Castle Avenue Team New York, NY 2123806134 (Phone)
Client type:
Home Buyers Home Sellers
Property type:
Condo/Townhome
Interests:
Weight trainingRunning - 10K and half marathon distances
Skills:
Foreign buyers Financial analysis
About:
Wei Min is a Manhattan buyer-focused condominium specialist often interviewed by the media such as The Wall Street Journal, CNN and The New York Times. In a testament to negotiation savvy, The New York Times mentioned Wei Min's deal in the cover story "Developers Cease Condo Incentives." As one of Manhattan's foreign buyer experts, Wei Min was interviewed for The Wall Street Journal's article "Foreigners Snapping Up U.S. Property." Previously, Wei Min was VP at Citigroup responsible for a $500 million portfolio and where he also received Citigroup's Chairman's Award, awarded to the top 2% of managers. Originally from Malaysia, he speaks English, Cantonese, Malaysian and Mandarin. He received an MBA from the University of Illinois at Urbana-Champaign and a BBA, Summa Cum Laude, from Marshall University. Wei Min is a Licensed Associate Real Estate Broker with Rutenberg Realty and a member of the Real Estate Board of New York. Wei Min Tan New York Licensed Associate Real Estate Broker Castle Avenue Team at Rutenberg Realty 127 E 56 St, 4th floor, New York, NY 10022 USA Email: tan@castle-avenue.com Cell: +1.212.380.6134
Medicine Doctors
Dr. Wei Y Tan, New York NY - MD (Doctor of Medicine)
Techniques that facilitate matrix factorization associated with graphics processing units are provided. In one example, a system includes a first graphics processing unit, a second graphics processing unit and a central processing unit. The first graphics processing unit processes a first data block of a data matrix associated with a matrix factorization system to generate first information for the matrix factorization system. The second graphics processing unit processes a first portion of a second data block of the data matrix separate from a second portion of the second data block to generate second information for the matrix factorization system. The central processing unit processes a machine learning model for the matrix factorization system based on at least the first information provided by the first graphics processing unit and the second information provided by the second graphics processing unit.
- Armonk NY, US Liana L. Fong - Irvington NY, US Wei Tan - Elmsford NY, US
International Classification:
G06T 1/60 G06T 1/20 G06F 17/16
Abstract:
Techniques that facilitate matrix factorization associated with graphics processing units are provided. In one example, a computer-implemented method is provided. The computer-implemented method can comprise loading, by a graphics processing unit operatively coupled to a processor, item features from a data matrix into a shared memory. The data matrix can be a matrix based on one or more user features and item features. The computer-implemented method can further comprise tiling and aggregating, by the graphics processing unit, outer products of the data matrix tiles to generate an aggregate value and approximating, by the graphics processing unit, an update to a user feature of the data matrix based on the aggregate value and the loaded item features.
- Armonk NY, US Wei Tan - Elmsford NY, US Guohui Wang - Elmsford NY, US Zhe Zhang - WHITE PLAINS NY, US
International Classification:
H04L 29/08
Abstract:
Methods, systems and computer program products for data fetching in a networked computing environment. In one embodiment, the method comprises receiving a request from an analytical node for a set of data for a defined job, and identifying in networked storage a subset of the data for the job. The subset of data is loaded to the analytical node based on the sequence in which the data are projected to be accessed in the job. In an embodiment, the request includes a specification for the job, and the specification is analyzed to identify the subset of data. In one embodiment, the subset of data is identified by identifying another job having a relationship to the defined job, and identifying the data used for that other job. In an embodiment, the networked computing environment is a cloud computing environment, and the defined job is an analytics job.
Minimizing Overhead Of Applications Deployed In Multi-Clouds
International Business Machines Corporation - Armonk NY
International Classification:
H04L 29/08 H04L 12/923 H04L 12/24 G06F 8/60
Abstract:
A computer readable storage medium and methods for distributing an application among computing nodes in a distributed processing system. A method estimates a cost of storing information pertaining to the application on different computing nodes; estimates a cost for computing resources required to execute the application on different computing nodes; estimates a cost of inter-node communication required to execute the application on different computing nodes; and selects at least one computing node to execute the application based on minimizing a total of at least one of the cost estimates.
Index Maintenance Based On A Comparison Of Rebuild Vs. Update
- Armonk NY, US Jason Crawford - Westchester NY, US Liana L. Fong - Irvington NY, US Wei Tan - Elmsford NY, US
International Classification:
G06F 16/22
Abstract:
A method, system and computer program product for index maintenance in a computer system comprising a plurality of nodes, a database, and an index to the database. In one embodiment, the method comprises, for a defined period of time, building a snapshot of selected change requests received by the nodes to change the database. After this defined period of time, a selection is made, based on specified criteria, whether to rebuild a new index to the database, or to add entries to a current index. When the selection is to rebuild a new index, the new index is rebuilt based on data in the database and in the change requests in the snapshot. When the selection is to add entries to a current index, entries are added to the current index based on data in the database and in the change requests in the snapshot.
Matrix Factorization With Two-Stage Data Block Dispatch Associated With Graphics Processing Units
Techniques that facilitate matrix factorization associated with graphics processing units are provided. In one example, a system includes a first graphics processing unit, a second graphics processing unit and a central processing unit. The first graphics processing unit processes a first data block of a data matrix associated with a matrix factorization system to generate first information for the matrix factorization system. The second graphics processing unit processes a first portion of a second data block of the data matrix separate from a second portion of the second data block to generate second information for the matrix factorization system. The central processing unit processes a machine learning model for the matrix factorization system based on at least the first information provided by the first graphics processing unit and the second information provided by the second graphics processing unit.
