TheoryOther ResourcesCenter for the Neural Basis of Cognition (a joint center with the University of Pittsburgh)The Reinforcement Learning HomepageThe Learning Lab Homepagelist of conferences related to machine learningThe Neural Information Processing Systems (NIPS) ConferenceDavid Aha's list of machine learning researchers and resourcescommentcommentmaintained by thrun@cs.cmu.edu
 

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