Vitaly Feldman, Age 46Mountain View, CA
Vitaly Feldman Phones & Addresses
Mountain View, CA
Palo Alto, CA
San Francisco, CA
San Jose, CA
24 Magnolia Ave, Cambridge, MA 02138
Mentions for Vitaly Feldman
Publications & IP owners
Us Patents
Critical Area Preprocessing Of Numeric Control Data For Cutting Sheet Material
US Patent:
2002009, Jul 18, 2002
Filed:
Mar 16, 2001
Appl. No.:
09/727942
Inventors:
Vitaly Feldman - Newton MA, US
Sergio Manevich - Winchester MA, US
Sergio Manevich - Winchester MA, US
International Classification:
B26D003/00
B26D005/00
B26D005/00
US Classification:
083/049000, 083/056000, 083/076900, 083/075500
Abstract:
A method and system of cutting parts from sheet material comprising a numerically-controlled cutting system having a cutting tool for cutting along a path, the method comprising the steps of: (a) placing a plurality of templates which define the shapes and sizes of the parts to be cut upon the sheet material while minimizing the spaces between the templates to form a closely-packed marker; (b) entering the marker into a pre-processor; (c) detecting common lines and tangencies between templates in the marker; (d) determining a path and speed for said cutting tool; and (e) directing the cutting tool in accordance with the path and speed such that the parts are cut from the sheet material. The pre-processor identifies critical segments of the cutting path where cutting difficulties may arise and modifies the data that guide the cutting tool for more accurate cutting through the critical segments. In particular, the pre-processor identifies segments of the cutting path proximately close to one another called “common line segments” and generates a modified cutting path using a single pass to cut common line segments. The method and system of the present invention provide an optimal cutting path and control of a cutting tool resulting in higher quality cut pieces and the highest possible throughput. Therefore, the method disclosed allows for and makes desirable the close nesting of templates without buffers.
Dictionary Refinement For Information Extraction
US Patent:
2013031, Nov 28, 2013
Filed:
May 25, 2012
Appl. No.:
13/480974
Inventors:
Laura Chiticariu - San Jose CA, US
Vitaly Feldman - Palo Alto CA, US
Frederick R. Reiss - Sunnyvale CA, US
Sudeepa Roy - , US
Huaiyu Zhu - Union City CA, US
Vitaly Feldman - Palo Alto CA, US
Frederick R. Reiss - Sunnyvale CA, US
Sudeepa Roy - , US
Huaiyu Zhu - Union City CA, US
Assignee:
INTERNATIONAL BUSINESS MACHINES CORPORATION - Armonk NY
International Classification:
G06F 17/30
US Classification:
707723, 707E17014
Abstract:
A method for refining a dictionary for information extraction, the operations including: inputting a set of extracted results from execution of an extractor comprising the dictionary on a collection of text, wherein the extracted results are labeled as correct results or incorrect results; processing the extracted results using an algorithm configured to set a score of the extractor above a score threshold, wherein the score threshold balances a precision and a recall of the extractor; and outputting a set of candidate dictionary entries corresponding to a full set of dictionary entries, wherein the candidate dictionary entries are candidates to be removed from the dictionary based on the extracted results.
Refining A Dictionary For Information Extraction
US Patent:
2013031, Nov 28, 2013
Filed:
Aug 30, 2012
Appl. No.:
13/598946
Inventors:
Laura Chiticariu - San Jose CA, US
Vitaly Feldman - Palo Alto CA, US
Frederick R. Reiss - Sunnyvale CA, US
Sudeepa Roy - , US
Huaiyu Zhu - Union City CA, US
Vitaly Feldman - Palo Alto CA, US
Frederick R. Reiss - Sunnyvale CA, US
Sudeepa Roy - , US
Huaiyu Zhu - Union City CA, US
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
G06F 17/30
US Classification:
707723, 707E17014
Abstract:
A method for refining a dictionary for information extraction, the operations including: inputting a set of extracted results from execution of an extractor comprising the dictionary on a collection of text, wherein the extracted results are labeled as correct results or incorrect results; processing the extracted results using an algorithm configured to set a score of the extractor above a score threshold, wherein the score threshold balances a precision and a recall of the extractor; and outputting a set of candidate dictionary entries corresponding to a full set of dictionary entries, wherein the candidate dictionary entries are candidates to be removed from the dictionary based on the extracted results.
Linear Time Algorithms For Privacy Preserving Convex Optimization
US Patent:
2021015, May 27, 2021
Filed:
Nov 20, 2020
Appl. No.:
16/953977
Inventors:
- Mountain View CA, US
Vitaly Feldman - Mountain View CA, US
Tomer Koren - Herzliya, IL
Vitaly Feldman - Mountain View CA, US
Tomer Koren - Herzliya, IL
International Classification:
G06N 20/00
G06F 17/18
G06F 21/60
G06F 17/18
G06F 21/60
Abstract:
Methods, systems, and apparatus, including computer programs encoded on computer storage media for training a machine learning model. The method includes obtaining a training data set comprising a plurality of training examples; determining i) a stochastic gradient descent step size schedule, ii) a stochastic gradient descent noise schedule, and iii) a stochastic gradient descent batch size schedule, wherein the stochastic gradient descent batch size schedule comprises a sequence of varying batch sizes; and training a machine learning model on the training data set, comprising performing stochastic gradient descent according to the i) stochastic gradient descent step size schedule, ii) stochastic gradient descent noise schedule, and iii) stochastic gradient descent batch size schedule to adjust a machine learning model loss function.
NOTICE: You may not use PeopleBackgroundCheck or the information it provides to make decisions about employment, credit, housing or any other purpose that would require Fair Credit Reporting Act (FCRA) compliance. PeopleBackgroundCheck is not a Consumer Reporting Agency (CRA) as defined by the FCRA and does not provide consumer reports.