Abstract: The decentralized stochastic gradient method emerges as a promising solution for solving large-scale machine learning problems. This paper studies the decentralized Markov chain gradient ...
Researchers from the Max Planck Institute for Intelligent Systems (MPI-IS), the Tübingen AI Center and Ellis Institute ...
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Stable-GFlowNet uncovers more hidden weaknesses in generative AI models
KAIST researchers have developed a safety verification technology that uncovers roughly seven times more hidden ...
In this useful Tools & Resources article, the authors describe a new cryogenic light microscopy design and characterize its temperature and spatial stability. This compelling system avoids the ...
Cryptographic code sits at the foundation of modern computing. It protects operating systems, cloud services, firmware, messaging systems, and the protocols that connect them. Small mistakes can have ...
This is a collection of Multi-Agent Reinforcement Learning (MARL) papers. Each category is a potential start point for you to start your research. Some papers are listed more than once because they ...
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I am a research scientist at Google Brain. I graduated from SCS of CMU, with a PhD in Machine Learning and an MSc in Lanugage Technologies, advised by Jaime Carbonell and Alex Smola.
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