Search Results for author:
Found 13 papers, 6 papers with code
Bounding the fairness and accuracy of classifiers from population statistics
We consider the study of a classification model whose properties are impossible to estimate using a validation set, either due to the absence of such a set or because access to the classifier, even as a black-box, is impossible.
Fairness and Unfairness in Binary and Multiclass Classification: Quantifying, Calculating, and Bounding
We propose a new interpretable measure of unfairness, that allows providing a quantitative analysis of classifier fairness, beyond a dichotomous fair/unfair distinction.
Providing early indication of regional anomalies in COVID19 case counts in England using search engine queries
Our analysis shows that searches for "fever" and "cough" were the most correlated with future case counts, with searches preceding case counts by 16-17 days.
Tracking COVID-19 using online search
Furthermore, we analyse the time series of online search queries in relation to confirmed COVID-19 cases data jointly across multiple countries, uncovering interesting patterns.
Social and Information Networks
Algorithmic Copywriting: Automated Generation of Health-Related Advertisements to Improve their Performance
The marginal contribution of the generator model was, on average, 28\% lower than that of human-authored ads, while the translator model received, on average, 32\% more clicks than human-authored ads.
Privacy, Altruism, and Experience: Estimating the Perceived Value of Internet Data for Medical Uses
Here we describe experiments where methods from Mechanism Design were used to elicit a truthful valuation from users for their Internet data and for services to screen people for medical conditions.
Multi-Season Analysis Reveals the Spatial Structure of Disease Spread
Understanding the dynamics of infectious disease spread in a heterogeneous population is an important factor in designing control strategies.
Characterizing Efficient Referrals in Social Networks
Users of social networks often focus on specific areas of that network, leading to the well-known "filter bubble" effect.
Social and Information Networks
Microsoft Malware Classification Challenge
The Microsoft Malware Classification Challenge was announced in 2015 along with a publication of a huge dataset of nearly 0. 5 terabytes, consisting of disassembly and bytecode of more than 20K malware samples.
Cryptography and Security
Discriminative Learning of Prediction Intervals
Most current methods for constructing prediction intervals offer guarantees for a single new test point.
Automatic Representation for Lifetime Value Recommender Systems
The LTV approach considers the future implications of the item recommendation, and seeks to maximize the cumulative gain over time.
Predicting Counterfactuals from Large Historical Data and Small Randomized Trials
The conventional way to answer this counterfactual question is to estimate the effect of the new treatment in comparison to that of the conventional treatment by running a controlled, randomized experiment.
A Reinforcement Learning System to Encourage Physical Activity in Diabetes Patients
Messages were personalized through a Reinforcement Learning (RL) algorithm which optimized messages to improve each participant's compliance with the activity regimen.
