#30daysofflcode search results
Completed the #30DaysOfFLCode Learned so much and advanced mixing of PHEs project. Next up: zk proofs for verifiable computations to enhance PETs. Grateful for the journey and the amazing people I met! 🚀 the journey will continue …
🌟 Protect privacy while advancing AI by using differential privacy combined with federated learning! Practical, efficient -- and now more accessible through Flower 🌐 To support #30DaysOfFLCode, we've provided a range of differential privacy concepts we offer via the…
I'm publicly committing to the #30DaysOfFLCode Challenge! Join me in learning more about #FederatedLearning → 30DaysOfFLCode.com
Earned my certificate in Federated Learning through the #30DaysOfFLCode challenge! 🚀 Big thanks to the @openminedorg organizers and it's amazing community for driving the future of AI forward. Let’s keep pushing boundaries together! 🌟
🎉 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞 𝐂𝐨𝐦𝐩𝐥𝐞𝐭𝐞𝐝! 🎉 I’m so excited to share that I’ve finished the #30DaysOfFLCode challenge! 🙌 #30DaysOfFLCode #Completed #Learning #PrivacyTech @openminedorg
#30DaysOfFLCode Day 18: Learnt concepts on Secure Multi-Party Computation. - courses.openmined.org/courses/founda… - youtube.com/watch?v=NXFLrm… Good old NPTEL :')
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Lec 01 What is Secure Multi-Party Computation (MPC)?
Days 30: #30DaysOfFLCode 🚀 A journey that just started on its last day: Today I started reviewing syftbox and took my notes. I used the older version 0.2.9, but the new version is also interesting. It seems like we will be working on it for a long time. Thanks to the…
I don’t usually wear stuff like this, but this one’s pretty cool. It makes you feel like you belong somewhere. And honestly, I care about that feeling 👊🦁 #30DaysOfFLCode @openminedorg
Day13. #30DaysOfFLCode #FederatedLearning → youtube.com/watch?v=yOsrAn (wip) + Attended the Recommender Systems discussion. @siddhant230 and others
#30DaysOfFLCode Day 24: 1. PHOTON - Enable data source segregation from compute in FL. 2. DEPT - Unique embeddings for each client 3. WorldLM - Federations of federation s.t the same settings (eg DP) don't need to be applied to all participating silos (eg legal, privacy)
Day 29: Fine-tuning LLMs with Federated Learning on heterogeneous servers! 🚀 Techniques like PEFT, gradient compression, & low-rank approximation enable privacy-preserving collaboration, details: github.com/moisesvw/30Day… 🌐 #30DaysOfFLCode by @openminedorg
Day 7 Fuzzy regulations lead to uncertainties and loop holes. The goal should be finding a "safe zone" where there is compliance with no ambiguity. #30DAYSOFFLCODE linkedin.com/posts/afsoun0_…
#30DaysOfFLCode Day 14: Learnt Homomorphic Encryption concepts from this tutorial by @openminedorg: courses.openmined.org/courses/founda… Cybersec is indeed magic lol.
#30DaysOfFLCode Day 27: A nice, light-weight tutorial where they discuss FL for non-iid data. Got me reading about different types of non-iid-ness and open research problems. blog.openmined.org/federated-cred…
Day 4 of my #30DaysOfFLCode Challenge from @openminedorg : Working on reproducing the results of "Federated Heterogeneous Graph Neural Network for Privacy-preserving Recommendation" My GitHub for the notes: github.com/SlokomManel/30… Here's a quick summary of FedHGNN:
Day 9: Syftbox installation complete, and the datasite is now connected! #30DaysOfFLCode linkedin.com/posts/afsoun0_…
linkedin.com
#30daysofflcode #syftbox | Afsoun O
Day 9: Installation complete, and the datasite is now connected! I encountered some issues initially, but with Siddhant Rai's guidance, I understood that I needed to install WSL (Windows Subsystem...
