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Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning
#ICLR2018 General purpose, fixed-length representations of sentences via multi-task training by@sandeep1337@APTrizzle ArXiv https://arxiv.org/abs/1804.00079 Github https://github.com/Maluuba/gensen pic.twitter.com/7le5BHPTGX
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Interested in causal models? Check out our work applying it to genomics.
#ICLR2018 4:30-6:30p today @ East Meeting (#9). With Dave Blei@blei_labpic.twitter.com/CJp1loZH6m
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Visit the
#ICLR2018 Google booth now to see some Project Magenta demos (https://magenta.tensorflow.org/demos/ ) and chat with researcher@jesseengel about using machine learning and generative models to explore melodies and beats in the browser.pic.twitter.com/9F66g4h40i
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Google Zurich's Jannis Bulian (Software Engineer) and Neil Houlsby (Research Scientist) discuss a new framework that uses deep reinforcement learning to Ask the Right Questions, in an
#ICLR2018 contributed talk. To learn more, check out the paper at http://goo.gl/3LZz8W pic.twitter.com/SLxi6dInJi
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Available in PyTorch 0.4 as optim.Adam(amsgrad=True) https://pytorch.org/docs/stable/optim.html#torch.optim.Adam …
#ICLR2018 talk and best paper https://twitter.com/ale_suglia/status/991232574738653184 …
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Spherical CNNs: rotation equivariant CNNs for spherical signals (e.g. omnidirectional images, signals on the globe)
#iclr2018 talk https://github.com/jonas-koehler/s2cnn … -
A small glimpse of Googlers presenting at
#ICLR2018, with a Best Paper award (http://goo.gl/bVjGwZ ),@jesseengel sharing work on Latent Constraints (http://goo.gl/U39haK ), and an Empirical Study: Sensitivity and Generalization in Neural Networks (http://goo.gl/84aDNm )pic.twitter.com/NFUFGHWdql
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"Accelerated SGD is a better suited algorithm for pure SGD than momentum methods such as NAG, Heavy-Ball" Kidambi et. al.
#iclr2018 talk https://github.com/rahulkidambi/AccSGD … -
I'll be presenting our work on latent constraints at
#ICLR2018 tomorrow 4:30-6:30pm. Come by and say hi! (http://g.co/magenta/latent-constraints …)pic.twitter.com/VAccFuaKaB
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Read all about the research that Google is presenting this week at
@ICLR18 in Vancouver, including a best paper award!#ICLR2018#DeepLearning#MachineLearninghttp://goo.gl/oKgSG4 -
Privacy and ML: two unexpected allies? Read our new
#CleverHans blog post with@goodfellow_ian on how ML researchers can contribute to and benefit from research on differential privacy! Join us at our poster (#11) on PATE tomorrow (Monday) at#ICLR2018 http://www.cleverhans.io/privacy/2018/04/29/privacy-and-machine-learning.html … -
We will be presenting "A Neural Representation of Sketch Drawings" at
#ICLR2018. Please come by to say hello to@douglas_eck and myself! Details: https://iclr.cc/Conferences/2018/Schedule?showEvent=293 … Poster PDF: https://goo.gl/cBztfd pic.twitter.com/pe70rfGWRW
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Details of all our
#ICLR2018 papers in one place -https://deepmind.com/blog/deepmind-papers-iclr-2018/ …pic.twitter.com/grT5wlfXiy
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Congratulations to Google Brain team and CMU researchers for achieving 1st place on the
@stanford Question Answering Dataset (SQuAD) leaderboard (https://rajpurkar.github.io/SQuAD-explorer/ ). They will be presenting their work next week at#ICLR2018 with their paper https://arxiv.org/abs/1804.09541 https://twitter.com/lmthang/status/989229887473909761 …
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"Measuring the Intrinsic Dimension of Objective Landscapes" https://eng.uber.com/intrinsic-dimension/ …,
#ICLR2018. Turns out loss landscapes are simpler than you might think! Measuring carefully can give beautiful insights. And some RL problems are way easy. With@ChunyuanLi and@mimosavvy. -
Happy to announce our QANet models, #1 on
@stanfordnlp question answering dataset (SQuAD). 3 ideas: deep & fast arch (130+ layers), data augmentation, transfer learning. Joint work /w@AdamsYu@dmdohan@oahziur, Quoc Le, et al. See our#ICLR2018 paper https://openreview.net/pdf?id=B14TlG-RW …pic.twitter.com/wSdKHp4nCt
এই থ্রেডটি দেখান -
We just released the
@PyTorch implementation of our#ICLR2018 paper, Active Neural Localization: http://github.com/devendrachaplot/Neural-Localization … … Environment code and pre-trained models available too. - with E. Parisotto and R. Salakhutdinov (@rsalakhu) -
New
#iclr2018 paper on Unifying Deep Generative Models: Establishing formal connections between deep generative modelling approaches, including GANs and VAEs, with Zhiting Hu, Zichao Yang, and Eric Xing: Paper: https://openreview.net/forum?id=rylSzl-R-¬eId=rJkg4yTSM … -
Large-Scale Optimal Transport and Mapping Estimation https://arxiv.org/abs/1711.02283 - A stochastic dual algorithm for large-scale optimal transport - A method to turn a transportation plan into a Monge 1-to-1 map - Applications to generative modeling and domain adaptation
#ICLR2018 pic.twitter.com/bW34JhaVRU
এই থ্রেডটি দেখান -
Our new
#iclr2018 paper on Learning Awareness Models, with@laurent_dinh@serkancabi@notmisha@NandoDF and many others. Paper: https://openreview.net/pdf?id=r1HhRfWRZ … Videos: https://goo.gl/mZuqAV pic.twitter.com/hDiW2ochCk
এই থ্রেডটি দেখান
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