Statistics

• Readings from Christian Robert's seminar on classic statistics papers could be fun! List is here: https://www.ceremade.dauphine.fr/~xian/M2classics.html
• Asymptotic statistics --- van der Vaart
• Lasso, ARS, sparsity
• Approximate Bayesian Computation
• 9 Great Statistics papers published after 1970 from Rob Tibshirani: http://normaldeviate.wordpress.com/2012/12/21/guest-post-rob-tibshirani/
• Blog post on 5 most influential statistics papers of 2000-2010 with various people's suggestions: http://simplystatistics.org/2013/07/22/what-are-the-5-most-influential-statistics-papers-of-2000-2010/

Nonparametrics (Bayesian and otherwise)

• Bayesian nonparametric --- Nils Hjort edited book
• All of nonparametric statistics
• Gaussian processes
• Something about with kernels

Inference

• Variational Inference in Nonconjugate Models
• Nonparametric Bayes particle filtering
• Sequential monte carlo

Optimisation

• Nesterov acceleration
• ADMM (e.g., Foundations and Trends book)
• SGD papers
• SGD: Xiao, L., & Zhang, T. (2014). A proximal stochastic gradient method
  > with progressive variance reduction. SIOPT, 24(4), 2057-2075.
  > http://epubs.siam.org/doi/abs/10.1137/140961791
• SGD: Duchi, J. C., Bartlett, P. L., & Wainwright, M. J. (2012).
  > Randomized smoothing for stochastic optimization. SIOPT, 22(2),
  > 674-701.
  > http://epubs.siam.org/doi/abs/10.1137/110831659
  >

Scaling

• leskovic et al mining massive data sets. http://www.mmds.org/#book
• Papers on locality sensitive hashhing http://www.mit.edu/~andoni/LSH/
• Papers on Spark
• Several streaming inference papers from this past NIPS

Machine learning

• Taskar stuff with DPPs

Neural networks

• Batch Normalization: Accelerating Deep Network Training by Reducing
  Internal Covariate Shift
  Sergey Ioffe, Christian Szegedy
  http://arxiv.org/abs/1502.03167

-- CharlesSutton - 07 Nov 2013