Day 26 of #30DaysOfFLCode! 🤓 Hands-on today with PySyft! I explored its tools for privacy-preserving AI, diving deeper into secure computations and federated learning. Practical experience makes all the difference! 🔒🤖
#30DaysOfFLCode Day 28: - Aggregation algorithms in Federated Learning: youtube.com/watch?v=6Pl5FV… - SCAFFOLD: youtube.com/watch?v=GYHrHq… lessgooo
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FLOW Seminar #4: Praneeth Karimireddy (EPFL) SCAFFOLD: an algorithm...
Day 24 of #30DaysOfFLCode 🔒 Today, I am exploring FATE-LLM: A Industrial Grade Federated Learning Framework for Large Language Models Learn more from the authors: 📘 Full Paper: arxiv.org/pdf/2310.10049 🎥 Short Talk: youtube.com/watch?v=mKitmN…
Day 23 of #30DaysOfFLCode 🔒 Today, I explored a fascinating case study on how Apple combines Machine Learning with Homomorphic Encryption to enhance user privacy. Read more here: machinelearning.apple.com/research/homom…
I am publicly taking the #30daysofFLCode challenge with @openmind_agi . I hope I can share all my learnings day wise here. #FederatedLearning #FL
I'm publicly committing to the #30DaysOfFLCode Challenge! Join me in learning more about #FederatedLearning → 30DaysOfFLCode.com
I'm publicly committing to the #30DaysOfFLCode Challenge! Join me in learning more about #FederatedLearning → 30DaysOfFLCode.com
SyftBox : Compute on private data without accessing it! 🔹 Data Owners keep control & share only results 🔹 API Developers run secure computations 🔹 Fully decentralized & privacy-first syftbox-documentation.openmined.org/tutorials/comp… #30DaysOfFLCode #AI #Privacy #Decentralization #SyftBox
I'm publicly committing to the #30DaysOfFLCode Challenge! Join me in learning more about #FederatedLearning and Privacy Enhancing Technologies (PETs). Let’s build our skills and shape the future of AI together! 🚀 Check out here: 30DaysOfFLCode.com #AI #OpenMined
I'm publicly committing to the #30DaysOfFLCode Challenge! Join me in learning more about #FederatedLearning → 30DaysOfFLCode.com
Last month, I completed the #30DaysOfFLCode Challenge by @openminedorg! I encourage anyone interested in learning about privacy-preserving technologies, security in AI, and FL to take the challenge! info.openmined.org/30daysofflcode
Day 30: Efficient Pruning for Machine Learning under HE -Pruning boosts traditional ML efficiency but not in HE-based ML. Tile sparsity enables efficient efficient pruning by skipping entire blocks of encrypted data, reducing operations. fhe.org/meetups/041-Ef… #30DaysOfFLCode
Day 29: Concrete ML - Machine Learning on Encrypted Data A model is converted to an FHE-compatible format via quantization, and its weights are encrypted. It then performs predictions on FHE-encrypted data, with the results being encrypted youtube.com/watch?v=DP_4OB… #30DaysOfFLCode
Day 28: Verifiable FHE 1 Users can employ ZKP to verify that the FHE encryption of their plain query was correctly done. On the server side, it can be used to verify that the computations on this encrypted data are carried out correctly. blog.sunscreen.tech/snarks-shortco… #30DaysOfFLCode
Day 27: Apple's Enhanced Visual Search with ML, HE & PNNS ML model on your device identifies matching landmarks in your photo gallery, creates an encrypted code from them which is used with HE to retrieve a desired photo from Apple's server machinelearning.apple.com/research/homom… #30DaysOfFLCode
Day 26: Private Information Retrieval PIR allows a user to send an encrypted query to a server, which then performs homomorphic computations to retrieve the desired information, sending back the result still encrypted to preserve privacy. machinelearning.apple.com/research/homom… #30DaysOfFLCode
Day 25: Problems and Research Trends in Federated Learning I read about problems in FL which requires further research. This includes improving efficiency and effectiveness, reduction in training biases, and robustness against attacks. drive.google.com/file/d/1QGY2Zy… #30DaysOfFLCode
Day 24: Cross-Silo Federated Learning -It involves fewer clients (organizations) with specific identities -Most clients participate in each FL round with very few going offline. -Data Partition can be vertical or horizontal across clients. drive.google.com/file/d/1QGY2Zy… #30DaysOfFLCode
Day 23: Cross-device Federated Learning (FL) and Challenges - In cross-device FL, devices share the same features but have different data samples - Communication among FL clients is challenging because the mobile devices often go offline. drive.google.com/file/d/1QGY2Zy… #30DaysOfFLCode
Day 22: Cross-Device Federated Learning at Apple Apple uses differentially private federated learning to personalize Siri. This enables an iPhone to respond exclusively to its owner’s voice, even in the presence of other phones and voices technologyreview.com/2019/12/11/131… #30DaysOfFLCode
technologyreview.com
How Apple personalizes Siri without hoovering up your data
The tech giant is using privacy-preserving machine learning to improve its voice assistant while keeping your data on your phone.
