Xiao Cai

US Patent:

20200112570, Apr 9, 2020

Filed:

Oct 9, 2018

Appl. No.:

16/155382

Inventors:

- San Francisco CA, US
Ze Huang - Santa Clara CA, US
Qiao Wang - Palo Alto CA, US
David Spenser DyTang - San Francisco CA, US
Kiarash Amiri - San Francisco CA, US
Tara Michelle Mitchell - San Francisco CA, US
Xiao Cai - Burlingame CA, US

International Classification:

H04L 29/06
H04W 12/12

Abstract:

A computing system can receive, over one or more networks, location data from the computing devices of user as the user operate throughout a region. For each user, the computing system can determine whether the user is operating a location-spoofing application on the computing device of the user based, at least in part, on the location data received from the computing device of the user.

US Patent:

20190018426, Jan 17, 2019

Filed:

Aug 22, 2018

Appl. No.:

16/108446

Inventors:

- San Francisco CA, US
Xiao Cai - San Bruno CA, US

International Classification:

G05D 1/02
G01C 21/34

Abstract:

A system uses machine models to estimate trip durations or distance. The system trains a historical model to estimate trip duration using characteristics of past trips. The system trains a real-time model to estimate trip duration using characteristics of recently completed trips. The historical and real-time models may use different time windows of training data to predict estimates, and may be trained to predict an adjustment to an initial trip estimate. A selector model is trained to predict whether the historical model, the real-time model, or a combination of the historical and real-time models will more accurately estimate a trip duration, given features associated with a trip duration request, and the system accordingly uses the models to estimate a trip duration. In some embodiments, the real-time model and the selector may be trained using batch machine learning techniques which allow the models to incorporate new trip data as trips complete.