Interests
- Numerical Linear Algebra
- Numerical optimization algorithms for convex and nonconvex problems.
- On-line optimization
- Recommender systems with tabular data
- Software development: design principles, TDD and BDD, C++, C#, F#
Projects
- Incremental proximal point - a library of algorithms for building incremental proximal-point methods for machine learning.
- AutoDiff - a .NET library for automatically computing derivatives of mathematical functions.
- TREM OPF Solver - A MATLAB solver for a class of optimal power flow problems using the Tree Reduction and Expansion Method. See paper below.
- Machine learning proximal operators library - A library of proximal operator implementations of functions useful in machine learning, for implementing algorithms such as online proximal point, or stochastic proximal iteration.
Publications
- Rotem Stram, Rani Abboud, Alex Shtoff, Oren Somekh, Ariel Raviv, Yair Koren Mystique: A Budget Pacing System for Performance Optimization in Online Advertising. to appear in The Web Conference 2024
- Alex Shtoff, Yohay Kaplan, Ariel Raviv Improving conversion rate prediction via self-supervised pre-training in online advertising. in 2023 IEEE International Conference on Big Data (BigData). doi: 10.1109/BigData59044.2023.10386162
- Yohay Kaplan, Yair Koren, Alex Shtoff, Oren Somekh Conversion-Based Dynamic-Creative-Optimization in Native Advertising. 2022 IEEE International Conference on Big Data (BigData) (Preprint)
- Alex Shtoff Efficient implementation of incremental proximal-point methods. Submitted (Preprint, code)
- Alex Shtoff, Yair Koren Mitigating Divergence of Latent Factors via Dual Ascent for Low Latency Event Prediction Models. 2021 IEEE International Conference on Big Data (Big Data), 2021, pp. 1940-1949 (Preprint)
- Yohay Kaplan, Naama Krasne, Alex Shtoff, and Oren Somekh Unbiased Filtering of Accidental Clicks in Verizon Media Native Advertising. Proceedings of the 30th ACM International Conference on Information & Knowledge Management, 3878–3887 (October 2021)
- Amir Beck, Yuval Beck, Yoash Levron, Alex Shtof, Luba Tetruashvili Globally solving a class of optimal power flow problems in radial networks by tree reduction Journal of Global Optimization 72 (3), 373–402 (November 2018)
(paper, software)
- Alex Shtof, Alexander Agathos, Yotam Gingold, Ariel Shamir, Daniel Cohen‐Or Geosemantic Snapping for Sketch‐Based Modeling Computer Graphics Forum 32 (2pt2), 245-253 (May 2013)
(paper, paper supplemental, video)
Conference talks
- Globally Solving a Class of Optimal Power Flow Problems in Radial Networks, International Symposium on Mathematical Programming (July 2018) (presentation).
Thesis
Links