Keivan Alizadeh-Vahid
email: knavweuhandsiscn.t@egi.o unscramble

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I am a Computer Science PhD student at University of Washington jointly advised by Ali Farhadi & Mohammad Rastegari. Before joining here, I received my B.Sc. Degree in Software Engineering from Sharif University of Technology.

My research interests include computer vision and machine learning and optimization. I am interested in finding more efficient solutions to the existing problems in ML. I'm also interested in defining and solving new tasks that can further extend our intelligent systems' abilities.

  Preprints
* - equal contribution
NED

[NEW] In the Wild: From ML Models to Pragmatic ML Systems
Matthew Wallingford, Aditya Kusupati*, Keivan Alizadeh-Vahid*, Aaron Walsman, Aniruddha Kembhavi and Ali Farhadi
Under Review, 2020

abstract / bibtex / pdf / arXiv / code

  Publications
BFT

Butterfly Transform: An Efficient FFT Based Neural Architecture Design
Keivan Alizadeh-Vahid, Anish Prabhu , Ali Farhadi and Mohammad Rastegari
Conference on Computer Vision and Pattern Recognition (CVPR), 2020

abstract / bibtex / pdf / arXiv / code / poster / presentation / video

RPF

Recurrent Poisson Factorization for Temporal Recommendation
Seyed Abbas Hosseini, Keivan Alizadeh, Ali Khodadadi, Ali Arabzadeh, Mehrdad Farajtabar, Hongyuan Zha, Hamid R Rabiee
ACM Conference on Knowledge Discovery and Data Mining (KDD), 2017

We also published a refined version on IEEE Transactions on Knowledge and Data Engineering 2018.

abstract / bibtex / pdf / arXiv / code


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