Search Results for author:
Found 6 papers, 2 papers with code
Privacy Aware Experiments without Cookies
We propose a two-stage experimental design, where the two brands only need to agree on high-level aggregate parameters of the experiment to test the alternate experiences.
Video Manipulations Beyond Faces: A Dataset with Human-Machine Analysis
To this end, we present VideoSham, a dataset consisting of 826 videos (413 real and 413 manipulated).
Time-uniform central limit theory, asymptotic confidence sequences, and anytime-valid causal inference
While the CLT approximates the distribution of a sample average by that of a Gaussian at a fixed sample size, we use strong invariance principles (stemming from the seminal 1970s work of Komlos, Major, and Tusnady) to uniformly approximate the entire sample average process by an implicit Gaussian process.
Botcha: Detecting Malicious Non-Human Traffic in the Wild
Malicious bots make up about a quarter of all traffic on the web, and degrade the performance of personalization and recommendation algorithms that operate on e-commerce sites.
Forecasting Granular Audience Size for Online Advertising
Orchestration of campaigns for online display advertising requires marketers to forecast audience size at the granularity of specific attributes of web traffic, characterized by the categorical nature of all attributes (e. g. {US, Chrome, Mobile}).
Saliency Prediction for Mobile User Interfaces
However, given the difference in what constitutes a mobile interface, and the usage context of these devices, we postulate that saliency prediction for mobile interface images requires a fresh approach.
