Welcome! I'm currently a PhD student at the Computer Science department of University of Toronto. My advisor is Gennady Pekhimenko . My research is motivated by developing ML tools and frameworks to benefit various end users, current including but not limited to the fields of neural architecture search and federated learning. I finished my Master of Science in Machine Learning at CMU, and I earned my Bachelor of Arts degree in Computer Science and History from Columbia University.


Select Publications


NAS-Bench-360: Benchmarking Diverse Tasks for Neural Architecture Search
Renbo Tu*, Nicholas Roberts, Mikhail Khodak, Junhong Shen, Frederic Sala, Ameet Talwalkar.
Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2022
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NAS-Bench-Suite-Zero: Accelerating Research on Zero Cost Proxies
Arjun Krishnakumar, Colin White, Arber Zela*, Renbo Tu*, Mahmoud Safari, Frank Hutter.
Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2022
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Federated Hyperparameter Tuning: Challenges, Baselines, and Connections to Weight-Sharing
Mikhail Khodak, Renbo Tu, Tian Li, Liam Li, Maria-Florina Balcan, Virginia Smith, Ameet Talwalkar.
Neural Information Processing Systems (NeurIPS), 2021
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Towards Deeper Generative Architectures for GANs using Dense connections
Samarth Tripathi, Renbo Tu.
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