Automatic Feature Extraction, Categorization and Detection of Malicious Code in Android Applications von Qadir, Muhammad Zuhair, Jilani, Atif Nisar, Sheikh, Hassam Ullah

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DNS: Determinantal Point Process Based Neural Network Sampler for Ensemble Reinforcement Learning von Sheikh, Hassam, Frisbee, Kizza, Phielipp, Mariano

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Preventing Value Function Collapse in Ensemble {Q}-Learning by Maximizing Representation Diversity von Sheikh, Hassam Ullah, Bölöni, Ladislau

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Multi-Agent Reinforcement Learning for Problems with Combined Individual and Team Reward von Sheikh, Hassam Ullah, Bölöni, Ladislau

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Universal Policies to Learn Them All von Sheikh, Hassam Ullah, Bölöni, Ladislau

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The Emergence of Complex Bodyguard Behavior Through Multi-Agent Reinforcement Learning von Sheikh, Hassam Ullah, Bölöni, Ladislau

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Designing a Multi-Objective Reward Function for Creating Teams of Robotic Bodyguards Using Deep Reinforcement Learning von Sheikh, Hassam Ullah, Bölöni, Ladislau

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Emergence of Scenario-Appropriate Collaborative Behaviors for Teams of Robotic Bodyguards von Sheikh, Hassam Ullah, Boloni, Ladislau

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Minimizing Communication while Maximizing Performance in Multi-Agent Reinforcement Learning von Vijay, Varun Kumar, Sheikh, Hassam, Majumdar, Somdeb, Phielipp, Mariano

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Preventing Value Function Collapse in Ensemble {Q}-Learning by Maximizing Representation Diversity von Sheikh, Hassam Ullah, Bölöni, Ladislau

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Learning Intrinsic Symbolic Rewards in Reinforcement Learning von Sheikh, Hassam, Khadka, Shauharda, Miret, Santiago, Majumdar, Somdeb

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Automatic Feature Extraction, Categorization and Detection of Malicious Code in Android Applications von Qadir, Muhammad Zuhair, Jilani, Atif Nisar, Sheikh, Hassam Ullah

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DNS: Determinantal Point Process Based Neural Network Sampler for Ensemble Reinforcement Learning von Hassam Sheikh, Kizza Frisbee, Phielipp, Mariano

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Emergence of Scenario-Appropriate Collaborative Behaviors for Teams of Robotic Bodyguards von Sheikh, Hassam Ullah, Boloni, Ladislau

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Multi-Agent Reinforcement Learning for Problems with Combined Individual and Team Reward von Sheikh, Hassam Ullah, Bölöni, Ladislau

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Direct Telephonic Communication in a Heart Failure Transitional Care Program: An observational study von Ota, Ken S, Beutler, David S, Sheikh, Hassam, Weiss, Jessica L, Parkinson, Dallin, Nguyen, Peter, Gerkin, Richard D, Loli, Akil I

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Universal Policies to Learn Them All von Sheikh, Hassam Ullah, Bölöni, Ladislau

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Designing a Multi-Objective Reward Function for Creating Teams of Robotic Bodyguards Using Deep Reinforcement Learning von Sheikh, Hassam Ullah, Bölöni, Ladislau

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The Emergence of Complex Bodyguard Behavior Through Multi-Agent Reinforcement Learning von Sheikh, Hassam Ullah, Bölöni, Ladislau

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Minimizing Communication while Maximizing Performance in Multi-Agent Reinforcement Learning von Vijay, Varun Kumar, Hassam Sheikh, Majumdar, Somdeb, Phielipp, Mariano

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