papers

Publications (18)

cs.AI2020

Causal Inference in the Presence of Interference in Sponsored Search Advertising

Razieh Nabi, Joel Pfeiffer, Murat Ali Bayir +2

In classical causal inference, inferring cause-effect relations from data relies on the assumption that units are independent and identically distributed. This assumption is violat…

cs.IR2023

DeepTagger: Knowledge Enhanced Named Entity Recognition for Web-Based Ads Queries

Simiao Zuo, Pengfei Tang, Xinyu Hu +3

Named entity recognition (NER) is a crucial task for online advertisement. State-of-the-art solutions leverage pre-trained language models for this task. However, three major chall…

cs.LG2021

Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction

Shuxi Zeng, Murat Ali Bayir, Joesph J. Pfeiffer +2

It is often critical for prediction models to be robust to distributional shifts between training and testing data. From a causal perspective, the challenge is to distinguish the s…

math.NT2006

On the existence of distortion maps on ordinary elliptic curves

Denis Charles

Distortion maps allow one to solve the Decision Diffie-Hellman problem on subgroups of points on the elliptic curve. In the case of ordinary elliptic curves over finite fields, it…

cs.CR2021

Masked LARk: Masked Learning, Aggregation and Reporting worKflow

Joseph J. Pfeiffer, Denis Charles, Davis Gilton +3

Today, many web advertising data flows involve passive cross-site tracking of users. Enabling such a mechanism through the usage of third party tracking cookies (3PC) exposes sensi…

cs.AI2014

ICE: Enabling Non-Experts to Build Models Interactively for Large-Scale Lopsided Problems

Patrice Simard, David Chickering, Aparna Lakshmiratan +7

Quick interaction between a human teacher and a learning machine presents numerous benefits and challenges when working with web-scale data. The human teacher guides the machine to…