Reading Groups

Machine Learning & Statistics Reading Group

Weekly on Wednesdays 13:00-14:00

  • Classification Accuracy as a Proxy for Two Sample Testing (led by Yi Yu)
    https://arxiv.org/abs/1602.02210
    Wednesday 13th September 2017, 13:00-14:00
    Main Mathematics Building, Boardroom
  • Consistency of Random Forests (led by Patrick Rubin-Delanchy)
    https://arxiv.org/abs/1405.2881
    Wednesday 20th September 2017, 13:00-14:00
    Main Mathematics Building, Boardroom
  • The Mondrian Kernel (led by Sam Livingstone)
    https://arxiv.org/abs/1606.05241
    Wednesday 5th October 2017, 13:00-14:00
    Main Mathematics Building, Boardroom
  • Controlling the false discovery rate via knockoffs (led by Haeran Cho)
    https://projecteuclid.org/euclid.aos/1438606853
    https://statweb.stanford.edu/~candes/papers/MF_knockoffs.pdf
    Wednesday 11th October, 13:00-14:00
    Main Mathematics Building, Boardroom
  • Sparse precision matrix estimation (led by Yi Yu)
    – node wise regression https://arxiv.org/pdf/math/0608017.pdf
    – graphical lasso http://www.columbia.edu/~my2550/papers/graph.final.pdf
    – clime http://www-stat.wharton.upenn.edu/~tcai/paper/Precision-Matrix.pdf
    – adaptive clime https://arxiv.org/abs/1212.2882
    Wednesday 25th October, 13:00-14:00
    Main Mathematics Building, SM4
  • Learning the differences between two graphical models (led by Song Liu)
    Wednesday 8th November 2017, 13:00-14:00
    Main Mathematics Building, SM4
  • Decomposable graph laws (led by Peter Green)
    http://arxiv.org/abs/1705.00554
    Wednesday 15th November 2017, 13:00-14:00
    Main Mathematics Building, SM3
  • Feedforward neural networks and backpropagation (led by Patrick Rubin-Delanchy)
    https://www.nature.com/articles/nature14539
    30th November 2017, 13:00 – 14:00
    Main Maths Building, SM3
  • NIPS 2017 Report (led by Song Liu)
    13th December 2017, 13:00 – 14:00
    Main Maths Building, SM2
  • Signal-plus-noise matrix models: eigenvector deviations and fluctuations via the two-to-infinity norm with statistical applications (led by Joshua Cape)
    https://arxiv.org/abs/1705.10735; https://arxiv.org/abs/1802.00381https://arxiv.org/abs/1710.10936
    Wednesday 21st March 2018, 13:00-14:00
    Chemistry room E204
  • Topological Data Analysis Review (led by Patrick Rubin-Delanchy)
    https://www.annualreviews.org/doi/pdf/10.1146/annurev-statistics-031017-100045
    Wednesday 23rd May 2018, 13:00-14:00
    Howard House 4th Floor seminar room
  • Daniel Sussman (Boston University)
    Wednesday 20th June, 13:00-14:00, Howard House 4th Floor seminar room
    Title: Multiple Network Inference: From Joint Embeddings to Graph Matching
  • Topological Data Analysis II (led by Vinesh Solanki)
    Wednesday 11th July 2018, 13:00-14:00
    Venue TBC
  • Gaussian Processes and our lost friend the Factor Graph (led by Carl Henrik Ek)
    • Wednesday 17th October 2018, 14:00-15:00, Main Maths Building, PC2
    • Abstract:   A Gaussian process is a non-parametric stochastic process that defines a global covariance structure across an infinite input domain.  Defined by interpretable co-variance functions they provide flexible yet strong regularisation which facilitates learning from small amounts of data. In this talk I will first provide an introduction to Gaussian processes from a machine learning perspective, and show how efficient inference can be performed by formulating a bound on the marginal likelihood. I will then show recent work on combining Gaussian processes with Factor graphs with application in time series alignment and Bayesian optimisation.
  • High-dimensional Probability I (led by Yi Yu)
    • Wednesday 31st October 2018, 15.40-16.40
    • Tyndalls Park Rd 30-32.
  • High-dimensional Probability II (led by Tobias Kley)
    • Wednesday 14th November 2018, 15.40-16.40
    • Tyndalls Park Rd 30-32.
  • High-dimensional Probability III (led by Tobias Kley)
    • Wednesday 21th November 2018, 15.40-16.40
    • Tyndalls Park Rd 30-32.
  • High-dimensional Probability IV (led by Ayalvadi Ganesh)
    • Wednesday 30th January 2019, 12.00-13.00
    • Tyndalls Park Rd 30-32.
  • High-dimensional Probability V (led by Yi Yu)
    • Wednesday 6th February 2019, 12.00-13.00
    • 4th Floor Seminar Room, Howard House
  • High-dimensional Probability VI (led by Tobias Kley)
    • Wednesday 13th February 2019, 12.00-13.00
    • 2th Floor Seminar Room, Howard House
  • High-dimensional Probability VII (led by Vinesh Solanki)
    • Wednesday 20th February 2019, 12.00-13.00
    • 2th Floor Seminar Room, Howard House
  • High-dimensional Probability VIII (led by Yi Yu)
    • Wednesday 27th February 2019, 12.00-13.00
    • 2th Floor Seminar Room, Howard House
  • High-dimensional Probability IX (led by Yi Yu)
    • Wednesday 6th March 2019, 12.00-13.00
    • 2th Floor Seminar Room, Howard House
  • High-dimensional Probability X (led by Ayalvadi Ganesh)
    • Wednesday 13th March 2019, 12.00-13.00
    • 2th Floor Seminar Room, Howard House
  • High-dimensional Probability XI (led by Song Liu)
    • Wednesday 20th March 2019, 12.00-13.00
    • 2th Floor Seminar Room, Howard House

Monte Carlo Reading Group

Weekly on Thursdays 13:00-14:00

  • Week 7-10 Metastability and multi-modality (led by Mathieu Gerber)
  • Week 3-6: Non-reversible Markov chain methods (led by Christophe Andrieu and Samuel Livingstone)
  • Week 2: Transport Maps (led by Nick Whiteley)

Statistics and Probability Students Group

Fortnightly 14:00-15:00 in PC2

  • 3 November – EM algorithm (led by Kathryn Leeming)
  • 17 November – Connectivity in temporal networks with a non-uniform deployment of devices (led by Pete Pratt)
  • 1 December – LASSO (led by Bertrand Nortier)

css.php