Search Results - "Rieger, Phillip"

The influence of turbidity on larval walleye, Stizostedion vitreum, behavior and development in tank culture by Rieger, Phillip W., Summerfelt, Robert C.

“…The behavior and development of larval walleye, Stizostedion vitreum, cultured in clear and turbid water in laboratory aquaria are compared from hatch to 17…”
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BayBFed: Bayesian Backdoor Defense for Federated Learning by Kumari, Kavita, Rieger, Phillip, Fereidooni, Hossein, Jadliwala, Murtuza, Sadeghi, Ahmad-Reza

“…Federated learning (FL) is an emerging technology that allows participants to jointly train a machine learning model without sharing their private data with…”
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SAFELearn: Secure Aggregation for private FEderated Learning by Fereidooni, Hossein, Marchal, Samuel, Miettinen, Markus, Mirhoseini, Azalia, Mollering, Helen, Nguyen, Thien Duc, Rieger, Phillip, Sadeghi, Ahmad-Reza, Schneider, Thomas, Yalame, Hossein, Zeitouni, Shaza

“…Federated learning (FL) is an emerging distributed machine learning paradigm which addresses critical data privacy issues in machine learning by enabling…”
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Phantom: Untargeted Poisoning Attacks on Semi-Supervised Learning (Full Version) by Knauer, Jonathan, Rieger, Phillip, Fereidooni, Hossein, Sadeghi, Ahmad-Reza

“…Deep Neural Networks (DNNs) can handle increasingly complex tasks, albeit they require rapidly expanding training datasets. Collecting data from platforms with…”
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FLEDGE: Ledger-based Federated Learning Resilient to Inference and Backdoor Attacks by Castillo, Jorge, Rieger, Phillip, Fereidooni, Hossein, Chen, Qian, Sadeghi, Ahmad

“…Federated learning (FL) is a distributed learning process that uses a trusted aggregation server to allow multiple parties (or clients) to collaboratively…”
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Structural consequences of electron-transfer reactions. 25. Electron-transfer-induced isomerizations of cobalt-, nickel-, and palladium-cyclooctatetraene complexes: the role played by the ligand vs. metal composition of the redox orbital by Geiger, William E, Rieger, Phillip H, Corbato, Carolyn, Edwin, Joseph, Fonseca, Esteban, Lane, Gregg A, Mevs, Judith M

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FreqFed: A Frequency Analysis-Based Approach for Mitigating Poisoning Attacks in Federated Learning by Fereidooni, Hossein, Pegoraro, Alessandro, Rieger, Phillip, Dmitrienko, Alexandra, Sadeghi, Ahmad-Reza

“…Federated learning (FL) is a collaborative learning paradigm allowing multiple clients to jointly train a model without sharing their training data. However,…”
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FLAIRS: FPGA-Accelerated Inference-Resistant & Secure Federated Learning by Li, Huimin, Rieger, Phillip, Zeitouni, Shaza, Picek, Stjepan, Sadeghi, Ahmad-Reza

“…Federated Learning (FL) has become very popular since it enables clients to train a joint model collaboratively without sharing their private data. However, FL…”
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FLAIRS: FPGA-Accelerated Inference-Resistant & Secure Federated Learning by Li, Huimin, Rieger, Phillip, Zeitouni, Shaza, Picek, Stjepan, Sadeghi, Ahmad-Reza

“…Federated Learning (FL) has become very popular since it enables clients to train a joint model collaboratively without sharing their private data. However, FL…”
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ARGUS: Context-Based Detection of Stealthy IoT Infiltration Attacks by Rieger, Phillip, Chilese, Marco, Mohamed, Reham, Miettinen, Markus, Fereidooni, Hossein, Sadeghi, Ahmad-Reza

“…IoT application domains, device diversity and connectivity are rapidly growing. IoT devices control various functions in smart homes and buildings, smart…”
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BayBFed: Bayesian Backdoor Defense for Federated Learning by Kumari, Kavita, Rieger, Phillip, Fereidooni, Hossein, Jadliwala, Murtuza, Sadeghi, Ahmad-Reza

“…Federated learning (FL) allows participants to jointly train a machine learning model without sharing their private data with others. However, FL is vulnerable…”
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CrowdGuard: Federated Backdoor Detection in Federated Learning by Rieger, Phillip, Krauß, Torsten, Miettinen, Markus, Dmitrienko, Alexandra, Sadeghi, Ahmad-Reza

“…Federated Learning (FL) is a promising approach enabling multiple clients to train Deep Neural Networks (DNNs) collaboratively without sharing their local…”
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AuthentiSense: A Scalable Behavioral Biometrics Authentication Scheme using Few-Shot Learning for Mobile Platforms by Fereidooni, Hossein, König, Jan, Rieger, Phillip, Chilese, Marco, Gökbakan, Bora, Finke, Moritz, Dmitrienko, Alexandra, Sadeghi, Ahmad-Reza

“…Mobile applications are widely used for online services sharing a large amount of personal data online. One-time authentication techniques such as passwords…”
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DeepSight: Mitigating Backdoor Attacks in Federated Learning Through Deep Model Inspection by Rieger, Phillip, Nguyen, Thien Duc, Miettinen, Markus, Sadeghi, Ahmad-Reza

“…Federated Learning (FL) allows multiple clients to collaboratively train a Neural Network (NN) model on their private data without revealing the data…”
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FLAME: Taming Backdoors in Federated Learning (Extended Version 1) by Nguyen, Thien Duc, Rieger, Phillip, Chen, Huili, Yalame, Hossein, Möllering, Helen, Fereidooni, Hossein, Marchal, Samuel, Miettinen, Markus, Mirhoseini, Azalia, Zeitouni, Shaza, Koushanfar, Farinaz, Sadeghi, Ahmad-Reza, Schneider, Thomas

“…Federated Learning (FL) is a collaborative machine learning approach allowing participants to jointly train a model without having to share their private,…”
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Behavior of larval walleye by Rieger, Phillip Warren

“…High resolution cinematography was used to observe larval walleye (Stizostedion vitreum) behavior in laboratory aquaria. Observations focused on gas bladder…”
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Electron-transfer-induced isomerizations of Co-, Ni-, and Pd-cyclooctatetraene complexes : the role played by the ligand vs metal composition of the redox orbital by GEIGER, W. E, RIEGER, P. H, CORBATO, C, EDWIN, J, FONSECA, E, LANE, G. A, MEVS, J. M

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