The ML test score: A rubric for ML production readiness and technical debt reduction
Creating reliable, production-level machine learning systems brings on a host of concerns
not found in small toy examples or even large offline research experiments. Testing and …
not found in small toy examples or even large offline research experiments. Testing and …
[PDF][PDF] A reliable effective terascale linear learning system
We present a system and a set of techniques for learning linear predictors with convex
losses on terascale data sets, with trillions of features, 1 billions of training examples and …
losses on terascale data sets, with trillions of features, 1 billions of training examples and …
In defense of minhash over simhash
MinHash and SimHash are the two widely adopted Locality Sensitive Hashing (LSH)
algorithms for large-scale data processing applications. Deciding which LSH to use for a …
algorithms for large-scale data processing applications. Deciding which LSH to use for a …
Combining predictive models in predictive analytical modeling
WH Lin, TH Green, R Kaplow, G Fu… - US Patent 8,370,280, 2013 - Google Patents
(57) ABSTRACT A method can include the actions of receiving a feature vector, the feature
vector including one or more elements; identifying an element type for each of the one or …
vector including one or more elements; identifying an element type for each of the one or …
Dynamic predictive modeling platform
JM Breckenridge, T Green, R Kaplow, WH Lin… - US Patent …, 2013 - Google Patents
5,271,088 A 12, 1993 Bahler 5,583,968 A 12/1996 Trompf 5,586.221 A 12/1996 Isik et al.
5,727,128 A 3, 1998 Morrison 5,752,007 A 5, 1998 Morrison 5,862,513 A 1/1999 Mezzatesta …
5,727,128 A 3, 1998 Morrison 5,752,007 A 5, 1998 Morrison 5,862,513 A 1/1999 Mezzatesta …
Optimal densification for fast and accurate minwise hashing
Minwise hashing is a fundamental and one of the most successful hashing algorithm in the
literature. Recent advances based on the idea of densification (Shrivastava\& Li, 2014) have …
literature. Recent advances based on the idea of densification (Shrivastava\& Li, 2014) have …
Predictive analytical model matching
WH Lin, THK Green, R Kaplow, G Fu… - US Patent …, 2012 - Google Patents
(*) Notice: Subject to any disclaimer, the term of this OTHER PUBLICATIONS patent is
extended or adjusted under 35 Duchi, John, et al.,“Boosting with Structural Sparsity', 2009 …
extended or adjusted under 35 Duchi, John, et al.,“Boosting with Structural Sparsity', 2009 …
Updateable predictive analytical modeling
JM Breckenridge, T Green, R Kaplow, WH Lin… - US Patent …, 2013 - Google Patents
Methods, systems, and apparatus, including computer pro grams encoded on one or more
computer storage devices, for training and retraining predictive models. A series of training …
computer storage devices, for training and retraining predictive models. A series of training …
[PDF][PDF] What's your ML test score? A rubric for ML production systems
Using machine learning in real-world production systems is complicated by a host of issues
not found in small toy examples or even large offline research experiments. Testing and …
not found in small toy examples or even large offline research experiments. Testing and …
Hosting predictive models
WH Lin, TH Green, R Kaplow, G Fu… - US Patent 8,364,613, 2013 - Google Patents
US PATENT DOCUMENTS 5,271,088 A 12, 1993 Bahler 6,243,696 B1 6, 2001 Keeler et al.
6,778,959 B1 8, 2004 Wu et al. 6,879,971 B1 4/2005 Keeler et al. 6,920,458 B1 7/2005 Chu …
6,778,959 B1 8, 2004 Wu et al. 6,879,971 B1 4/2005 Keeler et al. 6,920,458 B1 7/2005 Chu …