#machineunlearning search results

Locking in from today to learn AI, Machine learning, deep learning. Started with hands on machine learning book by @aureliengeron Completed First chapter, can't wait to finish another chapter. #machineunlearning #DeepLearning


When a company claims that your personal data has been removed from their model, have you ever wondered whether they've indeed done so? 🤔 If a new paper on arXiv claims that its proposed #MachineUnlearning algorithm can unlearn your personal data from an #LLM, how do we know…


In the era of Large Language Models (LLMs) like ChatGPT, deleting users' data is a complicated beast. We're designing solutions to help LLMs forget, advancing #machineunlearning techniques to protect the #righttobeforgotten. 🔗 spr.ly/6017P2VoU

Data61news's tweet image. In the era of Large Language Models (LLMs) like ChatGPT, deleting users' data is a complicated beast.

We're designing solutions to help LLMs forget, advancing #machineunlearning techniques to protect the #righttobeforgotten. 

🔗 spr.ly/6017P2VoU

"Ever seen an AI with a messy memory? Time for some digital decluttering with machine unlearning! 🧹🔒 Let's keep our data safe while teaching AI to forget the fluff. #AIHoarding #DataPrivacy #MachineUnlearning #ArtificialIntelligence #openAI Read the full article…

thyshaaz's tweet image. "Ever seen an AI with a messy memory? Time for some digital decluttering with machine unlearning! 🧹🔒 Let's keep our data safe while teaching AI to forget the fluff. #AIHoarding #DataPrivacy #MachineUnlearning #ArtificialIntelligence #openAI 
Read the full article…

🤩 Glad to see our work "Towards Adversarial Evaluations of Inexact Machine Unlearning" arxiv.org/abs/2201.06640 inspire "Towards Unbounded Machine Unlearning" arxiv.org/abs/2302.09880 from #GoogleBrain @GoogleAI @Eleni30fillou & @uniofwarwick. #MachineUnlearning #ProfGiri🧵👇🏽

ponguru's tweet image. 🤩 Glad to see our work "Towards Adversarial Evaluations of Inexact Machine Unlearning" arxiv.org/abs/2201.06640 inspire "Towards Unbounded Machine Unlearning" arxiv.org/abs/2302.09880 from #GoogleBrain @GoogleAI @Eleni30fillou & @uniofwarwick. #MachineUnlearning #ProfGiri🧵👇🏽

A comprehensive look into machine unlearning as a tool for improving AI safety by strategically removing specific data influence. #AISafety #MachineUnlearning #KnowledgeRemoval

GoatstackAI's tweet image. A comprehensive look into machine unlearning as a tool for improving AI safety by strategically removing specific data influence. #AISafety #MachineUnlearning #KnowledgeRemoval

Machine Unlearning in Generative AI: A Survey #MachineUnlearning #GenAI 👉 buff.ly/3YnOuDz

woojinrad's tweet image. Machine Unlearning in Generative AI: A Survey 

#MachineUnlearning #GenAI
👉 buff.ly/3YnOuDz

AI models use machine unlearning to forget specific data while preserving performance, respecting privacy and user preferences. Learn more at ez.works #MachineUnlearning #AIRespectPrivacy

EZ_Official_'s tweet image. AI models use machine unlearning to forget specific data while preserving performance, respecting privacy and user preferences. Learn more at ez.works #MachineUnlearning #AIRespectPrivacy

Q: What techniques can be used for machine unlearning? A: Techniques like adversarial training, generative models, and selective parameter updates can be employed for machine unlearning. @MichaelDell #MachineUnlearning

JordanJamesEtem's tweet image. Q: What techniques can be used for machine unlearning?
A: Techniques like adversarial training, generative models, and selective parameter updates can be employed for machine unlearning.
@MichaelDell #MachineUnlearning
JordanJamesEtem's tweet image. Q: What techniques can be used for machine unlearning?
A: Techniques like adversarial training, generative models, and selective parameter updates can be employed for machine unlearning.
@MichaelDell #MachineUnlearning
JordanJamesEtem's tweet image. Q: What techniques can be used for machine unlearning?
A: Techniques like adversarial training, generative models, and selective parameter updates can be employed for machine unlearning.
@MichaelDell #MachineUnlearning
JordanJamesEtem's tweet image. Q: What techniques can be used for machine unlearning?
A: Techniques like adversarial training, generative models, and selective parameter updates can be employed for machine unlearning.
@MichaelDell #MachineUnlearning

