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Computer Science

D-Index
51
Citations
14874
World Ranking
5236
National Ranking
2410

Overview

Vikas Sindhwani is a researcher affiliated with Google in the United States. Their work focuses on fields spanning Computer Science and Engineering, with significant contributions to Control and Systems Engineering, Computer Vision and Pattern Recognition, and Artificial Intelligence. Additional expertise includes Biomedical Engineering and Aerospace Engineering.

The scientist's research topics cover several key areas within robotics and machine learning, including:

  • Robotic Path Planning Algorithms
  • Reinforcement Learning in Robotics
  • Robot Manipulation and Learning
  • Fault Detection and Control Systems
  • Multimodal Machine Learning Applications
  • Model Reduction and Neural Networks
  • Human Pose and Action Recognition

Vikas Sindhwani has contributed extensively to academic publications, with a large number of works appearing in prominent venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • IEEE Robotics and Automation Letters
  • 2022 International Conference on Robotics and Automation (ICRA)
  • The International Journal of Robotics Research
  • Foundations of Computational Mathematics

Some recent papers authored or coauthored by Sindhwani are:

  • "Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language" (2022, arXiv (Cornell University))
  • "Transporter Networks: Rearranging the Visual World for Robotic Manipulation" (2020, arXiv (Cornell University))
  • "Learning Stability Certificates from Data" (2020, arXiv (Cornell University))
  • "Trajectory Optimization with Optimization-Based Dynamics" (2022, IEEE Robotics and Automation Letters)

Collaboration is also a significant aspect of Sindhwani's research, with frequent coauthors including:

  • Krzysztof Choromański
  • Deepali Jain
  • Pete Florence
  • Sumeet Singh

Best Publications

  • Manifold Regularization: A Geometric Framework for Learning from Labeled and Unlabeled Examples

    Mikhail Belkin;Partha Niyogi;Vikas Sindhwani

  • Low-rank matrix factorization for Deep Neural Network training with high-dimensional output targets

    Tara N. Sainath;Brian Kingsbury;Vikas Sindhwani;Ebru Arisoy

  • Beyond the point cloud: from transductive to semi-supervised learning

    Vikas Sindhwani;Partha Niyogi;Mikhail Belkin

  • Optimization Techniques for Semi-Supervised Support Vector Machines

    Olivier Chapelle;Vikas Sindhwani;Sathiya S. Keerthi

  • A Co-Regularization Approach to Semi-supervised Learning with Multiple Views

    Vikas Sindhwani;Partha Niyogi;Mikhail Belkin

  • Socratic Models: Composing Zero-Shot Multimodal Reasoning with Language

    Unknown

  • SystemML: Declarative machine learning on MapReduce

    Amol Ghoting;Rajasekar Krishnamurthy;Edwin Pednault;Berthold Reinwald

  • Data Quality from Crowdsourcing: A Study of Annotation Selection Criteria

    Pei-Yun Hsueh;Prem Melville;Vikas Sindhwani

  • On Manifold Regularization.

    Misha Belkin;Partha Niyogi;Vikas Sindhwani

  • Large scale semi-supervised linear SVMs

    Vikas Sindhwani;S. Sathiya Keerthi

  • An RKHS for multi-view learning and manifold co-regularization

    Vikas Sindhwani;David S. Rosenberg

  • Document-Word Co-regularization for Semi-supervised Sentiment Analysis

    V. Sindhwani;P. Melville

  • Structured transforms for small-footprint deep learning

    Vikas Sindhwani;Tara N. Sainath;Sanjiv Kumar

  • A Non-negative Matrix Tri-factorization Approach to Sentiment Classification with Lexical Prior Knowledge

    Tao Li;Yi Zhang;Vikas Sindhwani

  • Learning evolving and emerging topics in social media: a dynamic nmf approach with temporal regularization

    Ankan Saha;Vikas Sindhwani

  • An Efficient Method for Gradient-Based Adaptation of Hyperparameters in SVM Models

    S. S. Keerthi;Vikas Sindhwani;Olivier Chapelle

  • Branch and Bound for Semi-Supervised Support Vector Machines

    Olivier Chapelle;Vikas Sindhwani;S. S. Keerthi

  • Emerging topic detection using dictionary learning

    Shiva Prasad Kasiviswanathan;Prem Melville;Arindam Banerjee;Vikas Sindhwani

  • Fast Conical Hull Algorithms for Near-separable Non-negative Matrix Factorization

    Abhishek Kumar;Vikas Sindhwani;Prabhanjan Kambadur

  • Deterministic annealing for semi-supervised kernel machines

    Vikas Sindhwani;S. Sathiya Keerthi;Olivier Chapelle

  • Quasi-Monte Carlo feature maps for shift-invariant kernels

    Haim Avron;Vikas Sindhwani;Jiyan Yang;Michael W. Mahoney

Frequent Co-Authors

Tara N. Sainath
Tara N. Sainath Google (United States)
Adrian Weller
Adrian Weller University of Cambridge
Partha Niyogi
Partha Niyogi University of Chicago
Jianying Hu
Jianying Hu IBM (United States)
Aleksandra Mojsilovic
Aleksandra Mojsilovic IBM (United States)
Marco Pavone
Marco Pavone Stanford University
Olivier Chapelle
Olivier Chapelle Google (United States)
Michael W. Mahoney
Michael W. Mahoney University of California, Berkeley
Berthold Reinwald
Berthold Reinwald IBM (United States)

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