5 citations · 6 across the 13 of their papers we have counts for
13 papers
The Spectral Neuron
Alex Shtoff
As machine learned models increase in complexity and expressive power, features of simpler models, such as intrinsic coefficient transparency and control over the shape of the mode…
tensorFM: Low-Rank Approximations of Cross-Order Feature Interactions
Alessio Mazzetto, Mohammad Mahdi Khalili, Laura Fee Nern +3
We address prediction problems on tabular categorical data, where each instance is defined by multiple categorical attributes, each taking values from a finite set. These attribute…
LiveRAG: A diverse Q&A dataset with varying difficulty level for RAG evaluation
David Carmel, Simone Filice, Guy Horowitz +4
With Retrieval Augmented Generation (RAG) becoming more and more prominent in generative AI solutions, there is an emerging need for systematically evaluating their effectiveness.…
A Simple Method for PMF Estimation on Large Supports
Alex Shtoff
We study nonparametric estimation of a probability mass function (PMF) on a large discrete support, where the PMF is multi-modal and heavy-tailed. The core idea is to treat the emp…
Steady Continuous Monitoring is (Just Barely) Impossible for Tests of Unbounded Length
Eric Bax, Alex Shtoff
AB testing evaluates the difference between a control and a treatment in a statistically rigorous manner. Continuous monitoring allows statistical evaluation of an AB test as it pr…
Early Stopping Based on Repeated Significance
Eric Bax, Arundhyoti Sarkar, Alex Shtoff
For a bucket test with a single criterion for success and a fixed number of samples or testing period, requiring a -value less than a specified value of for the success crit…
Low Rank Field-Weighted Factorization Machines for Low Latency Item Recommendation
Alex Shtoff, Michael Viderman, Naama Haramaty-Krasne +3
Factorization machine (FM) variants are widely used in recommendation systems that operate under strict throughput and latency requirements, such as online advertising systems. FMs…
Improving conversion rate prediction via self-supervised pre-training in online advertising
Alex Shtoff, Yohay Kaplan, Ariel Raviv
The task of predicting conversion rates (CVR) lies at the heart of online advertising systems aiming to optimize bids to meet advertiser performance requirements. Even with the rec…
Unbiased Filtering Of Accidental Clicks in Verizon Media Native Advertising
Yohay Kaplan, Naama Krasne, Alex Shtoff +1
Verizon Media (VZM) native advertising is one of VZM largest and fastest growing businesses, reaching a run-rate of several hundred million USDs in the past year. Driving the VZM n…
Function Basis Encoding of Numerical Features in Factorization Machines
Alex Shtoff, Elie Abboud, Rotem Stram +1
Factorization machine (FM) variants are widely used for large scale real-time content recommendation systems, since they offer an excellent balance between model accuracy and low c…
Conversion-Based Dynamic-Creative-Optimization in Native Advertising
Yohay Kaplan, Yair Koren, Alex Shtoff +2
Yahoo Gemini native advertising marketplace serves billions of impressions daily, to hundreds millions of unique users, and reaches a yearly revenue of many hundreds of millions US…
Efficient algorithms for implementing incremental proximal-point methods
Alex Shtoff
Model training algorithms which observe a small portion of the training set in each computational step are ubiquitous in practical machine learning, and include both stochastic and…
Mitigating Divergence of Latent Factors via Dual Ascent for Low Latency Event Prediction Models
Alex Shtoff, Yair Koren
Real-world content recommendation marketplaces exhibit certain behaviors and are imposed by constraints that are not always apparent in common static offline data sets. One example…