publications

publications by categories in reversed chronological order. for a more complete list check my google scholar

2023

  1. Efficiently Computing Sparse Fourier Transforms of q -ary Functions
    Yigit Efe Erginbas, Justin Singh Kang, Amirali Aghazadeh, and Kannan Ramchandran
    arXiv:2301.06200 2023
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2022

  1. Current progress and open challenges for applying deep learning across the biosciences
    Nicolae Sapoval, Amirali Aghazadeh, Michael G Nute, Dinler A Antunes, Advait Balaji, and 6 more authors
    Nature Communications 2022
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  2. On the sparsity of fitness functions and implications for learning
    David H Brookes, Amirali Aghazadeh, and Jennifer Listgarten
    Proceedings of the National Academy of Sciences (PNAS) 2022
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  3. BEAR: Sketching BFGS Algorithm for Ultra-High Dimensional Feature Selection in Sublinear Memory
    Amirali Aghazadeh, Vipul Gupta, Alex DeWeese, Ozan Koyluoglu, and Kannan Ramchandran
    In Mathematical and Scientific Machine Learning (MSML) 2022
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  4. Spectral Regularization Allows Data-frugal Learning over Combinatorial Spaces
    Amirali Aghazadeh, Nived Rajaraman, Tony Tu, and Kannan Ramchandran
    arXiv:2210.02604 2022
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2021

  1. Epistatic Net allows the sparse spectral regularization of deep neural networks for inferring fitness functions
    Amirali Aghazadeh, Hunter Nisonoff, Orhan Ocal, David H Brookes, Yijie Huang, and 3 more authors
    Nature Communications 2021
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  2. Group-Structured Adversarial Training
    Farzan Farnia, Amirali Aghazadeh, James Zou, and David Tse
    arXiv:2106.10324 2021
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  3. Anomalous nanoparticle surface diffusion in LCTEM is revealed by deep learning-assisted analysis
    Vida Jamali, Cory Hargus, Assaf Ben-Moshe, Amirali Aghazadeh, Hyun Dong Ha, and 2 more authors
    Proceedings of the National Academy of Sciences 2021
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2020

  1. CRISPRLand: Interpretable large-scale inference of DNA repair landscape based on a spectral approach
    Amirali Aghazadeh, Orhan Ocal, and Kannan Ramchandran
    Bioinformatics 2020
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2019

  1. Large dataset enables prediction of repair after CRISPR–Cas9 editing in primary T cells
    Ryan T Leenay, Amirali Aghazadeh, Joseph Hiatt, David Tse, Theodore L Roth, and 6 more authors
    Nature Biotechnology 2019
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  2. Data-driven semi-supervised and supervised learning algorithms for health monitoring of pipes
    Debarshi Sen, Amirali Aghazadeh, Ali Mousavi, Satish Nagarajaiah, Richard Baraniuk, and 1 more author
    Mechanical Systems and Signal Processing 2019
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  3. Sparsity-based approaches for damage detection in plates
    Debarshi Sen, Amirali Aghazadeh, Ali Mousavi, Satish Nagarajaiah, and Richard Baraniuk
    Mechanical Systems and Signal Processing 2019
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2018

  1. MISSION: Ultra large-scale feature selection using Count Sketches
    Amirali Aghazadeh, Ryan Spring, Daniel LeJeune, Gautam Dasarathy, Anshumali Shrivastava, and 1 more author
    In International Conference on Machine Learning (ICML) 2018
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  2. Insense: Incoherent sensor selection for sparse signals
    Amirali Aghazadeh, Mohammad Golbabaee, Andrew Lan, and Richard Baraniuk
    Signal Processing 2018
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2017

  1. Rhash: Robust hashing via l∞-norm distortion
    Amirali Aghazadeh, Andrew Lan, Anshumali Shrivastava, and Richard Baraniuk
    In International Joint Conference on Artificial Intelligence (IJCAI) 2017
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  2. Machine Learning in Large-scale Genomics: Sensing, Processing, and Analysis
    Amirali Aghazadeh
    2017
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2016

  1. Universal microbial diagnostics using random DNA probes
    Amirali Aghazadeh, Adam Y Lin, Mona A Sheikh, Allen L Chen, Lisa M Atkins, and 4 more authors
    Science Advances 2016
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2013

  1. Adaptive step size selection for optimization via the ski rental problem
    Amirali Aghazadeh, Ali Ayremlou, Daniel D Calderón, Tom Goldstein, Raajen Patel, and 2 more authors
    In International Conference on Acoustics, Speech and Signal Processing (ICASSP) 2013
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