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Efficiently learning Fourier sparse set functions: spotlight at
#NeurIPS2019 (4:10pm W Ballroom C; poster 44) https://papers.nips.cc/paper/9648-efficiently-learning-fourier-sparse-set-functions … with Andisheh Amrollahi, Amir Zandieh and@michaelkapralovHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Stochastic bandits allowing uncertainty about the observed context:
#NeurIPS2019 poster 44 https://papers.nips.cc/paper/9558-stochastic-bandits-with-context-distributions … with Johannes KirschnerHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
A domain agnostic measure for monitoring and evaluating GANs:
#NeurIPS2019 poster 135 https://papers.nips.cc/paper/9377-a-domain-agnostic-measure-for-monitoring-and-evaluating-gans … with Paulina Grnarova, Kfir Levy, Aurelien Lucchi, Nathanael Perraudin,@goodfellow_ian and Thomas HofmannHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Fast learning in games via opportunistic hallucination:
#NeurIPS2019 poster 6 https://papers.nips.cc/paper/9514-no-regret-learning-in-unknown-games-with-correlated-payoffs.pdf … with Pier Giuseppe Sessa,@ilijabogunovic and Maryam KamgarpourHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Andreas Krause proslijedio/la je Tweet
Adaptive decision making through submodularity at
#NeurIPS2019 (East Exhibition Hall B + C, #164). Marko Mitrovic,@EhsanKazzemi , Moran Feldman,@arkrausepic.twitter.com/SrSVlgLPQk
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Sequential decision making with submodularity at
#NeurIPS2019, and applications to machine teaching (posters 142 and 164), with@aminkarbasi@adishs@yisongyue@yuxinch@autreche et alHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
New results on safe exploration for Bayesian optimization, active learning etc.
#NeurIPS2019 Poster 197 http://papers.nips.cc/paper/8555-safe-exploration-for-interactive-machine-learning.pdf …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Andreas Krause proslijedio/la je Tweet
Alhussein Fawzi,
@DeepMindAI researcher, will talk about recent advances in#ArtificialIntelligence at Carving Through Data, a@SDSCdatascience introductory course to#MachineLearning, combining#DataScience &#ski March 9-13, 2020 https://bit.ly/2H1pVpJ@EPFL_en@ETH_enpic.twitter.com/jldCKuusNb
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We have open postdoctoral fellowship positions in the Foundations of Data Science program at
@ETH_en. https://math.ethz.ch/sfs/eth-foundations-of-data-science/postdoctoral-positions.html …@CSatETHHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Andreas Krause proslijedio/la je Tweet
There are open tenure-track faculty positions in ML/AI in the CS department at ETH:https://ethz.ch/en/the-eth-zurich/working-teaching-and-research/faculty-affairs/ausgeschriebene-professuren/ingenieurwissenschaften/APTT_ComputerScience_DataScience.html …
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Andreas Krause proslijedio/la je Tweet
This work was led by Adish Singla's group at MPI-SWS, with Anette Hunziker as first author: https://machineteaching.mpi-sws.org/adishsingla.html … Also joint work with
@yuxinch,@arkrause,@oisinmacaodha, Pietro Perona, and Manuel Gomez-Rodriguez. (5/5)Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
ETH Zurich has an open faculty position in Machine Learning. Please spread the word!https://ethz.ch/en/the-eth-zurich/working-teaching-and-research/faculty-affairs/ausgeschriebene-professuren/ingenieurwissenschaften/APTT_ComputerScience_DataScience.html …
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Andreas Krause proslijedio/la je Tweet
We are happy to announce the 2nd edition of Carving Through Data, a
@SDSCdatascience introductory course to#MachineLearning, combining#DataScience &#ski, will take place in March 2020 in#Fischeralp!@EPFL_en@ETH_en@CSatETH@valaiswallis https://carvingthroughdata.ch/ pic.twitter.com/VGFLwJrYMM
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Scaling safe Bayesian optimization to high dimensions via one-dimensional subspaces. Both local and global convergence guarantees. Experiments on the SwissFEL free electron laser.
#ICML2019 (Poster 147, http://proceedings.mlr.press/v97/kirschner19a/kirschner19a.pdf …) Great collaboration with@psich_en@CSatETHHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Adapting structured importance sampling distributions for stochastic optimization online using ideas from bandits, with applications to clustering and RL
#ICML2019 (Poster 157, http://proceedings.mlr.press/v97/borsos19a/borsos19a.pdf …)@zalanborsosHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Training generative models where data and samples can be in different spaces. Why and how?
#ICML2019 (Poster 173, http://proceedings.mlr.press/v97/bunne19a/bunne19a.pdf …)@_bunnechHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Fitting stochastic differential equations to data? See our
#ICML2019 paper today (Talk 11:40 Room 101, Poster 216, http://proceedings.mlr.press/v97/abbati19a/abbati19a.pdf …)@maosbot@bschoelkopfHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
We use continuous submodular optimization to address non-convex problems in variational inference in our
#ICML2019 paper (Poster 98, http://proceedings.mlr.press/v97/bian19a/bian19a.pdf …)@CSatETHHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Andreas Krause proslijedio/la je Tweet
# AReS and MaRS – Adversarial and MMD-Minimizing Regression for SDEs Using GPs, we efficiently estimate drift and diffusion parameters without discretisation.
#ICML2019
Wed 11:40 @ Room 101
Wed 18:30 @ Pacific Ballroom #216
https://arxiv.org/abs/1902.08480
1st
Gab Abbatipic.twitter.com/VRcHzbU49X
Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Andreas Krause proslijedio/la je Tweet
Our
#ICML2019 paper ‘Learning Generative Models across Incomparable Spaces' is finally on arXiv. By learning distributions relationally rather than absolutely, we disentangle data and generator space! Joint work with@elmelis,@arkrause & Stefanie Jegelka. https://arxiv.org/abs/1905.05461Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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