Isn't this just more complex and heavier on compute version of just adding noise to search? https://raw.githubusercontent.com/mlresearch/v235/main/assets/greshler24a/greshler24a.pdf
November 12, 2025 at 5:06 AM
Isn't this just more complex and heavier on compute version of just adding noise to search? https://raw.githubusercontent.com/mlresearch/v235/main/assets/greshler24a/greshler24a.pdf
While primarily a theoretical tool, discussions suggest central flow insights could lead to practical applications. This includes potentially speeding up convergence and improving future optimization methods. #MLResearch 4/6
October 9, 2025 at 4:00 AM
While primarily a theoretical tool, discussions suggest central flow insights could lead to practical applications. This includes potentially speeding up convergence and improving future optimization methods. #MLResearch 4/6
September 16, 2025 at 5:14 PM
Feature normalization in Ijepa helps stabilize training and improve performance in self-supervised learning. This project explores its impact on real-world vision tasks. Discover the insights: https://github.com/theAdamColton/elucidating-featurenorm-ijepa #MLResearch #OpenSource
August 16, 2025 at 3:27 AM
Feature normalization in Ijepa helps stabilize training and improve performance in self-supervised learning. This project explores its impact on real-world vision tasks. Discover the insights: https://github.com/theAdamColton/elucidating-featurenorm-ijepa #MLResearch #OpenSource
Excited to share that our paper that was accepted to #CHIL2025 "KEEP: Integrating Medical Ontologies with Clinical Data for
Robust Code Embeddings" is now available at PMLR: raw.githubusercontent.com/mlresearch/v...
Robust Code Embeddings" is now available at PMLR: raw.githubusercontent.com/mlresearch/v...
August 4, 2025 at 1:32 PM
Excited to share that our paper that was accepted to #CHIL2025 "KEEP: Integrating Medical Ontologies with Clinical Data for
Robust Code Embeddings" is now available at PMLR: raw.githubusercontent.com/mlresearch/v...
Robust Code Embeddings" is now available at PMLR: raw.githubusercontent.com/mlresearch/v...
Excited to welcome Aditya Grover, UCLA, as a keynote speaker at #IJCAI2025 in #Montreal. He is the winner of the IJCAI-25 Computers and Thought Award: aditya-grover.github.io
#AI #GenerativeAI #MLResearch
#AI #GenerativeAI #MLResearch
August 2, 2025 at 3:21 PM
Excited to welcome Aditya Grover, UCLA, as a keynote speaker at #IJCAI2025 in #Montreal. He is the winner of the IJCAI-25 Computers and Thought Award: aditya-grover.github.io
#AI #GenerativeAI #MLResearch
#AI #GenerativeAI #MLResearch
How do researchers turn papers into real-world impact?
At the WiML Symposium @ ICML 2025, join Microsoft’s Ida Momennejad and Yuhang He for a roundtable on academic-industry collaboration.
🗓 July 16 | 1–2 PM PT | Vancouver
#WiML #ICML2025 #MLResearch
At the WiML Symposium @ ICML 2025, join Microsoft’s Ida Momennejad and Yuhang He for a roundtable on academic-industry collaboration.
🗓 July 16 | 1–2 PM PT | Vancouver
#WiML #ICML2025 #MLResearch
July 14, 2025 at 3:05 PM
How do researchers turn papers into real-world impact?
At the WiML Symposium @ ICML 2025, join Microsoft’s Ida Momennejad and Yuhang He for a roundtable on academic-industry collaboration.
🗓 July 16 | 1–2 PM PT | Vancouver
#WiML #ICML2025 #MLResearch
At the WiML Symposium @ ICML 2025, join Microsoft’s Ida Momennejad and Yuhang He for a roundtable on academic-industry collaboration.
