Efficiently learning structured distributions from untrusted batches
© 2020 ACM. We study the problem, introduced by Qiao and Valiant, of learning from untrusted batches. Here, we assume m users, all of whom have samples from some underlying distribution over 1, ..., n. Each user sends a batch of k i.i.d. samples from this distribution; however an "-fraction of...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
ACM
2021
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| Online Access: | https://hdl.handle.net/1721.1/137507 |