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Computer Science

D-Index
68
Citations
91193
World Ranking
2015
National Ranking
1017

Overview

Michael Isard is a researcher affiliated with Google in the United States. Their work primarily focuses on computer science with a specialization in several subfields including artificial intelligence, computer vision and pattern recognition, hardware and architecture, computer networks and communications, and information systems.

The research topics covered by their publications include natural language processing techniques, parallel computing and optimization techniques, topic modeling, multimodal machine learning applications, cloud computing and resource management, graph theory and algorithms, and image retrieval and classification techniques.

Michael Isard has contributed to multiple papers published mainly in the venue arXiv (Cornell University), and also in UNC Libraries and Communications of the ACM. Significant papers include:

  • PaLM: Scaling Language Modeling with Pathways (2022), arXiv (Cornell University)
  • Gemini: A Family of Highly Capable Multimodal Models (2023), arXiv (Cornell University)
  • Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context (2024), arXiv (Cornell University)
  • PaLM 2 Technical Report (2023), arXiv (Cornell University)
  • Pathways: Asynchronous Distributed Dataflow for ML (2022), arXiv (Cornell University)

Their frequent co-authors include Aakanksha Chowdhery, Paul Barham, Andrew M. Dai, Érica Rodrigues Moreira, and Orhan Fırat. This collaboration suggests a research network centered around advanced machine learning models and distributed computing architectures.

Michael Isard's work explores highly technical dimensions of scalable machine learning systems and multimodal AI, evidenced by their involvement in studies addressing large-scale language models, multimodal understanding, and asynchronous dataflow systems for machine learning.

Best Publications

  • TensorFlow: a system for large-scale machine learning

    Martín Abadi;Paul Barham;Jianmin Chen;Zhifeng Chen

  • TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

    Martín Abadi;Ashish Agarwal;Paul Barham;Eugene Brevdo

  • C ONDENSATION —Conditional Density Propagation forVisual Tracking

    Michael Isard;Andrew Blake

  • The CONDENSATION Algorithm - Conditional Density Propagation and Applications to Visual Tracking

    Andrew Blake;Michael Isard

  • Object retrieval with large vocabularies and fast spatial matching

    J. Philbin;O. Chum;M. Isard;J. Sivic

  • Dryad: distributed data-parallel programs from sequential building blocks

    Michael Isard;Mihai Budiu;Yuan Yu;Andrew Birrell

  • Contour Tracking by Stochastic Propagation of Conditional Density

    Michael Isard;Andrew Blake

  • Active Contours: The Application of Techniques from Graphics, Vision, Control Theory and Statistics to Visual Tracking of Shapes in Motion

    Andrew Blake;Michael Isard

  • Lost in quantization: Improving particular object retrieval in large scale image databases

    J. Philbin;O. Chum;M. Isard;J. Sivic

  • Quincy: fair scheduling for distributed computing clusters

    Michael Isard;Vijayan Prabhakaran;Jon Currey;Udi Wieder

  • Total Recall: Automatic Query Expansion with a Generative Feature Model for Object Retrieval

    O. Chum;J. Philbin;J. Sivic;M. Isard

  • DryadLINQ: a system for general-purpose distributed data-parallel computing using a high-level language

    Yuan Yu;Michael Isard;Dennis Fetterly;Mihai Budiu

  • Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

    Unknown

  • Naiad: a timely dataflow system

    Derek G. Murray;Frank McSherry;Rebecca Isaacs;Michael Isard

  • BraMBLe: a Bayesian multiple-blob tracker

    M. Isard;J. MacCormick

  • ICONDENSATION: Unifying Low-Level and High-Level Tracking in a Stochastic Framework

    Michael Isard;Andrew Blake

  • Nonparametric belief propagation

    Erik B. Sudderth;Alexander T. Ihler;Michael Isard;William T. Freeman

  • Partitioned Sampling, Articulated Objects, and Interface-Quality Hand Tracking

    John MacCormick;Michael Isard

  • A Multi-View Embedding Space for Modeling Internet Images, Tags, and Their Semantics

    Yunchao Gong;Qifa Ke;Michael Isard;Svetlana Lazebnik

  • PaLM 2 Technical Report

    Unknown

  • Tracking loose-limbed people

    L. Sigal;S. Bhatia;S. Roth;M.J. Black

  • Bundling features for large scale partial-duplicate web image search

    Zhong Wu;Qifa Ke;Michael Isard;Jian Sun

Frequent Co-Authors

Andrew Blake
Andrew Blake University of Cambridge
Martín Abadi
Martín Abadi Google (United States)
Paul Barham
Paul Barham Google (United States)
Frank McSherry
Frank McSherry Materialize, Inc.
Andrew Zisserman
Andrew Zisserman University of Oxford
Leonid Sigal
Leonid Sigal University of British Columbia
Michael J. Black
Michael J. Black Max Planck Institute for Intelligent Systems
Tim Harris
Tim Harris Oracle (United States)
Henricus Johannes Maria Meijer
Henricus Johannes Maria Meijer Microsoft (United States)

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