System, Method, And Recording Medium For Differentiated And Partial Feature Update In Alternating Least Square
An alternating least square recommendation method, system, and non-transitory computer readable medium, include partially updating a user's feature when an update ratio is less than a pre-defined threshold ratio, the pre-defined threshold ratio being configurable based on a preference of an existing sparse matrix factorization, where the pre-defined threshold ratio is pre-defined by setting the pre-defined threshold ratio to variable values according to a past acceptable update.
- Armonk NY, US Liana L. Fong - Irvington NY, US Wei Tan - Elmsford NY, US
International Classification:
G06T 1/60 G06T 1/20 G06F 17/16
Abstract:
Techniques that facilitate matrix factorization associated with graphics processing units are provided. In one example, a computer-implemented method is provided. The computer-implemented method can comprise loading, by a graphics processing unit operatively coupled to a processor, item features from a data matrix into a shared memory. The data matrix can be a matrix based on one or more user features and item features. The computer-implemented method can further comprise tiling and aggregating, by the graphics processing unit, outer products of the data matrix tiles to generate an aggregate value and approximating, by the graphics processing unit, an update to a user feature of the data matrix based on the aggregate value and the loaded item features.
Resumes
Research Staff Member At Ibm T. J. Watson Research Center
Research Staff Member at IBM, Adjunct Professor, National CIMS Engineering Research Center at Tsinghua University, Associate Editor, IEEE Transactions on Automation Science and Engineering at IEEE
Location:
Greater New York City Area
Industry:
Computer Software
Work:
IBM since Dec 2010
Research Staff Member
Tsinghua University since 2012
Adjunct Professor, National CIMS Engineering Research Center
IEEE since 2012
Associate Editor, IEEE Transactions on Automation Science and Engineering
University of Chicago 2008 - 2010
Research Professional Associate
Computation Institute, the University of Chicago and Argonne National Lab 2007 - 2008
Scientific Research Programmer
Education:
Tsinghua University 2002 - 2008
Ph.D, Computer Engineering
Tsinghua University 1998 - 2002
Bachelor, Automation
Skills:
Java Workflow Petri Nets Grid Computing Bioinformatics Programming Research Teamwork Distributed Systems SOA BPM Big Data HBase Hadoop NoSQL Business Process Design LaTeX REST Software Engineering Software Development Shell Scripting Software Design Eclipse Middleware Databases Cloud Computing Open Source Web Services Optimization Linux Scalability
Interests:
Middleware, Distributed Computing, Service Computing, IT in Bio-medicine and Health-care, Petri net
Big Data, NoSQL
Honor & Awards:
Pace Setter Award, 2010, Argonne National Laboratory
caBIG™ Teamwork Award 2008. National Cancer Institute.
IBM PhD Fellowship. IBM Corp, 2006-2007 (Only 50+ awardees globally).
Outstanding Poster Award. Biomedical Informatics Without Borders Meeting, 2008
Languages:
Chinese English
Awards:
Pacesetter Award Argonne National Laboratory Best Paper Award IEEE Intl Conf on Services Computing (SCC) caBIG™ Teamwork Award National Cancer Institute Outstanding Poster Award Biomedical Informatics Without Borders Meeting IBM PhD Fellowship IBM
Intern At Offices Of Biotechnology And Business Development At Einstein College Of Medicine
Intern at Offices of Biotechnology and Business Development at Einstein College of Medicine, Project Manager at Einstein Consulting Club
Location:
Greater New York City Area
Industry:
Biotechnology
Work:
World Financial Group (WFG) - Piscataway since Feb 2013
Part-time Associate
Albert Einstein College of Medicine - Morris Park Ave 1300 Bronx, New York, 10461 since Aug 2007
Graduate Research Scientist
Education:
Albert Einstein College of Medicine 2007 - 2013
Ph.D, Molecular Genetics
Tianjin University 2005 - 2007
M.Sc, Bio-engineering
Nankai University 2001 - 2005
B.S, Biotechnology
Skills:
Molecular Biology Molecular Cloning Molecular Genetics High Throughput Screening Cell Culture Project Management Presentations Protein Expression Protein-protein Interactions Western Blotting RT-PCR Cell Biology
Interests:
Learning new stuff/Language
Painting/Drawing/Design
Cooking/Film/Reading
Kayaking/Ski/Hiking/Rafting/Skating
Languages:
English Chinese French
Awards:
Cun Cao Fellowship Honor for Outstanding Dissertation Member of Phi Theta Kappa Honor Society
Certifications:
From Scientist to CSO: Leadership & Management Development for Careers in Business and Industry, New York Academy of Sciences AAS in Fashion Art and Design, Fashion Institution of Technology
Yulia Krashennaya, 40, of Berkeley; Allie Kurtz, 26 of Santa Barbara; Caroline Carrie McLaughlin, 35, of Oakland; Marybeth Guiney, 51, of Santa Monica; Justin Carroll Dignam, 58, of Anaheim; Daniel Garcia, 46, of Berkeley; Ted Strom, 62, of Germantown, Tenn.; and Wei Tan, 26, of Goleta, Calif.
Date: Sep 06, 2019
Category: Headlines
Source: Google
Flickr
Googleplus
Wei Tan (Rush)
Wei Tan
Education:
Hunan international economics university - Accounting system
Wei Tan
Tagline:
I am an avid google user and love food, fun,games,reading and technology. You can easily find me reading, trying out new food,studying, in tuition or hanging out. I utterly love holidays and breaks!!! :)
Norma Schroeder (1964-1968), Lindsey Brennan (2000-2002), Thomas Ley (1974-1978), Wei Tan (1995-1999), Barbara Rohde (1982-1985), Najdat Abdulla (1983-1987)