All Talks

  • Tensorly: A Flexible Python Framework for Machine Learning

    PyData LA 2018, Nov. 2018

  • Large-scale ML: Deep, Distributed and Multi-Dimensional

    AI Frontiers 2018, Nov. 2018

  • QS

    Trinity of AI

    TEDx at Indiana University, October 2018

    slides
  • QS

    Opportunities for Infusing Physics in AI/ML Algorithms

    Physics Next Workshops, October 2018

    slides
  • QS

    Some Success Stories in Bridging Theory and Practice

    Georgia Institute of Technology, October 2018

    slides
  • The AI Trinity: Data + Algorithms + Infrastructure

    NYU Tandon School of Engineering, October 2018

    slides
  • QS

    Applied ML Research Snippets

    PyTorch Developer Conference, October 2018

    slides
  • The AI Trinity: Data + Algorithms + Infrastructure

    Simons Institute Open Lecture Series, October 2018

  • QS

    Tackling Data Scarcity in Deep Learning

    The Conference on Uncertainty in Artificial Intelligence (UAI), August 2018

    slides(part1)  slides(part2)
  • QS

    AI: present and future

    QS investors Caltech innovator series, June 2018

  • Building the next generation of AI

    Particle Design, May 2018

  • Role of Tensors in Large-Scale Machine Learning

    Matroid Scaled Machine Learning Conference, March 2018

  • Global Governance of AI Roundtable

    World Government Summit, March 2018

  • Robots Get Humanlike Brains With Machine Learning and A.I.

    DavidNazarNews, Dec. 2017

  • Leaning at Scale: Deep, Distributed and Multi-dimensional

    MLconf, Nov. 2017

  • Tensors for Large-scale Topic Modeling and Deep Learning

    AWS re:Invent, Nov. 2017

  • Talk in Silicon Valley Future Forum

    Silicon Valley Future Forum, Aug. 2017

  • Tutorial on distributed deep learning using apache mxnet: part 1

    Strata Data Conference, July 2017

  • Tutorial on distributed deep learning using apache mxnet: part 2

    Strata Data Conference, July 2017

  • Distributed deep learning on AWS using apache mxnet

    Strata Data Conference, July 2017

  • Short interview in IIT Bay Area Leadership Conf

    IIT Bay Area Leadership Conf,July 2017

  • Panel discussion: Artificial Intelligence

    IIT Bay Area Leadership Conference, June 2017

  • Efficient Distributed Deep Learning Using MXNet

    Simons Institute, May 2017

  • Panel discussion on "AI and its impact on job"

    IITM alumni meeting, April 2017

  • Distributed Deep Learning

    Anita Borg Institute, Feb. 2017

  • ICML 2016 Tutorial

    Recent Advances in Non-Convex Optimization

    ICML 2016 Tutorial, June 2016 slides

  • ICLR 2016

    Guaranteed Non-convex Learning Algorithms through Tensor Factorization

    ICLR 2016, May 2016

  • Tensor Methods for Large-Scale Machine Learning

    Southern California Machine Learning Symposium, May 2016

  • NIPS 2015 Workshop on Nonconvex Optimization

    Dec. 2015 slides

  • Tensor Methods - A New Paradigm for Training Probabilistic Models, Neural Networks and Reinforcement Learning

    MLConf at SF, Nov. 2015

  • O'Reilly Podcast

    The tensor renaissance in data science

    The O'Reilly Data Show Podcast, July 2015

  • COLT 2015

    Learning Overcomplete Latent Variable Models through Tensor Methods

    COLT 2015, July 2015

  • Tensor Methods: A New Paradigm for Training Probabilistic Models and Feature Learning

    MLconf , May 2015

  • Constructing Informative Features for Discriminative Learning

    Simons Institute, March 2015 slides

  • Tensor methods for largescale unsupervised learning applications to topic and community modeling

    Strata at the Hardcore Data Science Track, March 2015

  • Tackling Big Data with Tensor Methods

    Data Science Initiative, Dec. 2014

  • Tensor Methods for Learning Latent Variable Models: Theory and Practice

    Simons Institute, Nov. 2014

  • Guaranteed Learning of Latent Variable Models: Overlapping Community Models and Overcomplete

    University of Washington, Feb. 2014

  • Robust PCA via Non-convex Methods: Provable Bounds

    Joint work with Praneeth Netrapalli, U. N. Niranjan, Prateek Jain and Sujay Sanghavi slides

  • Machine Learning Summer School 2014, Pittsburgh

    youtube 1 youtube 2 youtube 3 slides 1 slides 2 slides 3

  • Tensor Methods for Learning Latent Variable Models: Theory and Practice

    Simons Institute slides

  • NIPS 2011

    High-Dimensional Graphical Model Selection

    Joint work with Vincent Tan (U. Wisc.) and Allay Willsky (MIT)

  • Fast and Guaranteed Learning of Overlapping Communities via Tensor Methods

    Cornell CAM Colloquium, Sept. 2013

  • A Tensor Spectral Approach to Learning Mixed Membership Community Models

    NC State ECE, May 2013

  • A Tensor Spectral Approach to Learning Mixed Membership Community Models

    Joint work with Rong Ge (Princeton), Daniel Hsu (Microsoft Research), Sham Kakade (Microsoft Research)