Goldfish, an efficient federated unlearning framework, addresses data removal constraints while maintaining performance. #MachineUnlearning #DataPrivacy #FederatedLearning

GoatstackAI's tweet image. Goldfish, an efficient federated unlearning framework, addresses data removal constraints while maintaining performance. #MachineUnlearning #DataPrivacy #FederatedLearning

I am happy to share that our paper, "Towards Robust and Cost-Efficient Knowledge Unlearning for Large Language Models", has been accepted to #ICLR2025! Stay tuned for the camera-ready version and the code release! #MachineUnlearning #LLMs

_sungmin_cha's tweet image. I am happy to share that our paper, "Towards Robust and Cost-Efficient Knowledge Unlearning for Large Language Models", has been accepted to #ICLR2025! Stay tuned for the camera-ready version and the code release! #MachineUnlearning #LLMs

#MachineUnlearning—a remarkable advancement in AI—allows models to 'forget’ specific pieces of data, eliminating the need to restart the training process from scratch. As #AI continues to advance, #innovations like these will be vital to balancing efficiency & ethical data use.

EMERITUS_INST's tweet image. #MachineUnlearning—a remarkable advancement in AI—allows models to 'forget’ specific pieces of data, eliminating the need to restart the training process from scratch. As #AI continues to advance, #innovations like these will be vital to balancing efficiency & ethical data use.

Q: What challenges are associated with machine unlearning in deep learning models? A: Challenges include catastrophic forgetting, preserving useful knowledge, and maintaining model performance during unlearning. #MachineUnlearning #Challenges @pmarca @bhorowitz @elonmusk

JordanJamesEtem's tweet image. Q: What challenges are associated with machine unlearning in deep learning models?
A: Challenges include catastrophic forgetting, preserving useful knowledge, and maintaining model performance during unlearning.
#MachineUnlearning #Challenges 
@pmarca @bhorowitz @elonmusk
JordanJamesEtem's tweet image. Q: What challenges are associated with machine unlearning in deep learning models?
A: Challenges include catastrophic forgetting, preserving useful knowledge, and maintaining model performance during unlearning.
#MachineUnlearning #Challenges 
@pmarca @bhorowitz @elonmusk
JordanJamesEtem's tweet image. Q: What challenges are associated with machine unlearning in deep learning models?
A: Challenges include catastrophic forgetting, preserving useful knowledge, and maintaining model performance during unlearning.
#MachineUnlearning #Challenges 
@pmarca @bhorowitz @elonmusk
JordanJamesEtem's tweet image. Q: What challenges are associated with machine unlearning in deep learning models?
A: Challenges include catastrophic forgetting, preserving useful knowledge, and maintaining model performance during unlearning.
#MachineUnlearning #Challenges 
@pmarca @bhorowitz @elonmusk

As LLMs like ChatGPT evolve, compliance with GDPR's data deletion rules presents complex challenges. Emerging machine unlearning aims to help models forget specific data without full retraining. 🤖 #MachineUnlearning #GDPR #AI_regulation link: ift.tt/V6BxpjH

TweetThreatNews's tweet image. As LLMs like ChatGPT evolve, compliance with GDPR's data deletion rules presents complex challenges. Emerging machine unlearning aims to help models forget specific data without full retraining. 🤖 #MachineUnlearning #GDPR #AI_regulation

link: ift.tt/V6BxpjH

🎉 Proud to share that Side Effects of Erasing Concepts from Diffusion Models was accepted to EMNLP 2025 (Findings). #EMNLP2025 #MachineUnlearning #ConceptErasure

