Peter M Hamilton

US Patent:

D3504824, Sep 13, 1994

Filed:

Jan 24, 1992

Appl. No.:

7/825188

Inventors:

Antonio C. Hu - Palo Alto CA
Peter W. Hamilton - Cincinnati OH
Leane K. Davis - Milford OH

Assignee:

The Procter & Gamble Company - Cincinnati OH

US Classification:

D 9448

US Patent:

50384546, Aug 13, 1991

Filed:

Mar 26, 1990

Appl. No.:

7/499240

Inventors:

Del M. Thornock - Concord CA
James R. Goldberg - Novato CA
Ronald W. Kock - Wyoming OH
Robert A. Paul - Fairfield OH
Peter W. Hamilton - Cincinnati OH
William Willhite - Cincinnati OH

Assignee:

The Procter & Gamble Company - Cincinnati OH

International Classification:

B29C 4906
B29C 4964

US Classification:

29451

Abstract:

A method for producing an integral bottle/collar combination for use in a package for storing and dispensing potentially dangerous material such as medicament tablets. The package is resistant to opening by children yet readily openable by adults. The process includes a step of injection molding a polymeric part having a finish portion, a preform portion, and a flange portion. The flange portion has at least one integrally formed socket having a resiliently deformable pushtab connected by a hinge. The preform portion of the injection molded part is blow molded into the shape of the bottle. The hingedly connected pushtab is then folded into its in-use position.

US Patent:

D3630250, Oct 10, 1995

Filed:

Oct 22, 1993

Appl. No.:

D/014497

Inventors:

Joseph F. Deflander - Wespelaar, BE
Nadi Bilani - Strombeek-Bever, BE
Johan W. Declerck - Ichtegem, BE
Antonio C. Hu - Palo Alto CA
Peter W. Hamilton - Cincinnati OH
Leane K. Davis - Milford OH

Assignee:

The Procter & Gamble Company - Cincinnati OH

US Classification:

D 9449

US Patent:

20170177996, Jun 22, 2017

Filed:

Oct 31, 2016

Appl. No.:

15/339701

Inventors:

- San Jose CA, US
Peter Hamilton - Novato CA, US
Andrew K. Story - Petaluma CA, US

International Classification:

G06N 3/08
G06F 17/11

Abstract:

As part of neural network sensitivity analyses, base outputs of hidden layer nodes of a neural network model for non-perturbed variables can be reused when perturbing the variables. Such an arrangement greatly reduces complexity of the calculations required to generate outputs of the model. Related apparatus, systems, techniques and articles are also described.

US Patent:

20150254568, Sep 10, 2015

Filed:

Mar 10, 2014

Appl. No.:

14/203195

Inventors:

- San Jose CA, US
Peter Hamilton - Novato CA, US
Andrew K. Story - Petaluma CA, US

Assignee:

FAIR ISAAC CORPORATION - San Jose CA

International Classification:

G06N 5/04
G06N 99/00

Abstract:

Data is received that include values that correspond to a plurality of variables. A score is then generated based on the received data and using a boosted ensemble of segmented scorecard models. The boosted ensemble of segmented scorecard models includes two or more segmented scorecard models. Subsequently, data including the score can be provided (e.g., displayed, transmitted, loaded, stored, etc.). Related apparatus, systems, techniques and articles are also described.

US Patent:

20150081606, Mar 19, 2015

Filed:

Sep 18, 2013

Appl. No.:

14/030834

Inventors:

- SAN JOSE CA, US
Peter Hamilton - Novato CA, US
Andrew K. Story - Petaluma CA, US

Assignee:

FAIR ISAAC CORPORATION - SAN JOSE CA

International Classification:

G06N 3/08

US Classification:

706 25

Abstract:

As part of neural network sensitivity analysis, base outputs of hidden layer nodes of a neural network model for non-perturbed variables can be reused when perturbing the variables. Such an arrangement greatly reduces complexity of the calculations required to generate outputs of the model. Related apparatus, systems, techniques and articles are also described.

US Patent:

20140180649, Jun 26, 2014

Filed:

Dec 20, 2012

Appl. No.:

13/722826

Inventors:

- Roseville MN, US
Peter Hamilton - Novato CA, US
Andrew K. Story - Petaluma CA, US
Andrew Flint - El Cerrito CA, US

Assignee:

FAIR ISAAC CORPORATION - Roseville MN

International Classification:

G06F 17/10

US Classification:

703 2

Abstract:

Data is received that characterizes a transaction and includes a plurality of values corresponding to variables. Thereafter, a score is determined for the transaction based on the received data and using a scoring model. The scoring model only uses variables pairs having a divergence residual above a pre-defined threshold. Thereafter, data is provided that characterizes the determined score. Related apparatus, systems, techniques and computer program products are also described.