Interested in shaping the future of #AI? Apply for the open #PhDposition in my group at @UniHannover. Join us in developing more efficient and interpretable reinforcement learning algorithms with applications in #gameAI. RTs appreciated🙂 Read more here: https://t.co/AwwOCejDGh
📢#AutoML23 will happen September 12-15 at the @HPI_DE in Potsdam, close to Berlin, Germany. The planned submission deadline is Thursday, March 23rd, 2023 (AOE). Please mark your calendar.
Save the date!
Our joint Dresden & @WiMLDS_Paris online meetup will be happening soon on March 17 at 🕡 with two amazing talks.
Don't forget to register at the link below!
#machinelearning#meetups
https://t.co/1aIQwzNMUw
Favorite #NeurIPS2020 presentations and posters this year
PS: heavily biased by what I happened to catch and whom I happened to talk to
PPS: still catching up on talks so the list is rather incomplete and I'd hope to grow
PPPS: with contributions from @ml_collective members
Fruitful social gathering at @WiMLworkshop about Non-traditional backgrounds opportunties! thanks to Francisca Cattan and Laia Tarres for the organization , and @OriolVinyalsML for the mentoring ! #NeuRIPS2020
If you follow me on Twitter, you probably know that I am pretty allergic to hype, especially around deep learning. So believe me when I say - this is a big f---ing deal.
https://t.co/GV7CDPQMlN
★ D!Light Update ★ We have one more great speaker to announce: Mengyuan Liu from @SAPConcur 🎉
Be part of our D!Light on #MachineLearining on Nov 26, from 6 pm👉https://t.co/uAmGvj1Bmr
See you on Thursday✌️@MLDD@Wimlds_Dresden
★ Take two of D!Light ★ After the kick-off in July, our #digital event series D!Light goes into the next round on November 26th (6 pm CET). This time, we have two great speakers on #MachineLearning from @Twitter & @AppsFlyer!
Join for free 👉https://t.co/uAmGvj1Bmr
Struck by "lack of capability" vs "a dearth of opportunity" here. Let me generalize to not just women and not just on leadership -- if you are in AI research and feel like you are held back by lack of opportunity, @ml_collective is here to help level the playing field.
Why have a "standard route" at all? It seems that the greatest poxes facing the ML community are intellectual homogeneity & group-think. Having everyone take too-similar paths to PhD appears (to me) the very pathology implicated. Granted, as a strange-path freak, I'm biased.
Something that always bothers me about working more on the MLOps/production/product-end of ML, is that my maths brain-muscles don't get enough regular practice.
What are your strategies for keeping the ML-relevant basics fresh? How much time do you dedicate to this?
#ICLR2020
I saw a guy debugging his model today.
No idpb.
No unittest.
No visualization.
No disabling regularization.
He just sat there staring at every line of code and cursing TensorFlow.
Like every machine learning researcher I know.