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The Call for Papers for
#AISTATS2020 is out at https://www.aistats.org The submission deadline is 8 October 2019. The conference will be held in Palermo, Italy, from 3 to 5 June 2020. -
Delighted to have a paper accepted for
#AISTATS2020. I guess that's the Summer holiday destination decided then
pic.twitter.com/lZmhjBPMrx
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Don't forget to submit to
#AISTATS2020, which will take place in Palermo, Italy June 3 - 5, 2020. Submit: https://cmt3.research.microsoft.com/AISTATS2020/ **DEADLINE**: Tuesday, October 8, 2019 @ 23:59 PDT CFP: https://www.aistats.org/cfp.html -
Exciting work
@PROWLER_IO with@stefanos_ele,@NicolasDurrande,@aptemav and@jameshensman on scaling inference in GP models by merging the sparse variational and the SDE approaches. Trick: state inducing features
O((M+N)d^3) scaling!
#aistats2020 https://arxiv.org/abs/2001.05363 pic.twitter.com/aG9YQtkmLH
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I am going to be Family Chair for
#AISTATS2020 (in Palermo, Italy, early June)! Please help me/us do a good job: if you are planning to attend and would consider taking your kids, (or if you simply think you have valuable advice) please reach out to me in direct messages. Thanks pic.twitter.com/jKITCnwD6Y -
#AISTATS2020 here we go! Filling gaps between UCB and Thompson Sampling with Randomized UCB: http://arxiv.org/abs/1910.04928 Featuring@sharan_vaswani, Abbas Mehrabian, and Branislav Kveton -
Good luck to everyone submitting to
#AISTATS2020! -
Eager to welcome you for AISTATS 2020 in
#Palermo , June 3-5.#AISTATS2020 pic.twitter.com/HTM8DeGuFi
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If your paper has used up all of the Greek letters and you start reusing some of those letters, you're doing something wrong. Or at least you're doing wrong by your reviewers!
#AISTATS2020 pic.twitter.com/WtVxk9BGzQ -
There's an important difference between decisions and predictions, especially when it comes to fairness. Check out our
#aistats2020 paper "Fair Decisions Despite Imperfect Predictions" with@autreche@krikamol@bschoelkopf Isabel Valera http://arxiv.org/abs/1902.02979 -
Check out our paper at
#AISTATS2020 "Distributionally Robust Bayesian Quadrature Optimization". Great work@thanhnguyentang and supervision team@santura Ci vediamo a Palermo!#AI#MachineLearning#ML#ProbabilityTheory#Optimization#DistributionalLearningpic.twitter.com/Jzx8oLondj
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Probably not feasible for
#AISTATS2020, but hopefully remote paper and poster presentations will be allowed from next edition! https://twitter.com/bschoelkopf/status/1225069303260766209 … -
Are generative models sensitive to adversarial attacks? The answer is yes (at least for flow-based models)! For details check out our
#aistats2020 paper: https://arxiv.org/pdf/1911.08654.pdf … This is a joint work with@umdcs students Phillip Pope and Yogesh Balaji.pic.twitter.com/XABOobFxBi
Prikaži ovu nit -
Reach out to our sponsorship chair
@konstantina_pll if you are interested in sponsoring AISTATS 2020.#aistats2020 https://twitter.com/Aistats2020/status/1220624255571963905 … -
Congrats to Quentin Bertrand and
@mathusmassias for their recent#AISTATS2020 paper. Lucky to supervise such great students with@agramfort. A presto a Palermo! -
I am very proud of this initiative, and I hope we will be able inspire other ML conferences to follow the same path!
#aistats2020#ICLR2020#NeurIPS2019#icml2020https://twitter.com/Aistats2020/status/1217849788642754560 … -
#AISTATS2020 RCD: Repetitive causal discovery of linear non-Gaussian acyclic models with latent confounders. (arXiv:2001.04197v1 [cs\.LG]) http://arxiv.org/abs/2001.04197 -
#AISTATS2020 POPCORN: Partially Observed Prediction COnstrained ReiNforcement Learning. (arXiv:2001.04032v1 [stat\.ML]) http://arxiv.org/abs/2001.04032 -
Check out our new paper at
#AISTATS2020: "Amortized Inference of Variational Bounds for Learning Noisy-OR" by Yiming Yan, Melissa Ailem, and@feishaAI https://arxiv.org/abs/1906.02428 -
"Black-box inference for non-linear latent force models" has been accepted to
#aistats2020 https://arxiv.org/abs/1906.09199 We propose an algorithm based on inverse autoregressive flows for posterior inference in non-linear latent force models. With@wilocw@dennisprangle and Tom Ryder.
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family-friendly ML conferences! 
