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Application
2380.2.01
US-20150012794-A1
US-20150205664-A1
US-20100023800-A1
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US-20130279232-A1
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OPT-9
FLO-2
FLO-5PROV
ONSO3175(B) - Onsemi378
ONSO3305US - Onsemi346
GTS-3DES
FLO-4
US8762658B2
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KMN-1PROV
PAT-2
PER-8 PROV
PER-9 PROV
INS-4PROV
HAR-1
CES-16
NXT-5PROV NXT-5, 6, 7, 8
IPP-0051-US14 cross roads
FLO-7PROV
IMI-5PROV
IPP-0050-US35 nextremity
VIL-12
OPT-13
TOY-1
US10998041B1
FSP1845
US6559866B2
Placeholder App
PER-10
KBR-1 1400.2.623
PER-13PROV
PAT-3
US20030023453
RMS-1DES
SMG-1DES
FLO-5
US10318495
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PER-11
US20140066758
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PER-17
JBR-1
PER-12
US11056880
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PON-1PROV, 2PROV, 3PROV
PER-33
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PER-32
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MCC-1
FLO-10
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PER-19
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TMC-PAT-1
DAR-2
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PER-16
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PER-21
BRT-PAT-1
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71212.157.USU1
FPR-PAT-1-PROV
71212.158.USP1
RMT-1
DAR-1PROV
DAR-2PROV
PON-1PROV
PON-2PROV
PON-3PROV
PER-18PROV
TMC-1PROV
TMC-2PROV
PER-13PCT
PER-13
PER-16PROV
PER-14PROV
PER-34PROV
TMC-4PROV
TMC-3
PAS-1PROV
VEH-1
PER-29DES
TEST.001
E2E-TEST.001
TEST-001
TEST-002
TEST-003
TEST-004
ZED006
FSP1011
GAV-PAT-1-PROV
Matter Number
Paragraph Number
70
Application Number
Reference Case 1
Reference Case 2
Content
In unsupervised learning, a set of data can be provided for example along with a cost function to be minimized, which can be a function of the data and the network output. The cost function can be dependent on the task and the properties of the parameters and observed variables or data. Unsupervised learning can be applied, for example, to pattern recognition, classification, and regression, general estimation problems, clustering, the estimation of statistical distributions, compression and filtering. Unsupervised learning can use one or more ANNs, expectation-maximization algorithms, data clustering, and the like. Association rule learning can use a priori algorithms, eclat algorithms, FP-growth algorithms, hierarchical clustering (e.g., single-linkage clustering and conceptual clustering), partitional clustering (e.g., K-means algorithm, fuzzy clustering), reinforcement learning (e.g., Monte Carlo method, Q-learning, temporal difference learning, and combinations thereof.
Notes
Added by DJM Jan 2024
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