Yahoo Research

Hello @CVPR , check out our “Salient Object-Aware Background Generation using Text-Guided Diffusion Models” paper co-authored by Erfan, Joao, Kapil, Shaunak, Mikhail, Yueh-Ning, and Paloma for the Generative Models for Computer Vision (GCV) workshop @ #CVPR2024 . #YahooResearch

Hi @ieeeICDE 2024, Join Liuqing presenting their work “An Effective, Efficient,and Stable Framework for Query Clustering” co-authored by Chang, Liuqing, Donghyun, Xinyue and Rao on Thirsday @ 13:15, Tuning and Industrial Applications Session in Theater 2. #YahooResearch #ICDE2024

Hi @TheWebConf 2024, Check out our poster presentation on “Mystique: A Budget Pacing System for Performance Optimization in Online Advertising”, co-authored by Rotem, Rani, Alex, Oren, Ariel and Yair, presented today at 12:00 - 1:30 PM #YahooResearch #TheWebConference #TheWebConf

Hi @iclr_conf, check out our poster on May 10, 4:30-6:30PM CEST:"Consistent algorithms for multi-label classification with macro-at-k metrics", by Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch, Rohit Babbar, Strom Borman, Krzysztof Dembczynski. #YahooResearch #ICLR2024 #ICLR

"SDEs for Minimax Optimization" by Enea Monzio Compagnoni, Antonio Orvieto, Hans Kersting, Frank Norbert Proske, Aurelien Lucchi will be up on on Saturday, May 4 (Poster Session 3), 15:00-17:00 See more for poster: virtual.aistats.org/media/PosterPD… and paper: proceedings.mlr.press/v238/monzio-co…

"Imposing Fairness Constraints in Synthetic Data Generation" by Mahed Abroshan, Andrew Elliot, Mahdi Khalili will be up on Thursday, May 2 (Poster Session 1), 17:00-19:00 (See more for poster: virtual.aistats.org/media/PosterPD… and paper: proceedings.mlr.press/v238/abroshan2…)

Join us at @aistats_conf and don’t miss our poster presentations: - "Imposing Fairness Constraints in Synthetic Data Generation" by Mahed, Andrew and Mahdi - "SDEs for Minimax Optimization" by @EneaMC, Antonio,@HansKersting, Frank and Aurelien #YahooResearch #AISTATS2024 #AISTATS

We're pleased to introduce Mystique – our open-source budget-pacing solution tailored for performance optimization in online advertising The source code is available here: lnkd.in/dtuBdAYu #YahooResearch #opensource #advertising #onlineadvertising #budgetpacing

Hello @ieeebigdata 2023! Join Alex and Naama presenting their papers in the Industry & Government sessions on Dec 16th, 2pm CET and Dec 17, 2 PM CET, respectively. #IEEEBigData #IEEEBigData2023 #YahooResearch

Join us at @NeurIPSConf 2023 and don’t miss our poster presentations today and tomorrow 10:45 a.m. CST — 12:45 p.m. CST Read more at: neurips.cc/virtual/2023/p… neurips.cc/virtual/2023/p… neurips.cc/virtual/2023/p… #YahooResearch #NeurIPS2023 #NeurIPS

Meet Martin and Srinath on Tuesday, August 8, 6:00 PM- 8:00 PM during the poster session or on Wednesday August 9, 1:30 PM-3:30 PM when Martin will present the paper in Room 101A, (Advertising 2). Read more at: dl.acm.org/doi/10.1145/35…

The paper co-authored by Martin, Srinath, Djordje, Shubham, Ivan, Nelson and Jelena tackles the problem of extreme multi-label classification in applications related to personalization and recommendation, with satisfactory trade-off between predictive performance & latency.

Hello @kdd_news, you can meet @YahooResearch Research Scientist Martin Pavlovski and Sr Princ Research Engineer Srinath Ravindran presenting “Extreme Multi-Label Classification for Ad Targeting using Factorization”. Check it out: youtube.com/watch?v=SLnMLI… #YahooResearch #KDD2023

“Counterfactual Fairness in Synthetic Data Generation” Co-authored by Mahed Abroshan, Mohammad Mahdi Khalili, Andrew Elliott See details here: openreview.net/pdf?id=tge5NiX…

“Leveraging the Hints: Adaptive Bidding in Repeated First-Price Auctions” Co-authored by Wei Zhang, Yanjun Han, Zhengyuan Zhou, Aaron Flores, Tsachy Weissman See details here: openreview.net/pdf?id=hjqTeP0…

Hello @NeurIPSConf! @YahooResearch is excited to be a Gold Sponsor at #NeurIPS2022 happening this week. Visit us at our booth and meet our scientists and engineers. Find #YahooResearch @ #NeurIPS2022 #NeuralNetworks #NeuralInformationProcessingSystems #Research #MachineLearning