Great work by Yanan Sui on Safe Bayesian Optimization applied to real human clinical experiments!https://t.co/DVL4QxKbjM
— Yisong Yue (@yisongyue) June 9, 2018
Appearing at @icmlconf #icml2018 pic.twitter.com/MAZhvFZRQc
Great work by Yanan Sui on Safe Bayesian Optimization applied to real human clinical experiments!https://t.co/DVL4QxKbjM
— Yisong Yue (@yisongyue) June 9, 2018
Appearing at @icmlconf #icml2018 pic.twitter.com/MAZhvFZRQc
Interesting talk at @NetflixResearch workshop on the use of Deep and Shallow latent models and the relation between MF, LDA, or Autoencoders. #WWW_2018 [PAPER] here: https://t.co/XT37RPAMLc pic.twitter.com/zQEpFLkt92
— Xavier 🎗🤖🏃 (@xamat) June 8, 2018
Few-shot learning problems can be ambiguous. Now MAML can handle the ambiguity by sampling multiple classifiers via a Bayesian formulation of meta-learning. We call it PLATIPUS: https://t.co/oOHQl1tuj4
— Sergey Levine (@svlevine) June 8, 2018
w/ @chelseabfinn and @imkelvinxu
some ambiguous celeba task: pic.twitter.com/oGakQW1Tr5
New paper: Similarity encoding for learning with dirty categorical variableshttps://t.co/j2JQxy5FcC
— Gael Varoquaux (@GaelVaroquaux) June 8, 2018
Code on https://t.co/9Saecz75MP
Useful for data scientists fighting with dirty data pic.twitter.com/0hmt0FXTfR
New paper on single trial dimensionality reduction and demixing in #neuroscience through tensor decompositions now published in @NeuroCellPress Congrats to @ItsNeuronal for leading this and thanks to @shenoystanford and Schnitzer lab for collaborating! https://t.co/EAxNd7ARj2
— Surya Ganguli (@SuryaGanguli) June 8, 2018
Check out my work at @GoogleAI on a linear complexity tSNE implementation for TensorFlow.js on the web! https://t.co/uXLEin9T5o
— Nicola Pezzotti (@nicolapezzotti) June 7, 2018
It has been great to collaborate with so many amazing engineers and researchers @zzznah @tafsiri @nsthorat @dsmilkov!
New AI safety paper - "Measuring and avoiding side effects using relative reachability": https://t.co/OIfaY3xIib
— DeepMind (@DeepMindAI) June 7, 2018
Just learned that our paper "Synthesizing Programs for Images using Reinforced Adversarial Learning" (aka SPIRAL) got a long talk at @icmlconf. If you haven't already, go check it out: https://t.co/1KA8brgIFg pic.twitter.com/T0LP8pGgwM
— Yaroslav Ganin (@yaroslav_ganin) June 7, 2018
Look forward to reading this - have enjoyed his big picture think pieces (informed by deep experience in planning algorithms) in the past. "Model-free, Model-based, and General Intelligence," Hector Geffner: https://t.co/DyWjvwoJnH
— Miles Brundage (@Miles_Brundage) June 7, 2018
Researchers develop AI that identifies and counts wildlife with 96.6% accuracy https://t.co/9JwjBQkHPz
— Nando de Freitas (@NandoDF) June 6, 2018
When the segmentation tool works so well that it almost directly gives you layers. Nice paper from @ofgulban: https://t.co/urrEE2Ll6z pic.twitter.com/NYORWQ95jb
— layerfMRI (@layerfMRI) June 6, 2018
Honored to receive the best paper award in COLT: "Algorithmic Regularization in Over-parameterized Matrix Sensing and Neural Networks with Quadratic Activations" https://t.co/7gXgwdOcQ1. Congrats to Yuanzhi and Hongyang!
— Tengyu Ma (@tengyuma) June 6, 2018