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Piotr Indyk

Piotr Indyk

D-Index & Metrics

Computer Science

D-Index
90
Citations
45910
World Ranking
598
National Ranking
322

Research.com Recognitions

  • 2015 - ACM Fellow For contributions to high-dimensional geometric computing, streaming/sketching algorithms, and the Sparse Fourier Transform.
  • 2012 - ACM Paris Kanellakis Theory and Practice Award With Andrei Broder and Moses S Charikar, for their groundbreaking work on Locality-Sensitive Hashing that has had great impact in many fields of computer science including computer vision, databases, information retrieval, machine learning, and signal processing.
  • 2003 - Fellow of Alfred P. Sloan Foundation

Overview

Piotr Indyk is affiliated with MIT in the United States and has contributed extensively to the field of computer science, with a focus on several subfields and topics.

Their primary fields of study include:

  • Computer Science

Within this broad area, they have specialized in subfields such as:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Computational Mechanics
  • Management Science and Operations Research
  • Computer Networks and Communications

Key topics of their work cover:

  • Machine Learning and Algorithms
  • Sparse and Compressive Sensing Techniques
  • Domain Adaptation and Few-Shot Learning
  • Imbalanced Data Classification Techniques
  • Data Management and Algorithms
  • Stochastic Gradient Optimization Techniques
  • Computational Geometry and Mesh Generation

Recent papers authored or coauthored by Piotr Indyk include:

  • Targeted Supervised Contrastive Learning for Long-Tailed Recognition, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Targeted Supervised Contrastive Learning for Long-Tailed Recognition, 2021, arXiv (Cornell University)
  • Learning-based Support Estimation in Sublinear Time, 2021, arXiv (Cornell University)
  • Addressing Feature Suppression in Unsupervised Visual Representations, 2023, 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • Optimal (Euclidean) Metric Compression, 2022, SIAM Journal on Computing

Frequent coauthors of Piotr Indyk are:

  • Sandeep Silwal
  • Tal Wagner
  • Shyam Narayanan
  • Ronitt Rubinfeld
  • Tianhong Li

Publication venues where their work has been featured include:

  • arXiv (Cornell University)
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • SIAM Journal on Computing

Over the course of their career, they have received several distinctions including:

  • ACM Fellow (2015) for contributions to high-dimensional geometric computing, streaming/sketching algorithms, and the Sparse Fourier Transform
  • ACM Paris Kanellakis Theory and Practice Award (2012) with collaborators for work on Locality-Sensitive Hashing impacting multiple computer science fields
  • Fellow of Alfred P. Sloan Foundation (2003)

Best Publications

  • Approximate nearest neighbors: towards removing the curse of dimensionality

    Piotr Indyk;Rajeev Motwani

  • Similarity Search in High Dimensions via Hashing

    Aristides Gionis;Piotr Indyk;Rajeev Motwani

  • Locality-sensitive hashing scheme based on p-stable distributions

    Mayur Datar;Nicole Immorlica;Piotr Indyk;Vahab S. Mirrokni

  • Near-Optimal Hashing Algorithms for Approximate Nearest Neighbor in High Dimensions

    Alexandr Andoni;Piotr Indyk

  • Near-optimal hashing algorithms for approximate nearest neighbor in high dimensions

    Alexandr Andoni;Piotr Indyk

  • Maintaining Stream Statistics over Sliding Windows

    Mayur Datar;Aristides Gionis;Piotr Indyk;Rajeev Motwani

  • Enhanced hypertext categorization using hyperlinks

    Soumen Chakrabarti;Byron Dom;Piotr Indyk

  • Stable distributions, pseudorandom generators, embeddings, and data stream computation

    Piotr Indyk

  • Approximate Nearest Neighbor: Towards Removing the Curse of Dimensionality

    Sariel Har-Peled;Piotr Indyk;Rajeev Motwani

  • Locality-Sensitive Hashing Using Stable Distributions

    Gregory Shakhnarovich;Trevor Darrell;Piotr Indyk

  • Finding interesting associations without support pruning

    E. Cohen;M. Datar;S. Fujiwara;A. Gionis

  • Nearest-neighbor methods in learning and vision : theory and practice

    Gregory Shakhnarovich;Piotr Indyk;Trevor Darrell

  • Approximate clustering via core-sets

    Mihai Bādoiu;Sariel Har-Peled;Piotr Indyk

  • Combining geometry and combinatorics: A unified approach to sparse signal recovery

    R. Berinde;A.C. Gilbert;P. Indyk;H. Karloff

  • Simple and practical algorithm for sparse fourier transform

    Haitham Hassanieh;Piotr Indyk;Dina Katabi;Eric Price

  • Sparse Recovery Using Sparse Matrices

    Anna Gilbert;Piotr Indyk

  • Algorithmic applications of low-distortion geometric embeddings

    P. Indyk

  • Practical and optimal LSH for angular distance

    Alexandr Andoni;Piotr Indyk;Thijs Laarhoven;Ilya Razenshteyn

  • Maintaining stream statistics over sliding windows: (extended abstract)

    Mayur Datar;Aristides Gionis;Piotr Indyk;Rajeev Motwani

  • Fast Estimation of Diameter and Shortest Paths (Without Matrix Multiplication)

    D. Aingworth;C. Chekuri;P. Indyk;R. Motwani

  • Nearest-Neighbor Methods in Learning and Vision: Theory and Practice (Neural Information Processing)

    Gregory Shakhnarovich;Trevor Darrell;Piotr Indyk

Frequent Co-Authors

Alexandr Andoni
Alexandr Andoni Columbia University
David P. Woodruff
David P. Woodruff Carnegie Mellon University
Rajeev Motwani
Rajeev Motwani Stanford University
Trevor Darrell
Trevor Darrell University of California, Berkeley
Gregory Shakhnarovich
Gregory Shakhnarovich Toyota Technological Institute at Chicago
Sariel Har-Peled
Sariel Har-Peled University of Illinois at Urbana-Champaign
Aristides Gionis
Aristides Gionis Royal Institute of Technology

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