Parikshit Gopalan
where else to find them
what they talk about
where they keep going back
- ITCS2 editions2022–2023
on a stage with
all 6 in the filters
who talks about the same things
- Udi Wieder2 talks
- Omer Reingold5 talks
- Michael P. Kim3 talks
- Lunjia Hu2 talks
- Varun Gupta7 talks
- Yuval Filmus9 talks
| title | conference | date |
|---|---|---|
| Loss Minimization through the lens of Outcome Indistinguishability | ITCS 2023 | 2023-01-10 |
Paper proves that requiring loss OI—Outcome Indistinguishability for a loss-derived distinguisher class—is sufficient to get an Omnipredictor, with learning… | ||
| Omnipredictors | ITCS 2022 | 2022-01-31 |
Shows that a multi-calibrated predictor (computed from data via a weak agnostic learner and multicalibration algorithms) serves as an omnipredictor for… | ||
| On the Power of Gradually Increasing Independence | Connections Between Algorithm Design and Complexity Theory | 2015-09-28 |
An iterative PRG method breaks a hard global test into stages that reduce dimension (n → √n → …) and increases independence at each stage so that a k-wise… | ||
| Coding for Modern Distributed Storage Systems I | Information Theory Boot Camp 2015 | 2015-01-13 |
Introduces a formal data locality R and proves any linear code with that locality needs length at least K + ceil(K/R) + D − 2, so locality forces a roughly… | ||
| Coding for Modern Distributed Storage Systems II | Information Theory Boot Camp 2015 | 2015-01-13 |
Continues the LRC story with explicit constructions and a concrete failure model: a Reed–Solomon variant picks a degree set skipping every (R+1)th monomial to… | ||
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