Research scientist @NVIDIA.

Toronto, Canada
Joined June 2021
(1/7) Our #CVPR2022 paper “How Much More Data Do I Need? Estimating Requirements For Downstream Tasks” explores data collection practices! w/ @james_r_lucas @davidjesusacu @lidaiqing @PhilionJonah @ALVAREZ_JOSEM @ZhidingYu @FidlerSanja @MarcTLaw Webpage: nv-tlabs.github.io/estimatin…
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Marc T. Law retweeted
How Much More Data Do I Need? Estimating Requirements for Downstream Tasks abs: arxiv.org/abs/2207.01725
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We just release the f-DAL source code into an easy-to-use library that allows integrating f-DAL with existing pipelines by only changing a few lines of code. Check it out nv-tlabs.github.io/fDAL/.
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Excited to share fDAL #ICML2021 We connect theory and algorithms for domain adaptation using a novel f-divergence based bound. fDAL explains existing algorithms, shows their bottlenecks and how to fix them! arxiv.org/abs/2106.11344 w/ @gjzhang1 @MarcTLaw @FidlerSanja @NVIDIAAI
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