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Kamalika Chaudhuri
3,674 posts
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Kamalika Chaudhuri
@kamalikac
Researcher, Google Deepmind. Formerly, Director FAIR @ Meta. Former Professor at UCSD. Researcher in AI privacy, security, and generalization.
San Diego
cseweb.ucsd.edu/users/kamalika
Joined May 2008
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  • user avatar
    Kamalika Chaudhuri
    @kamalikac
    Apr 23, 2020
    Excited to teach a class this quarter on Trustworthy Machine Learning. Lecture notes available at cseweb.ucsd.edu/classes/sp20/c…. So far we have notes on the Statistical Learning Framework and Robustness!
  • user avatar
    Kamalika Chaudhuri
    @kamalikac
    Jul 7, 2019
    See all videos from ICML 2019 here.
    user avatar
    ICML Conference
    @icmlconf
    Jul 6, 2019
    New videos from ICML 2019 have been posted and linked into the schedule. See all videos here: icml.cc/Conferences/20…
  • user avatar
    Kamalika Chaudhuri
    @kamalikac
    Aug 5, 2020
    New blog post: ucsdml.github.io/jekyll/update/… Paper: arxiv.org/abs/2004.05675 TLDR; we formalize a type of overfitting called data-copying in generative models, and provide a three-sample non-parametric test to detect it. Work w/ @kc_meehan and S. Dasgupta. To appear in #AISTATS2020
    ucsdml.github.io
    How to Detect Data-Copying in Generative Models
    What does it mean for a generative model to overfit? We formalize the notion of ‘data-copying’, when a generative model produces only slight variations of the training set and fails to express the...
  • user avatar
    Kamalika Chaudhuri
    @kamalikac
    Apr 22, 2019
    #ICML2019 decisions are out! A big thanks to our reviewers, area chairs and senior area chairs for their hard work. See you all in Long Beach! @rsalakhu
  • user avatar
    Kamalika Chaudhuri
    @kamalikac
    Dec 9, 2023
    Do representation learning models memorize their training data? To understand this, we propose a new method called Deja vu to measure memorization in these models. #NeuRIPS2023
    30K
  • user avatar
    Kamalika Chaudhuri
    @kamalikac
    Jun 7, 2019
    At ICML 2019, @rsalakhu and I ran a new Code-at-Submit-Time Experiment. How did it do? Find out here:
    Medium
    The ICML 2019 Code-at-Submit-Time Experiment
    From medium.com
  • user avatar
    Kamalika Chaudhuri
    @kamalikac
    Jul 8, 2020
    New paper at #ICML2020 on robustness of non-parametric methods. Paper: arxiv.org/abs/2003.06121 We take a closer look at robustness properties of general non-parametric methods in the large sample limit.
    arXiv logo
    arxiv.org
    When are Non-Parametric Methods Robust?
    A growing body of research has shown that many classifiers are susceptible to {\em{adversarial examples}} -- small strategic modifications to test inputs that lead to misclassification. In this...
  • user avatar
    Kamalika Chaudhuri
    @kamalikac
    Aug 26, 2020
    How expressive are some normalizing flows? Find out at the #AISTATS2020 poster session for our paper "The Expressive Power of a Class of Normalizing Flow Models". Paper: arxiv.org/abs/2006.00392 Poster link: aistats2020.net/poster_1181.ht… Time: 3pm PDT Wed/9am PDT Fri Work w/ Z. Kong
  • user avatar
    Kamalika Chaudhuri
    @kamalikac
    Dec 3, 2024
    We know that LLMs learn facts, but how well do  they properly unlearn pieces of knowledge? We investigate "deep unlearning" in our new paper.
    26K
  • user avatar
    Kamalika Chaudhuri
    @kamalikac
    Jan 22, 2024
    How do we better design classifiers that know when they don't know? There are two different kinds of uncertainty measures in the literature -- aleatoric, or due to inherent noise in the data from overlapping classes, and epistemic, or uncertainty due to atypical inputs.
    15K
  • user avatar
    Kamalika Chaudhuri
    @kamalikac
    Aug 24, 2020
    Excited to speak at the Adversarial Learning Workshop at KDD tomorrow!
    user avatar
    Pin-Yu Chen
    @pinyuchenTW
    Aug 24, 2020
    The 2nd workshop on Adversarial Learning Methods for Machine Learning and Data Mining @kdd_news will take place tomorrow! (8 am to noon Pacific time), live-streamed by Youtube (link will be posted tmr) sites.google.com/view/advml Invited speakers: @kamalikac @QuanquanGu @UnaMayMIT
    Image
  • user avatar
    Kamalika Chaudhuri
    @kamalikac
    Oct 11, 2018
    @rsalakhu and I are co-chairing ICML 2019. Here's the CFP: icml.cc/Conferences/20…
  • user avatar
    Kamalika Chaudhuri
    @kamalikac
    Feb 18, 2019
    Thoughtful debate must begin with accurate facts. At @icmlconf there is gentle encouragement, but no "demand" for code, and no requirement whatsoever about data. See our FAQ: icml.cc/Conferences/20…
    user avatar
    Nando de Freitas
    @NandoDF
    Feb 16, 2019
    Replying to @ilyasut
    It is also surprising that conferences like @icmlconf and @iclr2019 are increasingly demanding code and dataset releases despite authors pointing out potential unethical uses of their datasets. We need thoughtful debate at upcoming conferences, and responsible solutions.
  • user avatar
    Kamalika Chaudhuri
    @kamalikac
    May 31, 2025
    Congratulations to my student @chhaviyadav_ for successfully defending her thesis today! Chhavi is doing super interesting work in trustworthy ml - keep an eye out for her. I am excited to see what she does next!
    user avatar
    Chhavi Yadav
    @chhaviyadav_
    May 30, 2025
    Successfully defended my thesis today! Extremely grateful to my amazing advisor, @kamalikac, whose unwavering support, insights, teachings and motherly love made all this possible.. Even the darkest of days seemed lighter & hopeful after spending just 5 mins with her! It has been
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    8.1K

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