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researcher

Shachar Lovett

83 papers hereh-index 333.8k citations160 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • sole author7
  • first author11
  • middle author36
  • last author27

Across the 81 of 83 papers where every author was matched, so the position is known.

fields
  • cs.CC30
  • math.CO23
  • cs.LG10
  • cs.DM4
  • cs.DS4
  • cs.CG3
same name
  • Shachar Lovett — 3 papers
  • Shachar Lovett — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20072026
most citedBilinear Classes: A Structural Framework for Provable Generalization in RL

20 citations · 164 across the 63 of their papers we have counts for

collaborators
Showing cs.DMShow all

4 papers · 1 filter

cs.DM2021

Hypercontractivity on High Dimensional Expanders: a Local-to-Global Approach for Higher Moments

Mitali Bafna, Max Hopkins, Tali Kaufman +1

Hypercontractivity is one of the most powerful tools in Boolean function analysis. Originally studied over the discrete hypercube, recent years have seen increasing interest in ext…

cs.DM2018

MDS matrices over small fields: A proof of the GM-MDS conjecture

Shachar Lovett

An MDS matrix is a matrix whose minors all have full rank. A question arising in coding theory is what zero patterns can MDS matrices have. There is a natural combinatorial charact…

cs.DM2015

Bias vs structure of polynomials in large fields, and applications in information theory

Abhishek Bhowmick, Shachar Lovett

Let f be a polynomial of degree d in n variables over a finite field F. The polynomial is said to be unbiased if the distribution of f(x) for a uniform input $x…

cs.DM2012★ 1 cited

A Tail Bound for Read-k Families of Functions

Dmytro Gavinsky, Shachar Lovett, Michael Saks +1

We prove a Chernoff-like large deviation bound on the sum of non-independent random variables that have the following dependence structure. The variables Y1​,...,Yr​ are arbitrar…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.