Karthik Gopalratnam - San Francisco CA, US Myles Sussman - San Francisco CA, US Marc Berndl - San Francisco CA, US Dan Liu - Sunnyvale CA, US Sridhar Ramaswamy - Cupertino CA, US Nicholas C. Fox - San Francisco CA, US Jonathan G. Alferness - San Francisco CA, US Adam I. Juda - New York NY, US
Assignee:
Google Inc. - Mountain View CA
International Classification:
G06Q 30/00
US Classification:
705 144
Abstract:
In general, in one aspect, a first request to provide one or more advertisements on a first web page is received, the first web page comprising one or more items of web content related to a query. A first quality score is calculated for a first advertisement included in a set of one or more candidate advertisements. The first advertisement is presented on the first web page based at least in part on the first quality score. A second request is received to provide one or more advertisements on a second web page, the second web page comprising one or more different items of web content related to the query. A second quality score for the first advertisement is calculated based at least in part on the previous presentation of the first advertisement. It is determined whether to present the first advertisement on the second web page based at least in part on the second quality score.
Melvin Yamamoto - Fremont CA, US Clifford Oostman - Quilcene WA, US John Sze - Saratoga CA, US Keith Pearson - Campbell CA, US Philip Trenholme - Santa Cruz CA, US Dan Liu - Sunnyvale CA, US Chi Yu - Saratoga CA, US
Assignee:
Affymetrix, INC. - Santa Clara CA
International Classification:
C12Q 1/68 H01L 29/15 C12M 1/34 H01L 31/0256
US Classification:
435006000, 435287200, 257076000
Abstract:
The present invention provides methods to process multiple sensors by providing a sensor plate and HT plates. In a preferred embodiment of the invention, methods for assembling microarray pegs and microarray plates are described for high throughput microarray processing.
Melvin Yamamoto - Fremont CA, US Clifford Oostman - Quilcene WA, US John Sze - Saratoga CA, US Keith Pearson - Campbell CA, US Philip Trenholme - Santa Cruz CA, US Dan Liu - Sunnyvale CA, US Chi Yu - Saratoga CA, US
Assignee:
Affymetrix, INC. - Santa Clara CA
International Classification:
C12M 1/34 H01L 21/00
US Classification:
435287200, 438001000
Abstract:
The present invention provides methods to process multiple sensors by providing a sensor plate and HT plates. In a preferred embodiment of the invention, methods for assembling microarray pegs and microarray plates are described for high throughput microarray processing.
Consumable Elements For Use With Fluid Processing And Detection Systems
Mark Jones - Reading MA, US Christopher Petroff - Groton MA, US Dan Liu - Sunnyvale CA, US
Assignee:
Affymetrix, Inc. - Santa Clara CA
International Classification:
C12M 1/34
US Classification:
435287200
Abstract:
One embodiment describes an automated and flexible system to analyze probe arrays. It comprises a plurality of arrays mounted on pegs that are moved by an instrument handling robot to liquid reaction stations.
Consumable Elements For Use With Fluid Processing And Detection Systems
Mark Jones - Reading MA, US Christopher Petroff - Groton MA, US Dan Liu - Sunnyvale CA, US
Assignee:
Affymetrix, INC. - Santa Clara CA
International Classification:
C40B 60/12
US Classification:
506 39
Abstract:
One embodiment describes an automated and flexible system to analyze probe arrays. It comprises a plurality of arrays mounted on pegs that are moved by an instrument handling robot to liquid reaction stations.
Automated Assembly Device For Assembly Of Components Of A Disc Drive
Dan Liu - Bloomington MN Michael W. Pfeiffer - Richfield MN
Assignee:
Seagate Technology LLC - Scotts Valley CA
International Classification:
B11B 5127
US Classification:
2960303
Abstract:
An assembly device for assembling components of a disc drive, the assembly device being adapted to assembly components of a disc drive supported at a disc drive station. The assembly members are operably supported for operation between a load position and an install position aligned with the disc drive station. Components are engaged by the assembly members and transported to the disc drive station. At the disc drive station, the components are aligned for assembly in the disc drive.
