TY - JOUR
T1 - Learning with queries corrupted by classification noise
AU - Jackson, Jeffrey
AU - Shamir, Eli
AU - Shwartzman, Clara
PY - 1999/6
Y1 - 1999/6
N2 - Kearns introduced the "statistical query" (SQ) model as a general method for producing learning algorithms which are robust against classification noise. We extend this approach in several ways in order to tackle algorithms that use "membership queries", focusing on the more stringent model of "persistent noise". The main ingredients in the general analysis are: 1. Smallness of dimension of the classes of both the target and the queries. 2. Independence of the noise variables. Persistence restricts independence, forcing repeated invocation of the same point x to give the same label. We apply the general analysis to get a noise-robust version of Jackson's Harmonic Sieve, which learns DNF under the uniform distribution. This corrects an error in his earlier analysis of noise tolerant DNF learning.
AB - Kearns introduced the "statistical query" (SQ) model as a general method for producing learning algorithms which are robust against classification noise. We extend this approach in several ways in order to tackle algorithms that use "membership queries", focusing on the more stringent model of "persistent noise". The main ingredients in the general analysis are: 1. Smallness of dimension of the classes of both the target and the queries. 2. Independence of the noise variables. Persistence restricts independence, forcing repeated invocation of the same point x to give the same label. We apply the general analysis to get a noise-robust version of Jackson's Harmonic Sieve, which learns DNF under the uniform distribution. This corrects an error in his earlier analysis of noise tolerant DNF learning.
UR - http://www.scopus.com/inward/record.url?scp=0042097798&partnerID=8YFLogxK
U2 - 10.1016/S0166-218X(99)00045-1
DO - 10.1016/S0166-218X(99)00045-1
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AN - SCOPUS:0042097798
SN - 0166-218X
VL - 92
SP - 157
EP - 175
JO - Discrete Applied Mathematics
JF - Discrete Applied Mathematics
IS - 2-3
ER -