Functions to Interact with the 'FAIR Data Pipeline'
c(person("Sonia", "Mitchell", email = "sonia.mitchell@glasgow.ac.uk",
role = c("cre", "aut"), comment = c(ORCID = "0000-0003-1536-2066")),
person("Ryan", "Field", role = "ctb",
comment = c(ORCID = "0000-0002-4424-9890")))
R implementation of the 'FAIR Data Pipeline API'. The 'FAIR Data
Pipeline' is intended to enable tracking of provenance of FAIR (findable,
accessible and interoperable) data used in epidemiological modelling.
assertthat, cli, configr, dplyr, git2r, httr, jsonlite,
openssl, R6, rhdf5, semver, stats, usethis, utils, yaml

Descent-Based Calibrated Optimal Direct Estimation
Algorithms for solving a self-calibrated l1-regularized quadratic programming problem without parameter tuning. The algorithm, called DECODE, can handle high-dimensional data without cross-validation. It is found useful in high dimensional portfolio selection (see Pun (2018) <https://ssrn.com/abstract=3179569>) and large precision matrix estimation and sparse linear discriminant analysis (see Pun and Hadimaja (2019) <https://ssrn.com/abstract=3422590>).

Low-Level Interface to the '.NET' Virtual Machine Along the
Lines of the R C/Call API
Low-level interface to '.NET' virtual machine along the lines of the R C .call interface.  Can create '.NET' object, call methods, get or set properties, call static functions, etc.
mono 4.x or higher on OSX / Linux, .NET 4.x or
higher on Windows, 'msbuild' and 'nuget' available in the path

Subset Searching Algorithm Using DPP Greedy MAP
c(
person(
given = "Sining",
family = "Ng",
role = c("aut", "cre"),
email = "sining_ng@icloud.com",
comment = c(ORCID = "https://orcid.org/0000-0003-3463-707X")),
person(
given = "Laming",
family = "Chen",
role = c("aut"),
email = "laming.chen@hulu.com"),
person(
given = "Guoxin",
family = "Zhang",
role = c("aut"),
email = "guoxin.zhang@hulu.com"),
person(
given = "Hanning",
family = "Zhou",
role = c("aut"),
email = "eric.zhou@hulu.com"),
person(
given = "Jennifer",
family = "Gillenwater",
role = c("aut"),
email = "jengi@google.com"),
person(
given = "Ed H.",
family = "Chi",
role = c("aut"),
email = "edchi@google.com"),
person(
given = "Sagar",
family = "Jain",
role = c("aut"),
email = "sagarj@google.com"),
person(
given = "Alexander",
family = "Bonomo",
role = c("aut"),
email = "bonomo@google.com"),
person(
given = "Ajith",
family = "Ramanathan",
role = c("aut"),
email = "ajith@google.com"),
person(
given = "Mark",
family = "Wilhelm",
role = c("aut"),
email = "wilhelm@google.com"),
person(
given = "Antonio",
family = "Sánchez",
role = c("cph"),
comment="https://gitlab.com/cantonios"),
person(
given = "Christoph",
family = "Hertzberg",
role = c("cph"),
comment="https://gitlab.com/chhtz"),
person(
given = "David",
family = "Tellenbach",
role = c("cph"),
comment="https://gitlab.com/tellenbach"),
person(
given = "Eigen",
family = "Bugzilla",
role = c("cph"),
comment="https://gitlab.com/eigenbz"),
person(
given = "Gael",
family = "Guennebaud",
role = c("cph"),
comment="https://gitlab.com/ggael"),
person(
given = "Rasmus Munk",
family = "Larsen",
role = c("cph"),
comment="https://gitlab.com/rmlarsen1"),
person(
given = "Guoqiang",
family = "QI",
role = c("cph"),
comment="https://gitlab.com/guoqiangqi1"),
person(
given = "Konstantinos",
family = "Margaritis",
role = c("cph"),
comment="https://gitlab.com/freevec")
)
Given item set, item representation vector, and item ratings,
find a subset with better relevance-diversity trade-off. Also provide
machine learning algorithm to learn item representations maximizing
log likelihood under DPP assumption.
References: [1]Laming Chen, Guoxin Zhang, and Hanning Zhou(2017)<https://lsrs2017.files.wordpress.com/2017/08/lsrs_2017_lamingchen.pdf>
[2]Laming Chen, Guoxin Zhang, and Hanning Zhou(2018)<https://papers.nips.cc/paper/2018/file/dbbf603ff0e99629dda5d75b6f75f966-Paper.pdf>
[3]Wilhelm, Mark & Ramanathan, Ajith & Bonomo, Alexander & Jain, Sagar & Chi, Ed & Gillenwater, Jennifer(2018)<doi:10.1145/3269206.3272018>.
Sining Ng [aut, cre] (<https://orcid.org/0000-0003-3463-707X>),
Laming Chen [aut],
Guoxin Zhang [aut],
Hanning Zhou [aut],
Jennifer Gillenwater [aut],
Ed H. Chi [aut],
Sagar Jain [aut],
Alexander Bonomo [aut],
Ajith Ramanathan [aut],
Mark Wilhelm [aut],
Antonio Sánchez [cph] (https://gitlab.com/cantonios),
Christoph Hertzberg [cph] (https://gitlab.com/chhtz),
David Tellenbach [cph] (https://gitlab.com/tellenbach),
Eigen Bugzilla [cph] (https://gitlab.com/eigenbz),
Gael Guennebaud [cph] (https://gitlab.com/ggael),
Rasmus Munk Larsen [cph] (https://gitlab.com/rmlarsen1),
Guoqiang QI [cph] (https://gitlab.com/guoqiangqi1),
Konstantinos Margaritis [cph] (https://gitlab.com/freevec)