Top Tweets for #efficientML
🚀 The full programme for EMDL 2026 is now live.
EMDL 2026 runs on 25 June in Cambridge, co-located with ACM MobiSys 2026, a full day on the systems foundations of generative AI at the edge.
🌐 Site: https://t.co/wCa4yfS2GJ
#EMDL2026 #MobiSys2026 #EdgeAI #EfficientML
We're also hiring researchers in Efficient ML at Apple MLR.
https://t.co/9K5Q6gRTgc
#Apple #EfficientML #GenAI #MultimodalAI
🚀 We're launching the Efficient Qwen Competition @ AdaptFM #ICML2026!
How fast can you make Qwen3.5-4B run on a single A10G without breaking it?
$6,000 in prizes. Open to all. Submissions open May 4.
👉 https://t.co/kcIq04zzOo
#LLM #EfficientML #ModelOptimization
🎉 Happy to share that Xiao Ma, a PhD student I co-supervise with Dong Ma, has had his paper accepted at #ICLR2026!
"Architecture-Agnostic Test-Time Adaptation via Backprop-Free Embedding Alignment." Xiao Ma, Young D. Kwon, Pan Zhou, and Dong Ma
#TTA #EdgeAI #EfficientML #iclr
Thinking of making a small Discord for lightweight ML.
Mainly for my own projects(Check profile to know about it), others can share too (shoutout if solid). Not a teaching server.
If this is your thing, drop a hi.
RTs help, low reach 🙏
#MachineLearning #EdgeAI #EfficientML
The Training Data Paradox: When More Data Doesn't Mean Better Results
#DataQualityOverQuantity #MLParadox #SmartData #AIEfficiency #DataScience #ModelOptimization #DataCuration #MLChallenges #AIBestPractices #EfficientML
https://t.co/dLU7SwZVKV
📚 Next #EfficientML Reading Group!
🗓 Oct 28 @ 5pm CEST
🎤 Mathador-LM: A Dynamic Benchmark for Mathematical Reasoning on LLMs with @_EldarKurtic (NeuralMagic & ISTA)
🔗 https://t.co/nU7UnJHcx8
Will be giving a talk at @iiscbangalore later today, with hopes of setting up collaborations related to my ongoing research.
#EfficientML #Sustainable #ArtificialIntelligence
Having trouble running large text-to-image models (e.g., SDXL) on a desktop GPU due to memory constraints? We introduce MixDQ, a quantization method that achieves 2-3x memory and 1.45x e2e latency optimization without performance loss. (1/3)
#arxiv #efficientML #stablediffusion
Check out ‘Dataset Decomposition’, a new paper from the Machine Learning Research team @Apple that improves the training speed of LLMs by up to 3x:
https://t.co/tAuww5ZK7C
Hadi Pouransari et al.
#EfficientML #AI #ML #Apple
🚨Announcing the next Harvard #efficientml seminar on Learning to learn, featuring @janexwang and
Rising Star @juliancodaforno ! 🧠
➡️ April 22, 2:30 ET
📅Registration: https://t.co/nUPYMarhFV
🔗 Website: https://t.co/cL1iRnpkdb
@harvard_data @HarvardDBMI @KempnerInst
@sarahookr asks the question: is bigger really better when it comes to #AI models? Check out @harvardmagazine's feature on #KempnerInstitute's new #efficientml seminar series, in partnership with @harvardmed and @harvard_data, organized by @schwarzjn_
A driving force of competition between top AI companies is dataset expansion. But is bigger really better? @cohere's @sarahookr argues scaling could be inefficient. @schwarzjn_ of @HarvardDBMI believes smaller models can adapt. From @nhpasquini:
#harvard
https://t.co/mkruhdLOZL
Join the #KempnerInstitute for the next Harvard #efficientML seminar on Machine Unlearning with @NicolasPapernot and Anvith Thudi. March 25 @ 2:30pm. Free, virtual, open to the public.
🚨Announcing the next Harvard #efficientml eminar on Machine Unlearning, featuring @NicolasPapernot and Rising Star Anvith Thudi! 🧠
➡️ March 25 @ 2:30pm ET
📅 Registration: https://t.co/LZ3EoWwekP
🔗 Website: https://t.co/1yQupyqU3M
@harvard_data @HarvardDBMI @KempnerInst
🚨Announcing the next Harvard #efficientml eminar on Machine Unlearning, featuring @NicolasPapernot and Rising Star Anvith Thudi! 🧠
➡️ March 25 @ 2:30pm ET
📅 Registration: https://t.co/LZ3EoWwekP
🔗 Website: https://t.co/1yQupyqU3M
@harvard_data @HarvardDBMI @KempnerInst
We'll be publishing a lot more smashed models to Hugging Face, from GenAI and LLMs to computer vision and much more.
Tell us which ones you want below and we'll add them to the list !
#AI #EfficientML #HuggingFace #Smash
The summer #intern programme of @brave for 2024 is out! We are #hiring research sci/eng interns in our team. If pursuing a PhD and interested in #EfficientML, #DistributedML, #LLMs & on-device #measurements, reach out. Applications: https://t.co/36baAnOBLy
The review covers:
1️⃣ #NeuralNetworks basics
2️⃣ MEMS-based applications on MCUs
3️⃣ Efficient NNs
4️⃣ Deployment strategies
5️⃣ Limitations of TinyML
🚀 Unlock the full potential of TinyML applications on resource-constrained devices!
#TinyML #AI #Microcontrollers #EfficientML 🚀
🎓PhD students & researchers, 🚀join our public EfficientML Reading Group! 📚 A wide range of topics on ML (resource-)efficiency and beyond. Learn & discuss recent papers with peers!
📖 Check out the schedule: https://t.co/7e40lLkEt3
#EfficientML #MachineLearning #ReadingGroup
Thrilled to have two papers presented at @icmlconf! Dive in and explore our research on memory-efficient training of neural networks! #ICML2023 #EfficientML
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