- Redmond WA, US Dan Liu - Santa Clara CA, US Qi Guo - Sunnyvale CA, US
International Classification:
G06F 16/2457 G06F 17/18 G06F 17/15 G06N 3/04
Abstract:
In an example embodiment, a platform is provided that utilizes information available to a computer system to feed a neural network. The neural network is trained to determine both the probability that a searcher would select a given potential search result if it was presented to him or her and the probability that a subject of the potential search result would respond to a communication from the searcher. These probabilities are combined to produce a single score that can be used to determine whether to present the searcher with the potential search result and, if so, how high to rank the potential search result among other search results. During the training process, a rescaling transformation for each input feature is learned and applied to the values for the input features.
Two-Stage Training With Non-Randomized And Randomized Data
- Redmond WA, US Dan Liu - Santa Clara CA, US Qi Guo - Sunnyvale CA, US Wenxiang Chen - Sunnyvale CA, US Xiaoyi Zhang - Sunnyvale CA, US Lester Gilbert Cottle - Sunnyvale CA, US Xuebin Yan - Sunnyvale CA, US Yu Gong - Santa Clara CA, US Haitong Tian - San Jose CA, US Siyao Sun - Mountain View CA, US Pei-Lun Liao - Sunnyvale CA, US
International Classification:
G06F 16/9538 G06N 20/00 G06F 17/27 G06N 3/04
Abstract:
In an example embodiment, position bias and other types of bias may be compensated for by using two-phase training of a machine-learned model. In a first phase, the machine-learned model is trained using non-randomized training data. Since certain types of machine-learned models, such as those involving deep learning (e.g., neural networks) require a lot of training data, this allows the bulk of the training to be devoted to training using non-randomized training data. However, since this non-randomized training data may be biased, a second training phase is then used to revise the machine-learned model based on randomized training data to remove the bias from the machine-learned model. Since this randomized training data may be less plentiful, this allows the deep learning machine-learned model to be trained to operate in an unbiased manner without the need to generate additional randomized training data.
Amazon
Still Expression, Recent Flower Paintings by Liu Dan
Apr 2013 to 2000 Senior Customer Services RepresentativeHSBC San Francisco, CA Jun 2010 to Apr 2013 Customer Services RepresentativePorto LLC San Francisco, CA May 2009 to Jun 2010 BookkeeperSFSU Business Computer Lab San Francisco, CA Aug 2008 to Dec 2008 Junior Lab Consultant
Education:
San Francisco State University Dec 2009 Bachelors of Science in Business Administration
Skills:
QuickBooks, Microsoft Excel, Word, Access, PowerPoint, and Outlook, Ten key by touch
United States District Court, Central District of California Los Angeles, CA Mar 2012 to May 2012 Extern to the Honorable Dolly M. GeeUniversity of California, Hastings College of the Law San Francisco, CA Oct 2010 to Jun 2011 Research Assistant to Professor Robin FeldmanAsian Pacific American Legal Center Los Angeles, CA Jun 2010 to Aug 2010 Law ClerkUniversity of Southern California Los Angeles, CA Oct 2008 to Aug 2009 Research AssociateJohns Hopkins University School of Medicine Baltimore, MD Jan 2005 to Oct 2008 Postdoctoral Fellow
Education:
University of California, Hastings College of the Law San Francisco, CA May 2012 Juris DoctorUniversity of California, Irvine School of Law Irvine, CA 2011 to 2012University of Southern California Los Angeles, CA 2009 to 2010Peking University Dec 2004 Doctor of Philosophy in Neurobiology
Pamela Macapagal (1995-1999), George Rolfo (1984-1987), Sean Kinney (1995-1999), Betty Lax (1973-1975), Teres Rodney (1991-1995), E Dan Liu (1990-1994)
Dan Liu, a researcher at the Center for Polar and Deep Ocean Development at Shanghai Communications University, told the CSIS panel that the Philippine claims were some kind of political mask and questioned how the experts could evaluate the reefs unless they visited them personally something ne