🚨 Our paper “Side Effects of Erasing Concepts from Diffusion Models” has been accepted to EMNLP 2025 (Findings)! #EMNLP2025 We investigate the vulnerabilities of Concept Erasure Techniques (CETs) Big shoutout to my amazing collaborators @sourajitCS @manasgaur90 @trgokhale 1/n



What if AI didn’t just think - but forgot? 🤯 Imagine models designed to unlearn outdated ideas, bad data, and yesterday’s biases - evolving in real-time like living minds. Not just smarter, but wiser. Just a thought. #AI #MachineUnlearning #FutureTech #EthicalAI #NextGenAI


AI text-to-speech could soon 'unlearn' to mimic voices, a game-changer in the fight against audio deepfakes. #MachineUnlearning #AISafety


महत्त्वपूर्ण शब्दावली: मशीन अनलर्निंग (Machine Unlearning) sanskritiias.com/hindi/importan… #MachineUnlearning #importantterminology #importantwords #prelims #importantconcepts #India #upsc #prelimssexam #pcs #sanskritiias

sanskritiias's tweet image. महत्त्वपूर्ण शब्दावली: 
  
मशीन अनलर्निंग (Machine Unlearning)

sanskritiias.com/hindi/importan…

#MachineUnlearning #importantterminology #importantwords #prelims #importantconcepts #India #upsc #prelimssexam #pcs #sanskritiias

When a company claims that your personal data has been removed from their model, have you ever wondered whether they've indeed done so? 🤔 If a new paper on arXiv claims that its proposed #MachineUnlearning algorithm can unlearn your personal data from an #LLM, how do we know…


Exploring #MachineUnlearning teaching AI to forget on demand. Mapping privacy-first needs across finance, governance, startups & enterprises. Know a use case? Let’s chat and co-create value—open to partnerships that help us all generate leads! #DataPrivacy #GDPR #TrustworthyAI


✨ A heartfelt thank you to our mentor Shaista Tarannum for her constant guidance, insightful feedback, and support throughout this journey. 🙌 Special thanks to my amazing teammates: Varsha D R, Vidya Shree M S, Ananya K #AI #MachineUnlearning #groupaproject

BhavanaNB1's tweet image. ✨ A heartfelt thank you to our mentor Shaista Tarannum for her constant guidance, insightful feedback, and support throughout this journey.

🙌 Special thanks to my amazing teammates:
Varsha D R, Vidya Shree M S, Ananya K

#AI #MachineUnlearning  #groupaproject
BhavanaNB1's tweet image. ✨ A heartfelt thank you to our mentor Shaista Tarannum for her constant guidance, insightful feedback, and support throughout this journey.

🙌 Special thanks to my amazing teammates:
Varsha D R, Vidya Shree M S, Ananya K

#AI #MachineUnlearning  #groupaproject
BhavanaNB1's tweet image. ✨ A heartfelt thank you to our mentor Shaista Tarannum for her constant guidance, insightful feedback, and support throughout this journey.

🙌 Special thanks to my amazing teammates:
Varsha D R, Vidya Shree M S, Ananya K

#AI #MachineUnlearning  #groupaproject

🚨 ACM India Industry Webinar Alert! Join us for an insightful talk on Machine Unlearning & Multimodal Negation in GenAI 🤖🧠 🗓️ June 21, 2025 🕚 11:00 AM IST 🎙️ Prof. Mayank Vatsa, IIT Jodhpur 🔗 Register: lnkd.in/dqNHBBzG #ACMIndia #GenAI #MachineUnlearning #AIethics

Indiaacm's tweet image. 🚨 ACM India Industry Webinar Alert!

