Search Results - Mladenov, Martin

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  1. 1
    Relational linear programming

    Relational linear programming by Kersting, Kristian, Mladenov, Martin, Tokmakov, Pavel

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  2. 2
    Exploiting symmetries for scaling loopy belief propagation and relational training

    Exploiting symmetries for scaling loopy belief propagation and relational training by Ahmadi, Babak, Kersting, Kristian, Mladenov, Martin, Natarajan, Sriraam

    Published in Machine learning
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  3. 3
    Exploiting symmetries for scaling loopy belief propagation and relational training: Special Issue of Selected Papers from ECML-PKDD 2012

    Exploiting symmetries for scaling loopy belief propagation and relational training: Special Issue of Selected Papers from ECML-PKDD 2012 by AHMADI, Babak, KERSTING, Kristian, MLADENOV, Martin, NATARAJAN, Sriraam

    Published in Machine learning
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  4. 4
    Identifying Place Histories from Activity Traces with an Eye to Parameter Impact

    Identifying Place Histories from Activity Traces with an Eye to Parameter Impact by Andrienko, Gennady, Andrienko, Natalia, Mladenov, Martin, Mock, Michael, Politz, Christian

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  5. 5
    Recommender Ecosystems: A Mechanism Design Perspective on Holistic Modeling and Optimization

    Recommender Ecosystems: A Mechanism Design Perspective on Holistic Modeling and Optimization by Boutilier, Craig, Mladenov, Martin, Tennenholtz, Guy

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  6. 6
    Extracting Events from Spatial Time Series

    Extracting Events from Spatial Time Series by Andrienko, Gennady, Andrienko, Natalia, Mladenov, Martin, Mock, Michael, Poelitz, Christian

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  7. 7
    Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models

    Modeling Recommender Ecosystems: Research Challenges at the Intersection of Mechanism Design, Reinforcement Learning and Generative Models by Boutilier, Craig, Mladenov, Martin, Tennenholtz, Guy

    Published in arXiv.org
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  8. 8
    Content Prompting: Modeling Content Provider Dynamics to Improve User Welfare in Recommender Ecosystems

    Content Prompting: Modeling Content Provider Dynamics to Improve User Welfare in Recommender Ecosystems by Prasad, Siddharth, Mladenov, Martin, Boutilier, Craig

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  9. 9
    Minimizing Live Experiments in Recommender Systems: User Simulation to Evaluate Preference Elicitation Policies

    Minimizing Live Experiments in Recommender Systems: User Simulation to Evaluate Preference Elicitation Policies by Hsu, Chih-Wei, Mladenov, Martin, Meshi, Ofer, Pine, James, Pham, Hubert, Li, Shane, Liang, Xujian, Polishko, Anton, Yang, Li, Scheetz, Ben, Boutilier, Craig

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  10. 10
    Lifted Inference for Convex Quadratic Programs

    Lifted Inference for Convex Quadratic Programs by Mladenov, Martin, Kleinhans, Leonard, Kersting, Kristian

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  11. 11
    Reinforcement Learning with History-Dependent Dynamic Contexts

    Reinforcement Learning with History-Dependent Dynamic Contexts by Tennenholtz, Guy, Merlis, Nadav, Shani, Lior, Mladenov, Martin, Boutilier, Craig

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  12. 12
    The Symbolic Interior Point Method

    The Symbolic Interior Point Method by Mladenov, Martin, Belle, Vaishak, Kersting, Kristian

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  13. 13
    pyRDDLGym: From RDDL to Gym Environments

    pyRDDLGym: From RDDL to Gym Environments by Taitler, Ayal, Gimelfarb, Michael, Jeong, Jihwan, Gopalakrishnan, Sriram, Mladenov, Martin, Liu, Xiaotian, Sanner, Scott

    Published in arXiv.org
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  14. 14
    Ranking with Popularity Bias: User Welfare under Self-Amplification Dynamics

    Ranking with Popularity Bias: User Welfare under Self-Amplification Dynamics by Tennenholtz, Guy, Mladenov, Martin, Merlis, Nadav, Axtell, Robert L, Boutilier, Craig

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  15. 15
    Lifting Relational MAP-LPs Using Cluster Signatures

    Lifting Relational MAP-LPs Using Cluster Signatures by Apsel, Udi, Kersting, Kristian, Mladenov, Martin

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  16. 16
    Power Iterated Color Refinement

    Power Iterated Color Refinement by Kersting, Kristian, Mladenov, Martin, Garnett, Roman, Grohe, Martin

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  17. 17
    Demystifying Embedding Spaces using Large Language Models

    Demystifying Embedding Spaces using Large Language Models by Tennenholtz, Guy, Chow, Yinlam, Hsu, Chih-Wei, Jeong, Jihwan, Shani, Lior, Tulepbergenov, Azamat, Ramachandran, Deepak, Mladenov, Martin, Boutilier, Craig

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  18. 18
    Meta-Thompson Sampling

    Meta-Thompson Sampling by Kveton, Branislav, Konobeev, Mikhail, Manzil Zaheer, Hsu, Chih-wei, Mladenov, Martin, Boutilier, Craig, Szepesvari, Csaba

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  19. 19
    Advantage Amplification in Slowly Evolving Latent-State Environments

    Advantage Amplification in Slowly Evolving Latent-State Environments by Mladenov, Martin, Meshi, Ofer, Ooi, Jayden, Schuurmans, Dale, Boutilier, Craig

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  20. 20
    Planning and Learning with Stochastic Action Sets

    Planning and Learning with Stochastic Action Sets by Boutilier, Craig, Cohen, Alon, Daniely, Amit, Hassidim, Avinatan, Mansour, Yishay, Meshi, Ofer, Mladenov, Martin, Schuurmans, Dale

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