Search Results - "Kopparapu, Kavya"

Deep Learning–Enabled Assessment of Left Heart Structure and Function Predicts Cardiovascular Outcomes by Lau, Emily S., Di Achille, Paolo, Kopparapu, Kavya, Andrews, Carl T., Singh, Pulkit, Reeder, Christopher, Al-Alusi, Mostafa, Khurshid, Shaan, Haimovich, Julian S., Ellinor, Patrick T., Picard, Michael H., Batra, Puneet, Lubitz, Steven A., Ho, Jennifer E.

“…Deep learning interpretation of echocardiographic images may facilitate automated assessment of cardiac structure and function. We developed a deep learning…”
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RV SIZE MEASURED BY DEEP LEARNING PREDICTS ATRIAL FIBRILLATION, HEART FAILURE AND MORTALITY by Al-Alusi, Mostafa, Kopparapu, Kavya, Singh, Pulkit, Achille, Paolo Di, Lau, Emily Shou Wai, Reeder, Christopher, Khurshid, Shaan, Ellinor, Patrick, Ho, Jennifer, Picard, Michael H., Batra, Puneet, Lubitz, Steven

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TinyFedTL: Federated Transfer Learning on Tiny Devices by Kopparapu, Kavya, Lin, Eric

“…TinyML has rose to popularity in an era where data is everywhere. However, the data that is in most demand is subject to strict privacy and security…”
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FedFMC: Sequential Efficient Federated Learning on Non-iid Data by Kopparapu, Kavya, Lin, Eric

“…As a mechanism for devices to update a global model without sharing data, federated learning bridges the tension between the need for data and respect for…”
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TinyFedTL: Federated Transfer Learning on Ubiquitous Tiny IoT Devices by Kopparapu, Kavya, Lin, Eric, Breslin, John G., Sudharsan, Bharath

“…TinyML refers to the intersection of machine learning (ML), mathematical optimization, and tiny IoT embedded systems. In the current era of ubiquitous…”
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Hierarchical reinforcement learning with natural language subgoals by Ahuja, Arun, Kopparapu, Kavya, Fergus, Rob, Dasgupta, Ishita

“…Hierarchical reinforcement learning has been a compelling approach for achieving goal directed behavior over long sequences of actions. However, it has been…”
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FedCD: Improving Performance in non-IID Federated Learning by Kopparapu, Kavya, Lin, Eric, Zhao, Jessica

“…Federated learning has been widely applied to enable decentralized devices, which each have their own local data, to learn a shared model. However, learning…”
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ReST meets ReAct: Self-Improvement for Multi-Step Reasoning LLM Agent by Aksitov, Renat, Miryoosefi, Sobhan, Li, Zonglin, Li, Daliang, Babayan, Sheila, Kopparapu, Kavya, Fisher, Zachary, Guo, Ruiqi, Prakash, Sushant, Srinivasan, Pranesh, Zaheer, Manzil, Yu, Felix, Kumar, Sanjiv

“…Answering complex natural language questions often necessitates multi-step reasoning and integrating external information. Several systems have combined…”
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Hidden Agenda: a Social Deduction Game with Diverse Learned Equilibria by Kopparapu, Kavya, Duéñez-Guzmán, Edgar A, Matyas, Jayd, Vezhnevets, Alexander Sasha, Agapiou, John P, McKee, Kevin R, Everett, Richard, Marecki, Janusz, Leibo, Joel Z, Graepel, Thore

“…A key challenge in the study of multiagent cooperation is the need for individual agents not only to cooperate effectively, but to decide with whom to…”
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Melting Pot 2.0 by Agapiou, John P, Vezhnevets, Alexander Sasha, Duéñez-Guzmán, Edgar A, Matyas, Jayd, Mao, Yiran, Sunehag, Peter, Köster, Raphael, Madhushani, Udari, Kopparapu, Kavya, Comanescu, Ramona, Strouse, DJ, Johanson, Michael B, Singh, Sukhdeep, Haas, Julia, Mordatch, Igor, Mobbs, Dean, Leibo, Joel Z

“…Multi-agent artificial intelligence research promises a path to develop intelligent technologies that are more human-like and more human-compatible than those…”
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