Previous Rising Stars in Machine Learning
2022 Rising Stars
2021 Rising Stars
Tian Li
Doctoral Student at Carnegie Mellon University
"On Heterogeneity in Federated Settings"
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Xinyun Chen
Doctoral Student at the University of California, Berkeley
“Deep Learning for Program Synthesis: Towards Human-like Reasoning”
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Qi Lei
Associate Research Scholar at Princeton University
“Provable Representation Learning: The Importance of Task Diversity and Pretext Tasks"
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Diana Cai
Doctoral Student at Princeton University
“Probabilistic Inference Under Model Misspecification”
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Irene Chen
Doctoral Student at Massachusetts Insititute of Technology
“Machine Learning for Equitable Healthcare”
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Mahsa Ghasemi
Doctoral Student at The University of Texas at Austin
“Efficient Data Processing and Trustworthy Decision Making through Structured Task Representation”
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Nan Rosemary Ke
Doctoral Student at University of Montreal
"From 'What' to 'Why': Towards Causal Deep Networks”
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Surbhi Goel
Doctoral Student at The University of Texas at Austin
“Provably Efficient Algorithms for Learning Neural Networks”
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Adji Bousso Dieng
Doctoral Student at Columbia University
“Learning with Deep Probabilistic Generative Models”
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Karolina Gintare Dziugaite
Fundamental Research Scientist at Element AI
“PAC-Bayesian Approaches to Understanding Generalization in Deep Learning”
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