🗓 July 16 | 1–2 PM PT | Vancouver
#WiML #ICML2025 #MLResearch
In this episode, we talk about:
🔹 Decentralized & collaborative AI
🔹 Scaling laws & fine-tuning tricks
🔹 Data attribution for LLMs
🔹 Multilingual learning
🔹 UK 🇬🇧 vs. Canada 🇨🇦 research ecosystems
/3
#MLResearch #LLM #DecentralizedAI
🔹 Decentralized & collaborative AI
🔹 Scaling laws & fine-tuning tricks
🔹 Data attribution for LLMs
🔹 Multilingual learning
🔹 UK 🇬🇧 vs. Canada 🇨🇦 research ecosystems
/3
#MLResearch #LLM #DecentralizedAI
June 20, 2025 at 3:49 PM
In this episode, we talk about:
🔹 Decentralized & collaborative AI
🔹 Scaling laws & fine-tuning tricks
🔹 Data attribution for LLMs
🔹 Multilingual learning
🔹 UK 🇬🇧 vs. Canada 🇨🇦 research ecosystems
/3
#MLResearch #LLM #DecentralizedAI
🔹 Decentralized & collaborative AI
🔹 Scaling laws & fine-tuning tricks
🔹 Data attribution for LLMs
🔹 Multilingual learning
🔹 UK 🇬🇧 vs. Canada 🇨🇦 research ecosystems
/3
#MLResearch #LLM #DecentralizedAI
[9/9]
Appreciate any advice, pointers to relevant papers, or even “don’t do this” cautionary tales.
Thanks in advance!
#transformers #sparsity #maskedmodeling #deeplearning #symbolicAI #mlresearch #attentionmodels #structureddata
Appreciate any advice, pointers to relevant papers, or even “don’t do this” cautionary tales.
Thanks in advance!
#transformers #sparsity #maskedmodeling #deeplearning #symbolicAI #mlresearch #attentionmodels #structureddata
June 14, 2025 at 5:22 AM
[9/9]
Appreciate any advice, pointers to relevant papers, or even “don’t do this” cautionary tales.
Thanks in advance!
#transformers #sparsity #maskedmodeling #deeplearning #symbolicAI #mlresearch #attentionmodels #structureddata
Appreciate any advice, pointers to relevant papers, or even “don’t do this” cautionary tales.
Thanks in advance!
#transformers #sparsity #maskedmodeling #deeplearning #symbolicAI #mlresearch #attentionmodels #structureddata
Interesting paper on fairness in remote proctoring decisions for the Duolingo English Test. It also reveals a bit about the logistics of remote proctoring, including proctors based in the US, Philippines, and India.
raw.githubusercontent.com/mlresearch/v...
raw.githubusercontent.com/mlresearch/v...
raw.githubusercontent.com
May 23, 2025 at 1:58 AM
Interesting paper on fairness in remote proctoring decisions for the Duolingo English Test. It also reveals a bit about the logistics of remote proctoring, including proctors based in the US, Philippines, and India.
raw.githubusercontent.com/mlresearch/v...
raw.githubusercontent.com/mlresearch/v...
🎉Hats off to Dr. Stefan Blücher! He defended his PhD yesterday🎓
Thesis: "Towards Scalable and Transparent ML Algorithms with Applications in Explainable AI and Quantum Chemistry"
Thanks to all supporters!
#XAI #QuantumML #MLResearch #PhDCompleted @tuberlin.bsky.social @fraunhoferhhi.bsky.social
Thesis: "Towards Scalable and Transparent ML Algorithms with Applications in Explainable AI and Quantum Chemistry"
Thanks to all supporters!
#XAI #QuantumML #MLResearch #PhDCompleted @tuberlin.bsky.social @fraunhoferhhi.bsky.social
May 13, 2025 at 3:41 PM
🎉Hats off to Dr. Stefan Blücher! He defended his PhD yesterday🎓
Thesis: "Towards Scalable and Transparent ML Algorithms with Applications in Explainable AI and Quantum Chemistry"
Thanks to all supporters!
#XAI #QuantumML #MLResearch #PhDCompleted @tuberlin.bsky.social @fraunhoferhhi.bsky.social
Thesis: "Towards Scalable and Transparent ML Algorithms with Applications in Explainable AI and Quantum Chemistry"
Thanks to all supporters!