Join us for an insightful talk on Machine Unlearning & Multimodal Negation in GenAI 🤖🧠

🗓️ June 21, 2025
🕚 11:00 AM IST
🎙️ Prof. Mayank Vatsa, IIT Jodhpur
🔗 Register: lnkd.in/dqNHBBzG
#ACMIndia #GenAI #MachineUnlearning #AIethics

(3) WaterDrum embeds robust watermarks into text data & measures the #watermark strength after #MachineUnlearning: - It produces calibrated scores without referencing the retrained model; - The signal is orthogonal to model performance & applicable even with similar data. (4/n)

bryanklow's tweet image. (3) WaterDrum embeds robust watermarks into text data & measures the #watermark strength after #MachineUnlearning:
- It produces calibrated scores without referencing the retrained model;
- The signal is orthogonal to model performance & applicable even with similar data. (4/n)

(1) Traditional utility-centric #MachineUnlearning metrics rely on referencing a retrained model, which is prohibitively expensive😨. These metrics also struggle when the forget & retain sets contain similar data, which is a common scenario in realistic deployments😖. (2/n) #LLM

bryanklow's tweet image. (1) Traditional utility-centric #MachineUnlearning metrics rely on referencing a retrained model, which is prohibitively expensive😨. These metrics also struggle when the forget & retain sets contain similar data, which is a common scenario in realistic deployments😖. (2/n)
#LLM

When you are unauthorized for yourself 🤦‍♂️🤭 #MachineUnlearning #NaturalLanguageNotProcessing

samit_gh's tweet image. When you are unauthorized for yourself 🤦‍♂️🤭
#MachineUnlearning #NaturalLanguageNotProcessing

Recommendation from @Spotify, of album I've already heard on their service a couple of times. #MachineUnlearning

samgrover's tweet image. Recommendation from @Spotify, of album I've already heard on their service a couple of times. #MachineUnlearning

The #AISTATS2022 paper of @CYZ798775190 Shizhuo @bryanklow proposes an active task selection algorithm for #MetaLearning with a provable performance guarantee that is based on mutual information and online variational Bayesian #MachineUnlearning.


Postdoc, RA & Ph.D. positions in Collaborative ML/#FederatedLearning, Data Valuation, Incentive-Aware Mechanism Design, #MachineUnlearning @NUSComputing See groups.google.com/u/3/g/ml-news/… #NeurIPS2021 #ICML2021 #AAAI2021 #IJCAI2021 #UAI2021 #AISTATS2021


🤩 Glad to see our work "Towards Adversarial Evaluations of Inexact Machine Unlearning" arxiv.org/abs/2201.06640 inspire "Towards Unbounded Machine Unlearning" arxiv.org/abs/2302.09880 from #GoogleBrain @GoogleAI @Eleni30fillou & @uniofwarwick. #MachineUnlearning #ProfGiri🧵👇🏽

ponguru's tweet image. 🤩 Glad to see our work "Towards Adversarial Evaluations of Inexact Machine Unlearning" arxiv.org/abs/2201.06640 inspire "Towards Unbounded Machine Unlearning" arxiv.org/abs/2302.09880 from #GoogleBrain @GoogleAI @Eleni30fillou & @uniofwarwick. #MachineUnlearning #ProfGiri🧵👇🏽

(1) Traditional utility-centric #MachineUnlearning metrics rely on referencing a retrained model, which is prohibitively expensive😨. These metrics also struggle when the forget & retain sets contain similar data, which is a common scenario in realistic deployments😖. (2/n) #LLM

bryanklow's tweet image. (1) Traditional utility-centric #MachineUnlearning metrics rely on referencing a retrained model, which is prohibitively expensive😨. These metrics also struggle when the forget & retain sets contain similar data, which is a common scenario in realistic deployments😖. (2/n)
#LLM

(3) WaterDrum embeds robust watermarks into text data & measures the #watermark strength after #MachineUnlearning: - It produces calibrated scores without referencing the retrained model; - The signal is orthogonal to model performance & applicable even with similar data. (4/n)

bryanklow's tweet image. (3) WaterDrum embeds robust watermarks into text data & measures the #watermark strength after #MachineUnlearning:
- It produces calibrated scores without referencing the retrained model;
- The signal is orthogonal to model performance & applicable even with similar data. (4/n)

"Ever seen an AI with a messy memory? Time for some digital decluttering with machine unlearning! 🧹🔒 Let's keep our data safe while teaching AI to forget the fluff. #AIHoarding #DataPrivacy #MachineUnlearning #ArtificialIntelligence #openAI Read the full article…

thyshaaz's tweet image. "Ever seen an AI with a messy memory? Time for some digital decluttering with machine unlearning! 🧹🔒 Let's keep our data safe while teaching AI to forget the fluff. #AIHoarding #DataPrivacy #MachineUnlearning #ArtificialIntelligence #openAI 
Read the full article…

