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Computer Science

D-Index
30
Citations
6020
World Ranking
13900
National Ranking
5524

Overview

Atri Rudra is affiliated with the University at Buffalo, State University of New York in the United States. Their research contributions are primarily in the field of Computer Science, with notable work in several specialized subfields. These subfields include Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, Computer Networks and Communications, and Electrical and Electronic Engineering.

The scientist focuses on a range of research topics, such as Neural Networks and Applications, Topic Modeling, Domain Adaptation and Few-Shot Learning, Advanced Neural Network Applications, Time Series Analysis and Forecasting, Machine Learning in Healthcare, and Advanced Database Systems and Queries.

Atri Rudra has published extensively, with a strong presence in the arXiv preprint repository managed by Cornell University. Their frequent publication venues include:

  • arXiv (Cornell University)
  • Theory of Computing Systems
  • Applied Network Science
  • ACM SIGMOD Record
  • Proceedings of the ACM on Management of Data

Frequent coauthors of Rudra include Christopher Ré, Tri Dao, Albert Gu, Isys Johnson, and Daniel Y. Fu. The collaborations with these researchers have resulted in a series of papers contributing to various aspects of computer science and artificial intelligence.

Recent notable papers authored or coauthored by Atri Rudra include:

  • "FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness," 2022, published in arXiv (Cornell University)
  • "HiPPO: Recurrent Memory with Optimal Polynomial Projections," 2020, published in arXiv (Cornell University)
  • "Combining Recurrent, Convolutional, and Continuous-time Models with Linear State-Space Layers," 2021, published in arXiv (Cornell University)
  • "Hungry Hungry Hippos: Towards Language Modeling with State Space Models," 2022, published in arXiv (Cornell University)

The research covers a spectrum of topics, ranging from efficient attention mechanisms in neural networks to recurrent memory models and language modeling techniques. Their work addresses both theoretical and applied aspects of machine learning and data representation.

Best Publications

  • FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness

    Unknown

  • Efficient rijndael encryption implementation with composite field arithmetic

    A. Rudra;P.K. Dubey;C.S. Jutla;V. Kumar

  • When LP Is the Cure for Your Matching Woes: Improved Bounds for Stochastic Matchings

    Nikhil Bansal;Anupam Gupta;Jian Li;Julián Mestre

  • Online learning in online auctions

    Avrim Blum;Vijay Kumar;Atri Rudra;Felix Wu

  • Worst-case Optimal Join Algorithms

    Hung Q. Ngo;Ely Porat;Christopher Ré;Atri Rudra

  • Skew strikes back: new developments in the theory of join algorithms

    Hung Q Ngo;Christopher Ré;Atri Rudra

  • FAQ: Questions Asked Frequently

    Mahmoud Abo Khamis;Hung Q. Ngo;Atri Rudra

  • Worst-case optimal join algorithms: [extended abstract]

    Hung Q. Ngo;Ely Porat;Christopher Ré;Atri Rudra

  • Explicit Codes Achieving List Decoding Capacity: Error-Correction With Optimal Redundancy

    V. Guruswami;A. Rudra

  • Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers

    Albert Gu;Isys Johnson;Karan Goel;Khaled Saab

  • HiPPO: Recurrent Memory with Optimal Polynomial Projections

    Albert Gu;Tri Dao;Stefano Ermon;Atri Rudra

  • Ordering by weighted number of wins gives a good ranking for weighted tournaments

    Don Coppersmith;Lisa Fleischer;Atri Rudra

  • Approximating Matches Made in Heaven

    Ning Chen;Nicole Immorlica;Anna R. Karlin;Mohammad Mahdian

  • Efficiently decodable non-adaptive group testing

    Piotr Indyk;Hung Q. Ngo;Atri Rudra

  • Hungry Hungry Hippos: Towards Language Modeling with State Space Models

    Unknown

  • Explicit capacity-achieving list-decodable codes

    Venkatesan Guruswami;Atri Rudra

  • Joins via Geometric Resolutions: Worst Case and Beyond

    Mahmoud Abo Khamis;Hung Q. Ngo;Christopher Ré;Atri Rudra

  • Testing low-degree polynomials over prime fields

    Charanjit S. Jutla;Anindya C. Patthak;Atri Rudra;David Zuckerman

  • An energy complexity model for algorithms

    Swapnoneel Roy;Atri Rudra;Akshat Verma

  • Using smartphones to collect time–activity data for long-term personal-level air pollution exposure assessment

    Mark L. Glasgow;Carole B. Rudra;Eun Hye Yoo;Murat Demirbas

  • Learning Fast Algorithms for Linear Transforms Using Butterfly Factorizations

    Tri Dao;Albert Gu;Matthew Eichhorn;Atri Rudra

  • Testing low-degree polynomials over prime fields: Testing Low-Degree Polynomials

    Charanjit S. Jutla;Anindya C. Patthak;Atri Rudra;David Zuckerman

  • Efficiently Decodable Error-Correcting List Disjunct Matrices and Applications - (Extended Abstract).

    Hung Q. Ngo;Ely Porat;Atri Rudra

  • Explicit Capacity-Achieving List-Decodable Codes or Decoding Folded Reed-Solomon Codes up to their Distance

    Venkatesan Guruswami;Atri Rudra

Frequent Co-Authors

Christopher Ré
Christopher Ré Stanford University
Hung Q. Ngo
Hung Q. Ngo University at Buffalo, State University of New York
Venkatesan Guruswami
Venkatesan Guruswami University of California, Berkeley
Anna C. Gilbert
Anna C. Gilbert Yale University
Ely Porat
Ely Porat Bar-Ilan University
Murat Demirbas
Murat Demirbas University at Buffalo, State University of New York
Nikhil Bansal
Nikhil Bansal University of Michigan–Ann Arbor
Charanjit S. Jutla
Charanjit S. Jutla IBM (United States)
Michael Langberg
Michael Langberg University at Buffalo, State University of New York
Robert Krauthgamer
Robert Krauthgamer Weizmann Institute of Science

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