#XAI #QuantumML #MLResearch #PhDCompleted @tuberlin.bsky.social @fraunhoferhhi.bsky.social
NoProp: Training Neural Nets Without Backprop or Forwardprop
A new paper proposes "NoProp"—a radical approach to training neural networks without traditional back/forward propagation.
arxiv.org/abs/2503.24322
#AI #NeuralNetworks #MLResearch
A new paper proposes "NoProp"—a radical approach to training neural networks without traditional back/forward propagation.
arxiv.org/abs/2503.24322
#AI #NeuralNetworks #MLResearch
NoProp: Training Neural Networks without Back-propagation or Forward-propagation
The canonical deep learning approach for learning requires computing a gradient term at each layer by back-propagating the error signal from the output towards each learnable parameter. Given the…
arxiv.org
April 17, 2025 at 7:06 PM
NoProp: Training Neural Nets Without Backprop or Forwardprop
A new paper proposes "NoProp"—a radical approach to training neural networks without traditional back/forward propagation.
arxiv.org/abs/2503.24322
#AI #NeuralNetworks #MLResearch
A new paper proposes "NoProp"—a radical approach to training neural networks without traditional back/forward propagation.
arxiv.org/abs/2503.24322
#AI #NeuralNetworks #MLResearch
I have been asked to respond to the prompt below:
1. What, as you see it, are the most important potential benefits of #generativeAI technology? (List at least 2)
My response:
- Giving my partner a job in AI/MLresearch and development.
- Something to be destroyed in the #butlerianJihad
1. What, as you see it, are the most important potential benefits of #generativeAI technology? (List at least 2)
My response:
- Giving my partner a job in AI/MLresearch and development.
- Something to be destroyed in the #butlerianJihad
March 11, 2025 at 7:51 PM
I have been asked to respond to the prompt below:
1. What, as you see it, are the most important potential benefits of #generativeAI technology? (List at least 2)
My response:
- Giving my partner a job in AI/MLresearch and development.
- Something to be destroyed in the #butlerianJihad
1. What, as you see it, are the most important potential benefits of #generativeAI technology? (List at least 2)
My response:
- Giving my partner a job in AI/MLresearch and development.
- Something to be destroyed in the #butlerianJihad
Language Models are Few-Shot Learners, page 33 mentions bidirectional models as a promising direction. Any recent movement in that direction? #ai #mlresearch
February 10, 2025 at 7:49 PM
Language Models are Few-Shot Learners, page 33 mentions bidirectional models as a promising direction. Any recent movement in that direction? #ai #mlresearch
if it doesn't have pretty pictures I don't want it.
#mlresearch #academicsky #machinelearning #research
#mlresearch #academicsky #machinelearning #research
February 9, 2025 at 6:02 PM
if it doesn't have pretty pictures I don't want it.
#mlresearch #academicsky #machinelearning #research
#mlresearch #academicsky #machinelearning #research
February 8, 2025 at 3:35 PM
I’m looking forward to engaging discussions, insightful questions, and connecting with fellow researchers. If you’re attending NeurIPS, stop by my sessions—I’d love to chat! 🚀
#NeurIPS2024 #MachineLearning #ComputerVision #ProbabilisticModels #ErrorRecognition #AIResearch #MLResearch
#NeurIPS2024 #MachineLearning #ComputerVision #ProbabilisticModels #ErrorRecognition #AIResearch #MLResearch
December 8, 2024 at 10:57 PM
I’m looking forward to engaging discussions, insightful questions, and connecting with fellow researchers. If you’re attending NeurIPS, stop by my sessions—I’d love to chat! 🚀
#NeurIPS2024 #MachineLearning #ComputerVision #ProbabilisticModels #ErrorRecognition #AIResearch #MLResearch
#NeurIPS2024 #MachineLearning #ComputerVision #ProbabilisticModels #ErrorRecognition #AIResearch #MLResearch
This is #MLresearch. (Not even being sarcastic too.)
November 20, 2024 at 7:24 PM
This is #MLresearch. (Not even being sarcastic too.)