#SparseModels - Twitter Hashtag

6 months ago

Geometry explains sparsity: L₂ circles → smooth, distributed solutions L₁ diamonds → corners → sparse solutions This is why Lasso works. Notes: https://t.co/ekPGWpxnSj #Optimization #SparseModels #MachineLearning

ickma2311's tweet photo. Geometry explains sparsity:
L₂ circles → smooth, distributed solutions
L₁ diamonds → corners → sparse solutions

This is why Lasso works.

Notes: https://t.co/ekPGWpxnSj

#Optimization #SparseModels #MachineLearning https://t.co/EASnYnj9GE

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Chao Ma

@ickma2311

6 months ago

The “1/2-norm” isn’t a true norm: its unit ball is non-convex. Triangle inequality fails — midpoints fall outside the set. Yet it’s a powerful sparsity penalty. Full notes: https://t.co/ekPGWpxnSj #Convexity #SparseModels #Math

ickma2311's tweet photo. The “1/2-norm” isn’t a true norm: its unit ball is non-convex.
Triangle inequality fails — midpoints fall outside the set.

Yet it’s a powerful sparsity penalty.

Full notes: https://t.co/ekPGWpxnSj

#Convexity #SparseModels #Math https://t.co/e9DJl3Qcoq

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A A @A_A_i_A_A

7 months ago

https://t.co/wklOkvBW8D #OpenAI #AI #NeuralNetworks #SparseModels #AIInterpretability #AIDebugging #MachineLearning #DeepLearning #Tech

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Vaibhav | e/acc @fenestbuc

7 months ago

5/5 What aspects of trillion-param MoE deployment interest you most? Memory offloading strategies? Dynamic routing budgets? Hierarchical expert organization? Drop your thoughts below 👇 #MoE #LLMs #SparseModels #AIResearch

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EUSIPCO @eusipco

10 months ago

🗓️ 8-12 September #EUSIPCO 📃 Tutorials on the 8th of September #audioprocessing #signalprocessing #machinelearning #imagecoding #videocoding #sparsemodels #soundzone #beamforming #covariance #neuralnetworks ➡️ Which one are you interested in? 🔗 https://t.co/hogRqPiBGD

eusipco's tweet photo. 🗓️ 8-12 September #EUSIPCO 📃 Tutorials on the 8th of September #audioprocessing #signalprocessing #machinelearning #imagecoding #videocoding #sparsemodels #soundzone #beamforming #covariance #neuralnetworks ➡️ Which one are you interested in? 🔗 https://t.co/hogRqPiBGD https://t.co/5bOGo4a88i

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Global Tech Council @GTechCouncil

about 1 year ago

Tech terms decoded! 🛠️ Attention techies, it’s time for #TermOfTheDay. Today, we are learning about: Sparse Models! ⚡ #TechTerms #SparseModels #AI #MachineLearning #DeepLearning #TechEducation

GTechCouncil's tweet photo. Tech terms decoded! 🛠️

Attention techies, it’s time for #TermOfTheDay.

Today, we are learning about: Sparse Models! ⚡

#TechTerms #SparseModels #AI #MachineLearning #DeepLearning #TechEducation https://t.co/uWw5VbBd1d

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Red Hat AI

@RedHat_AI

over 1 year ago

@vllm_project Download Sparse Llama: https://t.co/nDPzf1D1uj See benchmarks and our approach: https://t.co/XpKhHDqkR0 Thanks to @_EldarKurtic, Alexdre Marques, @markurtz_, @DAlistarh, Shubhra Pandit & the Neural Magic team for always enabling efficient AI! #SparseModels #OpenSourceAI #vLLM

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AICompeteNCE📍 @AiCompetence

over 1 year ago

When it comes to machine learning and AI models, there’s a familiar challenge: scaling. #AIbottlenecks #AImodeloptimization #AIscaling #efficientAItraining #GRINMoE #scalingchallenges #sparsemodels #SparseMixerv2 https://t.co/dugtJJkPzE

AiCompetence's tweet photo. When it comes to machine learning and AI models, there’s a familiar challenge: scaling. #AIbottlenecks #AImodeloptimization #AIscaling #efficientAItraining #GRINMoE #scalingchallenges #sparsemodels #SparseMixerv2
https://t.co/dugtJJkPzE https://t.co/xQhgaececY

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AITopTools

@aitoptools

almost 3 years ago

#AI & #MachineLearning need to converge well. Check out this new theory that could make this possible! 🤔 #SparseModels https://t.co/VRZnG7PQfb

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FinSentim @FinSentim

over 4 years ago

Jonathan Schwarz et al. introduce #Powerpropagation, a new weight-parameterisation for #neuralnetworks that leads to inherently #sparsemodels. Exploiting the behavior of gradient descent, their method gives rise to weight updates exhibiting a "rich get richer" dynamic.

AK

@_akhaliq

over 4 years ago

Powerpropagation: A sparsity inducing weight reparameterisation pdf: https://t.co/fJtBgtSd8H abs: https://t.co/Ej2xH06vci a new weight-parameterisation for neural networks that leads to inherently sparse models

_akhaliq's tweet photo. Powerpropagation: A sparsity inducing weight reparameterisation
pdf: https://t.co/fJtBgtSd8H
abs: https://t.co/Ej2xH06vci

a new weight-parameterisation for neural networks that leads to inherently sparse models https://t.co/njKJXJh2J6

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FinSentim @FinSentim

almost 5 years ago

@sarahookr, @KaliTessera, and Benjamin Rosman take a broader view of training #sparsnetworks and consider the role of regularization, optimization, and architecture choices on #sparsemodels. They propose a simple experimental framework, #SameCapacitySparse vs #DenseComparison.

Sara Hooker

@sarahookr

almost 5 years ago

Tomorrow at @ml_collective DLTC reading group, @KaliTessera will be presenting our work on how initialization is only one piece of the puzzle for training sparse networks. Can taking a wider view of model design choices unlock sparse training? https://t.co/j6WHSDKN4j

sarahookr's tweet photo. Tomorrow at @ml_collective DLTC reading group, @KaliTessera will be presenting our work on how initialization is only one piece of the puzzle for training sparse networks.

Can taking a wider view of model design choices unlock sparse training?

https://t.co/j6WHSDKN4j https://t.co/fUnJHQd6kS

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