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If you are up early tomorrow, come to my talk at #CVPR2019 workshop on Vision With Biased or Scarce Data https://wvbsd.github.io/2019/ I will show our recent results on detecting hard examples using a new angular distance measure. Also talk about many ways to reduce our data reqs
Co-authors @BeidiChen @animesh_garg @Anshumali_ Zhiding Weiyung on detecting hard examples @NvidiaAI Active learning with @HuPeiyun @zacharylipton Deva Ramanan. Crowdsourcing with Ashish Khetan @zacharylipton Semi-supervised learning with neural rendering @TanNguyen689 Nhat Ho..
Otherwise you can attend my talk at 10:30AM tomorrow at #CVPR2019 workshop on semantic information https://sites.google.com/view/wsi-2019/ on Beyond Black-Boxes: Embedding Semantic Structures into Learning
#tensor operations in #NeuralNetworks lead to compression @JeanKossaifi @zacharylipton @furlanel @arankhanna #tensor-train LSTMs are much better for long-term #forecasting @yuqirose @StephanZheng @yisongyue + video prediction Jiahao Wonmin @furongh @jankautz @NvidiaAI
Other ways to add semantic structure into learning: blending symbolic expressions with data and learning common embeddings @ForoughArabsha1 Sameer Singh. Adding learning to control while retaining stability: @yisongyue @GuanyaShi Anqi Liu Soon Jo Chung @kazizzad @yuqirose
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