Publications

Conferences :

  1. Peter Henderson*, Riashat Islam*, Philip Bachman, Joelle Pineau, Doina Precup, David Meger. “Deep Reinforcement Learning that Matters”.  AAAI 2018 (Paper)
  2. David Krueger*, Chin-Wei Huang*, Riashat Islam, Ryan TurnerAaron Courville. “Bayesian Hypernets”.  Under review in ICLR 2018 (Paper)
  3. Maziar Gomrokchi, Susan Amin, Riashat Islam, Doina Precup. “Persistence Length-Based Exploration in Deep Reinforcement Learning”. In Submission, 2017 
  4. Yarin Gal, Riashat Islam, Zoubin Ghahramani. “Deep Bayesian Active Learning with Image Data”. ICML 2017 (Paper | Code | Poster | Slides) 


Workshops :

  1. David Krueger, Chin-Wei Huang, Riashat Islam, Ryan Turner, Alexandre Lacoste and Aaron Courville. “Bayesian Hypernetworks”.
    Bayesian Deep Learning workshop NIPS 2017
  2. Peter Henderson, Thang Doan, Riashat Islam and David Meger.
    “Bayesian Policy Gradients via Alpha-Divergence Dropout Inference”.
    Bayesian Deep Learning workshop, NIPS 2017
  3. Riashat Islam*, Peter Henderson*, Maziar Gomrokchi, Doina Precup. “Reprodicibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control”. Reproducibility in Machine Learning workshop, ICML 2017 (Paper | Poster)
  4. Riashat Islam*, Peter Henderson*, Doina Precup.
    Contributed talk at Reinforcement Learning workshop, ICML 2017 (Slides)
  5. Maziar Gomrokchi, Susan Amin, Riashat Islam, Doina Precup. “Using Locally Self-Avoiding Random Walks for Exploration in Reinforcement Learning”. RLDM 2017
  6. Yarin Gal, Riashat Islam, Zoubin Ghahramani. “Active Learning with Image Data”. Bayesian Deep Learning workshop, NIPS 2016 (Paper | Poster)

Preprints :

  1. Bogdan Mazoure*, Riashat Islam*. “Alpha-Divergences in Variational Dropout” arxiv preprint (Paper)

Profile :


Google Scholar Profile

DBLP Profile

Arxiv

 

Conferences and Paper Reviewing :

  1. (NIPS 2017 Workshop) Bayesian Deep Learning 

 

Thesis :

  1. Riashat Islam, Yarin Gal, Zoubin Ghahramani. “Active Learning Image Data using Uncertainty in Deep Learning”. Masters Thesis, University of Cambridge, 2016 (Thesis | Poster | Code)
  2. Riashat Islam, Guy Lever, John Shawe-Taylor. “Improving Convergence of Deterministic Policy Gradient Methods in Reinforcement Learning”. Undergraduate Thesis, University College London, 2015 (Thesis | Code)

 

Others :

  1. Riashat Islam*, Peter Henderson*, Maziar Gomrokchi, Doina Precup. “Reproducibility of Benchmarked Deep Reinforcement Learning Tasks for Continuous Control”, Montreal AI Symposium, 2017


Other Notes (Unpublished) :

  1. Deterministic Intra-Option Policy Gradient Theorem (Report)
  2. Option Critic in Reproducing Kernel Hilbert Space (Report)

 

Technical Reports/Projects :

  1. Riashat Islam. “Exploration in Continuous Control Reinforcement Learning” (Slides)
  2. Riashat Islam, Catherine McGhan, Richard Murray. “Improved State Estimation and Control for Resilient Spacecraft Executive”.  SURF 2017, Caltech and NASA JPL (Report | Slides)
  3. Riashat Islam. “Large Vocabulary Speech Recognition” (Report)
  4. Riashat Islam. “Speech Recognition with GMM-HMMs” (Report)
  5. Riashat Islam, Jiameng Gao, Vera Johne. “Unifying Review of Variational Inference and Learning using Deep Directed Latent Variable Models” (Report | Poster)
  6. Riashat Islam. “Keyword Spotting” (Report)
  7. Riashat Islam. “Statistical Machine Translation” (Slides)
  8. Riashat Islam. “Reinforcement Learning for Spoken Dialogue Systems” (Report)
  9. Riashat Islam. “Basic Algorithms in Reinforcement Learning” (Report)
  10. Riashat Islam. “Playing Blackjack with Reinforcement Learning” (Report)
  11. Riashat Islam. “Cost-Sensitive Decision Tree Classifiers” (Report)
  12. Riashat Islam. “Gaussian Processes” (Report)
  13. Riashat Islam. “Weighted Automata using OpenFST” (Report)
  14. Riashat Islam. “Statistical Speech Synthesis” (Report)