Panel on Understanding Sparsity with Yani Ioannou, @gkdziugait, Martha White and Dan Alistarh moderated by Elena Mocanu and Aleksandra Nowak.

Another poster novelty from sparsenn workshop: "tear-off papers"! Printed, stapled, and ready to grab.

Our first spotlight happening now! PopSparse: Accelerated block sparse matrix multiplication on IPU Presented by Zhiyi Li Graphcore

Today, I'm virtually at #ICLR2023 at SNN workshop sparsenn to "play the lottery with concave regularizers" 🌈 #sparsity #pruning #LotteryTicketHypothesis

I'm presenting a poster in the Sparse Neural Network workshop sparsenn at #ICLR2023 on "Efficient Real Time Recurrent Learning through combined activity and parameter sparsity". Come by if you're around! Link to paper: arxiv.org/abs/2303.05641

Our second spotlight presented by Shiwei Liu Ten Lessons We Have Learned in the New ''Sparseland'': A Short Handbook for Sparse Neural Network Researchers

The second session has just started with the talk by Aakanksha Chowdhery, “Efficiently Scaling Transformer Inference”. #ICLR2023

I'll be presenting our paper at the #ICLR2023 Sparsity workshop sparsenn with my co-authors Abhay Gupta and Shreyas Saxena! Great to see so many experts in the #sparsity field come together to share insights and knowledge. Come by if you're around. arxiv.org/abs/2303.10464

We will have the second round of the spotlight presentations now! Starting with “Massive Language Models Can be Accurately Pruned in One-Shot” presented by Elias Franter. #ICLR2023

The next spotlight presentation is “Efficient Backpropagation for Sparse Training with Speedup” presented by Mahdi Nikdan #ICLR2023

Our final spotlight “Automatic Noise Filtering with Dynamic Sparse Training in Deep Reinforcement Learning” is presented by Bram Grooten #ICLR2023

before and after #iclr2023

Excited to start the next part of the workshop! We have now the breakout sessions where the attendees discuss and brainstorm various topics in sparsity with each other! #ICLR2023

Martha White Brought up a great point during the panel discussion at the sparsenn workshop, “rather than taking existing architectures, which we’ve been working with for many years are kind of designed for dense architectures, and then saying...that’s our gold standard...(1/2)

We have the next round of talks! The first talk was given by Ce Zhang #ICLR2023

The next talk has just started: “Structured Sparsity Research” by Pavlo Molchanov

Come see us at the virtual poster session of the sparsenn workshop at #iclr2023, starting 11 AM ET Our work is on the effect of sparsification in the number of linear regions of neural networks, and how understanding this effect may help pruning with better accuracy (Poster 30)

Check out a new pruning library, JaxPruner! Excited to see how it will impact those already working in network pruning and quantization, and attract new people interested in trying out / applying these methods in new domains 🚀

Jeff Dean discussed the importance of sparse computation, adaptive computation and dynamically-changing neural networks sparsenn. He thinks "dense models are going to give way to these efficient sparse models"...I agree 💯

🙏 for joining us at 7am PT!