Search Results for author: Elad Yom-Tov

Found 13 papers, 6 papers with code

Bounding the fairness and accuracy of classifiers from population statistics

1 code implementation ICML 2020 Sivan Sabato, Elad Yom-Tov

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

1 code implementation7 Jun 2022 Sivan Sabato, Eran Treister, Elad Yom-Tov

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

no code implementations23 Jul 2020 Elad Yom-Tov, Vasileios Lampos, Ingemar J. Cox, Michael Edelstein

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

1 code implementation arXiv 2020 Vasileios Lampos, Simon Moura, Elad Yom-Tov, Michael Edelstein, Maimuna Majumder, Yohhei Hamada, Molebogeng X. Rangaka, Rachel A. McKendry, Ingemar J. Cox

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

no code implementations27 Oct 2019 Brit Youngmann, Ran Gilad-Bachrach, Danny Karmon, Elad Yom-Tov

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

no code implementations20 Jun 2019 Gilie Gefen, Omer Ben-Porat, Moshe Tennenholtz, Elad Yom-Tov

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

1 code implementation11 Feb 2019 Inbar Seroussi, Nir Levy, Elad Yom-Tov

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

1 code implementation1 May 2018 Reut Apel, Elad Yom-Tov, Moshe Tennenholtz

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

2 code implementations22 Feb 2018 Royi Ronen, Marian Radu, Corina Feuerstein, Elad Yom-Tov, Mansour Ahmadi

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

no code implementations16 Oct 2017 Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov

Most current methods for constructing prediction intervals offer guarantees for a single new test point.

Prediction Intervals

Automatic Representation for Lifetime Value Recommender Systems

no code implementations23 Feb 2017 Assaf Hallak, Yishay Mansour, Elad Yom-Tov

The LTV approach considers the future implications of the item recommendation, and seeks to maximize the cumulative gain over time.

Recommendation Systems Reinforcement Learning (RL)

Predicting Counterfactuals from Large Historical Data and Small Randomized Trials

no code implementations24 Oct 2016 Nir Rosenfeld, Yishay Mansour, Elad Yom-Tov

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

no code implementations13 May 2016 Irit Hochberg, Guy Feraru, Mark Kozdoba, Shie Mannor, Moshe Tennenholtz, Elad Yom-Tov

Messages were personalized through a Reinforcement Learning (RL) algorithm which optimized messages to improve each participant's compliance with the activity regimen.

reinforcement-learning Reinforcement Learning (RL)

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