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Private ltlf2asp
Linear Temporal Logic over Finite Traces (LTLf) is a popular logic to reason about finite sequences of events. In LTLf, the (bounded) satisfiability problem refers to whether... -
Private Cybersecurity NER BERT-base-cased model
This method includes a Python script and files of a BERT-base-cased model fine-tuned on our Cybersecurity NER dataset. The method requires as input a list of sentences that... -
Cybersecurity NER SecureBERT model
This method includes a Python script and files of a SecureBERT model fine-tuned on our Cybersecurity NER dataset. The method requires as input a list of sentences that will be...-
JSON
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TXT
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BIN
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JSON
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ZIP
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ZIP
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JSON
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JSON
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JSON
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ZIP
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TXT
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text/x-python
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JSON
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Cybersecurity NER RoBERTa-base model
This method includes a Python script and files of a RoBERTa-base model fine-tuned on our Cybersecurity NER dataset. The method requires as input a list of sentences that will...-
JSON
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TXT
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BIN
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JSON
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ZIP
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JSON
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JSON
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ZIP
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JSON
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JSON
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ZIP
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py
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JSON
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Private Dynamical Linear Upper Confidence Bound (DynLin-UCB)
The repository contains the code to run DynLin-UCB (Dynamical Linear Upper Confidence Bound). DynLin-UCB is an optimistic regret-minimization algorithm that can be used to... -
Online Learning of Order Flow and Market Impact (OLOFMI)
This library performs regime detection in the aggregated order flow time-series and market impact analysis. The required input file is in the format of the message file of the... -
Score-Driven Bayesian Online Change Point Detection (SD-BOCPD)
This code deals with Bayesian online detection in univariate time-series of changepoints, i.e. abrupt variations in the generative parameters of a data, and regimes, i.e.... -
Debiaser for Multiple Variables (DEMV)
DEMV is a Debiaser for Multiple Variables that aims to increase Fairness in any given dataset, both binary and categorical, with one or more sensitive variables, while keeping...-
ipynb
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ipynb
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Reducing radicalizism in social networks by feeds prioritization - Rebalancin...
Code and description of the methodology of the paper "Rebalancing Social Feed to Minimize Polarization and Disagreement" funded by SoBigData ++
