Organizer: Wojtek Czaja (Math), Tom Goldstein (CS), and Matt Guay (NIBIB/NIH)
When: Fridays @ 12 noon
Where:
Kirwan Hall 3206
Description: The RIT treats various topics in machine learning and computer vision, particularly focusing on deep neural networks. Everyone who is interested is encouraged to attend. We will hold one or two introductory talks on Deep Learning to kick off the semester. As the semester unfolds we will have participants volunteer to give talks about papers of interest or their own research in the field.

Archives: 2011 | 2012 | 2013 | 2014 | 2015 | 2016 | 2017 | 2018

  • Organizational Meeting

    Speaker: Organizational Meeting () -

    When: Fri, September 1, 2017 - 12:00pm
    Where: Kirwan Hall 1311
  • Introduction to Deep Learning

    Speaker: Ilya Kavalerov (UMD) -

    When: Fri, September 8, 2017 - 12:00pm
    Where: Kirwan Hall 1311
  • Introduction to Convolutional Neural Networks

    Speaker: Shujie Kang (UMD) -

    When: Fri, September 15, 2017 - 12:00pm
    Where: Kirwan Hall 3206
  • Training a Convolutional Neural Network

    Speaker: Shujie Kang (UMD) -

    When: Fri, September 29, 2017 - 12:00pm
    Where: Kirwan Hall 3206
  • A closer look at the ADAM optimizer

    Speaker: Eric Oden (UMD) -

    When: Fri, October 6, 2017 - 12:00pm
    Where: Kirwan Hall 3206
  • Reinforcement learning and Trust Region Policy Optimization

    Speaker: Cheng Jie (UMD) -

    When: Fri, October 13, 2017 - 12:00pm
    Where: Kirwan Hall 3206
  • Actor-Critic Method

    Speaker: Nathaniel Monsoon (UMD) -

    When: Fri, October 20, 2017 - 12:00pm
    Where: Kirwan Hall 3206
  • Analysis of Convergence of Back-Propagation

    Speaker: Andrew Lauziere (UMD) -

    When: Fri, October 27, 2017 - 12:00pm
    Where: Kirwan Hall 3206
  • Batch Training of Neural Networks

    Speaker: Roozbeh Yousefzadeh (UMD (CS)) -

    When: Fri, November 10, 2017 - 12:00pm
    Where: Kirwan Hall 3206
  • A Proof of Convergence For The Stochastic Gradient Descent Method on Convex Cost Functions

    Speaker: Daniel Mourad (UMD) -

    When: Fri, November 17, 2017 - 12:00pm
    Where: Kirwan Hall 3206
  • Optimization methods for discrete and saddle-point problems in machine learning

    Speaker: Tom Goldstein (UMD/CS) - https://www.cs.umd.edu/~tomg/

    When: Fri, December 1, 2017 - 12:00pm
    Where: Kirwan Hall 3206
  • Mathematics in Machine Learning: Present and Future

    Speaker: Wojtek Czaja (UMD (math)) -

    When: Fri, December 8, 2017 - 12:00pm
    Where: Kirwan Hall 3206
  • NeuroEvolution of Augmenting Topologies (NEAT): A Genetic Algorithm for Neural Networks

    Speaker: Brandon Alexander (UMD) -

    When: Wed, February 7, 2018 - 10:00am
    Where: Kirwan Hall 3206
  • Training Quantized Nets: A Deeper Understanding

    Speaker: Liam Fowl (UMD) -

    When: Thu, February 22, 2018 - 10:00am
    Where: Kirwan Hall 3206
  • Training Neural Networks Without Gradients: A Scalable ADMM Approach

    Speaker: Zeyad Emam (UMD) -

    When: Thu, March 1, 2018 - 10:00am
    Where: Kirwan Hall 3206
  • Spectral Networks and Locally Connected Networks on Graphs

    Speaker: Addison Bohannon (UMD) -

    When: Thu, March 8, 2018 - 10:00am
    Where: Kirwan Hall 3206
  • FiLM: Visual Reasoning with a General Conditioning Layer

    Speaker: Matthew Guay (NIH/NIBIB) -

    When: Thu, March 15, 2018 - 10:00am
    Where: Kirwan Hall 3206
  • Mallat’s scattering transform, the Fourier scattering transform, and applications in hyperspectral imagery

    Speaker: Ilya Kavarelov (UMD (ECE)) -

    When: Thu, March 29, 2018 - 10:00am
    Where: Kirwan Hall 3206
  • Transforming machine learning heuristics into provable algorithms: classical, stochastic, and neural

    Speaker: Cheng Tang (GWU) - https://sites.google.com/site/chengtanggwu/

    When: Thu, April 5, 2018 - 10:00am
    Where: CHM 0115
  • How non-convex are neural net loss functions, and what do they look like?

    Speaker: Thomas Goldstein (UMD (UMIACS)) - https://www.cs.umd.edu/~tomg/

    When: Thu, April 12, 2018 - 10:00am
    Where: Kirwan Hall 3206
  • Deep Learning - now and the future, an overview

    Speaker: James Yorke (UMD ) - http://www.chaos.umd.edu/~yorke/

    When: Thu, April 19, 2018 - 10:00am
    Where: Kirwan Hall 3206
  • Accelerated Gradient Descent Escapes Saddle Points Faster than Gradient Descent

    Speaker: Wojtek Czaja (UMD (MATH)) -

    When: Thu, May 3, 2018 - 10:00am
    Where: Kirwan Hall 3206