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Fast Learning Requires Good Memory: A Time-Space Lower Bound for Parity Learning
Parity Learning bounded storage model
2016/2/22
We prove that any algorithm for learning parities requires either a memory of
quadratic size or an exponential number of samples. This proves a recent conjecture
of Steinhardt, Valiant and Wager [SV...
On Agnostic Boosting and Parity Learning
agnostic learning, agnostic boosting learning parity withm noise sub-exponential algorithms
2012/11/30
The motivating problem is agnostically learning parity functions, i.e., parity with arbitrary or adversarial noise. Specifically, given random labeled examples from an arbitrary distribution, we would...