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Personal profile

Education/Academic qualification

Computer Science, PhD, University of California, Berkeley

20082013

Computer Science and Engineering, BTech, Indian Institute of Technology, Kanpur

20042008

Fingerprint Dive into the research topics where Anindya De is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Polynomials Engineering & Materials Science
Extractor Mathematics
Boolean functions Engineering & Materials Science
Threshold Function Mathematics
Random variables Engineering & Materials Science
Seed Engineering & Materials Science
Hardness Engineering & Materials Science
Pseudorandom Generator Mathematics

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Grants 2018 2018

Power Indices
Boolean Functions
Random variable
Social Choice
Vote

Research Output 2005 2019

  • 373 Citations
  • 28 Conference contribution
  • 11 Article

Density estimation for shift-invariant multidimensional distributions

De, A., Long, P. M. & Servedio, R. A., Jan 1 2019, 10th Innovations in Theoretical Computer Science, ITCS 2019. Blum, A. (ed.). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, 28. (Leibniz International Proceedings in Informatics, LIPIcs; vol. 124).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Invariance
Learning algorithms
Contamination

Optimal mean-based algorithms for trace reconstruction1,2

De, A., O’Donnell, R. & Servedio, R. A., Apr 1 2019, In : Annals of Applied Probability. 29, 2, p. 851-874 24 p.

Research output: Contribution to journalArticle

Trace
Deletion
Annual
Insertion
Strings

Simple and efficient pseudorandom generators from Gaussian processes

Chattopadhyay, E., De, A. & Servedio, R. A., Jul 1 2019, 34th Computational Complexity Conference, CCC 2019. Shpilka, A. (ed.). Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, (Leibniz International Proceedings in Informatics, LIPIcs; vol. 137).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Covariance matrix
Seed
Invariance

A new central limit theorem and decomposition for Gaussian polynomials, with an application to deterministic approximate counting

De, A. & Servedio, R. A., Aug 1 2018, In : Probability Theory and Related Fields. 171, 3-4, p. 981-1044 64 p.

Research output: Contribution to journalArticle

Central limit theorem
Counting
Decompose
Polynomial
Threshold Function
3 Citations (Scopus)

Boolean function analysis meets stochastic optimization: An approximation scheme for stochastic knapsack

De, A., Jan 1 2018, 29th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2018. Czumaj, A. (ed.). Association for Computing Machinery, p. 1286-1305 20 p. (Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Boolean functions
Knapsack
Stochastic Optimization
Approximation Scheme
Boolean Functions