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Using protocol buffers with Node.js + Swagger + Angular
Generate CommonJs module and typescript declaration file starting from model.proto and copy the result in the frontend folder
typescript  protocol  buffer  **  swagger 
yesterday by pokerone
Chameleons: The Misuse of Theoretical Models in Finance and Economics | Stanford Graduate School of Business
"In this essay I discuss how theoretical models in finance and economics are used in ways that make them “chameleons” and how chameleons devalue the intellectual currency and muddy policy debates. A model becomes a chameleon when it is built on assumptions with dubious connections to the real world but nevertheless has conclusions that are uncritically (or not critically enough) applied to understanding our economy. I discuss how chameleons are created and nurtured by the mistaken notion that one should not judge a model by its assumptions, by the unfounded argument that models should have equal standing until definitive empirical tests are conducted, and by misplaced appeals to “as-if” arguments, mathematical elegance, subtlety, references to assumptions that are “standard in the literature,” and the need for tractability."
economics  theory  to:read  good-economics  ** 
yesterday by MarcK
Machine-Learning Aided Peer Prediction - ec148-liuASCs.pdf
"Information Elicitation without Veri€cation (IEWV) is a classic problem where a principal wants to truthfully
elicit high-quality answers of some tasks from strategic agents despite that she cannot evaluate the quality
of agents’ contributions. Œe established solution to this problem is a class of peer prediction mechanisms,
where each agent is rewarded based on how his answers compare with those of his peer agents. Œese peer
prediction mechanisms are designed by exploring the stochastic correlation of agents’ answers. Œe prior
distribution of agents’ true answers is o‰en assumed to be known to the principal or at least to the agents.
In this paper, we consider the problem of IEWV for heterogeneous binary signal tasks, where the answer
distributions for di‚erent tasks are di‚erent and unknown a priori. A concrete seŠing is eliciting labels for
training data. Here, data points are represented by their feature vectors
x
’s and the principal wants to obtain
corresponding binary labels
y
’s from strategic agents. We design peer prediction mechanisms that leverage not
only the stochastic correlation of agents’ labels for the same feature vector
x
but also the (learned) correlation
between feature vectors
x
’s and the ground-truth labels
y
’s. In our mechanism, each agent is rewarded by how
his answer compares with a reference answer generated by a classi€cation algorithm specialized for dealing
with noisy data. Every agent truthfully reporting and exerting high e‚ort form a Bayesian Nash Equilibrium.
Some bene€ts of this approach include: (1) we do not need to always re-assign each task to multiple workers
to obtain redundant answers. (2) A class of surrogate loss functions for binary classi€cation can help us design
new reward functions for peer prediction. (3) Symmetric uninformative reporting strategy (pure or mixed)
is not an equilibrium strategy. (4) Œe principal does not need to know the joint distribution of workers’
information a priori. We hope this work can point to a new and promising direction of information elicitation
via more intelligent algorithms."
yiling.chen  econ-cs  paper  incentives  mturk  **  to:read 
yesterday by MarcK
Three Misfits in New York - Morraine - Teen Wolf (TV) [Archive of Our Own]
After Gerard beat up Stiles, the Sheriff doesn't believe his son's lies anymore. He demands answers and along the way mends his fragile relationship with his son. While they do their best to make sure that something like Gerard's attack will never happen again, new and unexpected friendships form and Stiles learns that he actually is kind of special. Suddenly it's not Scott by his side but Lydia and Derek, something he wouldn't have dared dreaming about in his wildest fantasies. Coupled with a surprise trip to New York and meeting an Avenger or five, life is bound to change drastically for the three misfits and their families.
1:teenwolf  1:avengers  2:gen  ** 
3 days ago by pollipocket

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