Learning under noisy supervision is governed by a feedback-truth gap | ScienceToStartup | ScienceToStartup

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References (47)

[1]

What Neural Networks Memorize and Why: Discovering the Long Tail via Influence Estimation

2020V. Feldman, Chiyuan Zhang

[2]

Learning From Noisy Labels With Deep Neural Networks: A Survey

2020Hwanjun Song, Minseok Kim et al.

[3]

Reinforcement Learning and Bayesian Inference Provide Complementary Models for the Unique Advantage of Adolescents in Stochastic Reversal

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"Develop a system for mitigating feedback-truth gaps in learning under noisy supervision, leveraging insights from neural and human studies."

Learning Theory•Score: 5•View PDF ↗

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Learning under noisy supervision is governed by a feedback-truth gap

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References (47)

Founder's Pitch

"Develop a system for mitigating feedback-truth gaps in learning under noisy supervision, leveraging insights from neural and human studies."

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Learning under noisy supervision is governed by a feedback-truth gap

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References (47)

Founder's Pitch

"Develop a system for mitigating feedback-truth gaps in learning under noisy supervision, leveraging insights from neural and human studies."

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