Day 21: Privacy Preserving AI - Lecture (Andrew Trask - OpenMined) Focuses on how privacy enhancing technologies such as differential privacy, multiparty computation and federated learning enables remote training of models on private data.youtu.be/4zrU54VIK6k?fe… #30DaysOfFLCode
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Privacy Preserving AI (Andrew Trask) | MIT Deep Learning Series
Completed the #30DaysOfFLCode Learned so much and advanced mixing of PHEs project. Next up: zk proofs for verifiable computations to enhance PETs. Grateful for the journey and the amazing people I met! 🚀 the journey will continue …
Day 20: Beyond Privacy Trade-offs with Structured Transparency Participants can't prevent other collaborators from misusing their data (copy problem). The proposed techniques enable collaborators to reduce the risks of collaboration. arxiv.org/abs/2012.08347 #30DaysOfFLCode
Day 19: Federated fine-tuning of LLMs (Part 3) I continued with the decentralized/federated fine-tuning of the LLM, leveraging parameter efficient fine-tuning to optimize communication efficiency and differential privacy to improve privacy learn.deeplearning.ai/courses/intro-… #30DaysOfFLCode
🗂️ epyepe.cloud/f/4l1ecyzp1u8 🗂️ epyepe.cloud/f/4o719sibdy8 🗂️ epyepe.cloud/f/m1tmflrzjkc 🗂️ epyepe.cloud/f/010snaa4id2 Bhsjdh.to
⭑ [ rt like before use! ] ⟢ ⭐️🍎 free .png files/frames🐟🧃 drive.google.com/drive/folders/… ‧₊˚ ⋅ 𓐐𓎩 ‧₊˚ ⋅
cdn.co-v.lat/a/9uYtrE8uw alst.fun/e/srhCKJWFm alst.fun/e/bPJFJioSK alst.fun/e/CRQpVMnGS alst.fun/e/QY5kbto2b alst.fun/e/V7o3gVUkn alst.fun/e/ysQvPX7wA alst.fun/e/Qx8KanwzX
Some of my personal favorites from the 30 day challenge I did back in November ✨
Day thirty of attempting to capture the essence of the abyss through a digital medium
౨ৎ [ like rt before use ] ⋆. 𐙚 ̊ 💗 pink png frames ! 🎀 🎀 + some white png that would match to be mixed💗 🫧 personal use only !! 🫧 🔗 drive.google.com/drive/folders/…
cdn.co-v.lat/a/5uXtrE9er alst.fun/e/f4DvTX7VC alst.fun/e/AbYSqu7Md alst.fun/e/6GRHTz8DS alst.fun/e/MsktyTnAg alst.fun/e/6aQnmUJHA alst.fun/e/JgvbWNUo9 alst.fun/e/nkBvUrPA8
Day thirty-one of attempting to capture the essence of the abyss through a digital medium
🩷 rt like before use 🩷 🎸 i⭐️u png frames 🎸 ❗️ personal use only ❗️ 🔗 drive.google.com/drive/u/4/fold…
Day thirty-five of attempting to capture the essence of the abyss through a digital medium
Day thirty-four of attempting to capture the essence of the abyss through a digital medium
Day thirty-three of attempting to capture the essence of the abyss through a digital medium
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