When the fully trained classifier says 'mustelid' 👌 #machineunlearning

chrissuthy's tweet image. When the fully trained classifier says 'mustelid' 👌
#machineunlearning

Q: What techniques can be used for machine unlearning? A: Techniques like adversarial training, generative models, and selective parameter updates can be employed for machine unlearning. @MichaelDell #MachineUnlearning

JordanJamesEtem's tweet image. Q: What techniques can be used for machine unlearning?
A: Techniques like adversarial training, generative models, and selective parameter updates can be employed for machine unlearning.
@MichaelDell #MachineUnlearning
JordanJamesEtem's tweet image. Q: What techniques can be used for machine unlearning?
A: Techniques like adversarial training, generative models, and selective parameter updates can be employed for machine unlearning.
@MichaelDell #MachineUnlearning
JordanJamesEtem's tweet image. Q: What techniques can be used for machine unlearning?
A: Techniques like adversarial training, generative models, and selective parameter updates can be employed for machine unlearning.
@MichaelDell #MachineUnlearning
JordanJamesEtem's tweet image. Q: What techniques can be used for machine unlearning?
A: Techniques like adversarial training, generative models, and selective parameter updates can be employed for machine unlearning.
@MichaelDell #MachineUnlearning

Q: What challenges are associated with machine unlearning in deep learning models? A: Challenges include catastrophic forgetting, preserving useful knowledge, and maintaining model performance during unlearning. #MachineUnlearning #Challenges @pmarca @bhorowitz @elonmusk

JordanJamesEtem's tweet image. Q: What challenges are associated with machine unlearning in deep learning models?
A: Challenges include catastrophic forgetting, preserving useful knowledge, and maintaining model performance during unlearning.
#MachineUnlearning #Challenges 
@pmarca @bhorowitz @elonmusk
JordanJamesEtem's tweet image. Q: What challenges are associated with machine unlearning in deep learning models?
A: Challenges include catastrophic forgetting, preserving useful knowledge, and maintaining model performance during unlearning.
#MachineUnlearning #Challenges 
@pmarca @bhorowitz @elonmusk
JordanJamesEtem's tweet image. Q: What challenges are associated with machine unlearning in deep learning models?
A: Challenges include catastrophic forgetting, preserving useful knowledge, and maintaining model performance during unlearning.
#MachineUnlearning #Challenges 
@pmarca @bhorowitz @elonmusk
JordanJamesEtem's tweet image. Q: What challenges are associated with machine unlearning in deep learning models?
A: Challenges include catastrophic forgetting, preserving useful knowledge, and maintaining model performance during unlearning.
#MachineUnlearning #Challenges 
@pmarca @bhorowitz @elonmusk

#MachineUnlearning—a remarkable advancement in AI—allows models to 'forget’ specific pieces of data, eliminating the need to restart the training process from scratch. As #AI continues to advance, #innovations like these will be vital to balancing efficiency & ethical data use.

EMERITUS_INST's tweet image. #MachineUnlearning—a remarkable advancement in AI—allows models to 'forget’ specific pieces of data, eliminating the need to restart the training process from scratch. As #AI continues to advance, #innovations like these will be vital to balancing efficiency & ethical data use.

महत्त्वपूर्ण शब्दावली: मशीन अनलर्निंग (Machine Unlearning) sanskritiias.com/hindi/importan… #MachineUnlearning #importantterminology #importantwords #prelims #importantconcepts #India #upsc #prelimssexam #pcs #sanskritiias

sanskritiias's tweet image. महत्त्वपूर्ण शब्दावली: 
  
मशीन अनलर्निंग (Machine Unlearning)

sanskritiias.com/hindi/importan…

#MachineUnlearning #importantterminology #importantwords #prelims #importantconcepts #India #upsc #prelimssexam #pcs #sanskritiias

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