Adversarial Learning in RecSys @AdversRecSys
Page dedicated to Research on Adversarial Machine Learning for Recommendation and Search. #TrustworhyML #Attack #Defense #Privacy. Tag the page to be retweeted! sisinflab.github.io Italy Joined May 2021-
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Today, there was a fascinating workshop on Technical Robustness& Safety on AI led by @biggiobattista. Battista is Associate Professor at the @univca and co-founder of the cybersecurity company @pluribus_one . We are grateful for our various partners in the ELSA project.
What a first day of #recsys2023 proper! Talked with several people & presented one of our works. Glad many reacted positively. My highlight from the day is SharpCF presented by @vivwylai from Visa. Good idea, clean execution & may also improve other algos. dl.acm.org/doi/abs/10.114…
Our preprint "Formalizing #Multimedia #Recommendation through #Multimodal Deep Learning" is now out on arXiv! arxiv.org/pdf/2309.05273… (1/2)
Read our last paper @SIGIRConf "Denoise to protect: a method to robustify visual recommenders from adversaries" to get insights on how to defend a #RecSys #IR engine from malicious product images presented today! 🔗dl.acm.org/doi/10.1145/35… 🧑💻 @sisinflab
-11 days to #SIGIR2023 🚀 I will present a novel defense strategy for robustify visual recommenders. If you are interested feel free to take a look at our work or get in touch with us @merrafelice @dmalitesta @walteranelli @TommasoDiNoia researchgate.net/publication/37…
Clean product images to reduce the risk of malicious users! Check our work in #Adversarial #RecSys that shortly will be presented at #SIGIR2023!
Clean product images to reduce the risk of malicious users! Check our work in #Adversarial #RecSys that shortly will be presented at #SIGIR2023!
(1/3) Too excited to share that the last work on my Ph.D. dissertation on #Adversarial #RecSys "Denoise to protect: a method to robustify visual recommenders from adversaries" has been accepted as Short Paper at @SIGIRConf #SIGIR2023. 📎 Pre-print soon!
📢 Are you on the job market this year or looking for new opportunities, whether full-time, internships, postdocs, etc? We would love to promote your work. Write a tweet describing your work and tag us (@trustworthy_ml), and we will retweet you! :)
We are excited to present a new event in our seminar series on ML Security! We will host @EdwardRaffML (@BoozAllen ) on February 16, 2023, at 16:00 CET. Registration: eventbrite.com/e/machine-lear… @adversarial_ML @trustworthy_ml @aivillage_dc @RedTeamVillage_
Models such as Stable Diffusion are trained on copyrighted, trademarked, private, and sensitive images. Yet, our new paper shows that diffusion models memorize images from their training data and emit them at generation time. Paper: arxiv.org/abs/2301.13188 👇[1/9]
If you are looking for new challenges in 2023, consider applying for a university assistant/postdoc position (40h/week, 6 years, on topics of RecSys, IR, NLP, MM, Fairness, etc.) in our group at @jkulinz @cpjku bit.ly/3WsGb5n @ACMRecSys @SIGIRConf @SIGIR2013 Please RT
While it's true that you can watch our @NeurIPSConf tutorial recording at any time, our Q&A (in 50 mins) and panel (in 60 mins) will be live! Come join us to discuss foundation models @RisingSayak @sijialiu17 @payel791 @AlexGittens8 @RTFMCelia @uiuc_aisecure @HildeKuehne
While it's true that you can watch our @NeurIPSConf tutorial recording at any time, our Q&A (in 50 mins) and panel (in 60 mins) will be live! Come join us to discuss foundation models @RisingSayak @sijialiu17 @payel791 @AlexGittens8 @RTFMCelia @uiuc_aisecure @HildeKuehne https://t.co/Ml18VSoJA5
Special Issue on "Trustworthy Recommender System" has a deadline in January 15, 2023. Strong works on #security #privacy, #explainability and #fairness of recommender systems, and conversational agents are welcome to submit their work to #ACM_TORS.
Special Issue on "Trustworthy Recommender System" has a deadline in January 15, 2023. Strong works on #security #privacy, #explainability and #fairness of recommender systems, and conversational agents are welcome to submit their work to #ACM_TORS.
My Ph.D. student Sejoon Oh @GTCSE presenting his paper on stability of recommender systems at ACM @cikm2022 #CIKM2022 Paper link: faculty.cc.gatech.edu/~srijan/pubs/C…
📢 1/ Call for Proposals: Research Brainstorm on “The Future of Trustworthy ML” at the Trustworthy ML Initiative Symposium on 10/27. Details 👇
Very exciting and proud work on scaling up robust (adversarial) training via efficient distributed optimization from an amazing team and collaborators! Special kudos to @sijialiu17 for his leadership to make all these great things happen @IBMResearch @MITIBMLab @UncertaintyInAI
Very exciting and proud work on scaling up robust (adversarial) training via efficient distributed optimization from an amazing team and collaborators! Special kudos to @sijialiu17 for his leadership to make all these great things happen @IBMResearch @MITIBMLab @UncertaintyInAI
"TUTORIAL ON ADVERSARIAL ROBUSTNESS OF DEEP LEARNING" live in less than 2 hours at @CIKM2021 by Dr. Wenjie Ruan, @XinpingYi, and Dr. Xiaowei Huang. Tutorial WebSite: tutorial-cikm.trustai.uk #Adversarial #Robustness #CIKM2021 #DeepLearning
2 papers in the main track at #RecSys2022 @ACMRecSys Adversary or Friend? An adversarial Approach to Improving Recommender Systems by Shivaswamy and Dario Garcia (@NetflixResearch) Defending Substitution-based Profile Pollution Attacks on Sequential Recommenders by Yue et al.
Paper recommendation: arxiv.org/abs/2206.12401 @kdd_news
Paper recommendation: arxiv.org/abs/2206.12401 @kdd_news
The paper submission deadline for the 15th ACM workshop on Artificial Intelligence and Security (aisec.cc), co-located with @acm_ccs, is postponed to July 20! #MLsec #MachineLearning #AI #adversarial @adversarial_ML #malware @trustworthy_ml @RedTeamVillage_
The paper submission deadline for the 15th ACM workshop on Artificial Intelligence and Security (aisec.cc), co-located with @acm_ccs, is postponed to July 20! #MLsec #MachineLearning #AI #adversarial @adversarial_ML #malware @trustworthy_ml @RedTeamVillage_

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