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AI & Statistics 2014
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Models and Estimation

  • graphical models (inference, parameter and structure learning, ...)
  • causality
  • approximations to Bayesian reasoning (variational methods, message passing, ...)
  • Bayesian nonparametrics
  • Gaussian processes
  • other stochastic processes (Dirichlet, Pitman-Yor, ...)
  • Bayesian model combination
  • objective Bayesian methods
  • deep belief nets, deep RBMs
  • frequentist methods (maximum likelihood, ...)
  • statistical learning theory, computational learning theory
  • nonparametric models
  • kernel methods
  • large margin methods
  • boosting
  • ensemble methods
  • model selection, feature/variable selection
  • spectral methods
  • nonlinear embedding, manifold learning
  • matrix and tensor factorization
  • sparse estimation, compressed sensing
  • maximum entropy, minimum description length, compression, bottlenecks
  • asymptotics, consistency
  • information theory
  • information geometry
  • online learning

Problem types

Supervised learning

  • classification and regression
  • structured prediction
  • prediction with missing data
  • active learning, experimental design

Unsupervised and semi-supervised learning

  • density estimation
  • clustering
  • latent variable models (mixtures, topic models, PCA, ...)

Reasoning about complex structures

  • logic and probability
  • representation languages
  • relational/structured learning
  • learning on graphs
  • spatial models
  • time series and sequence models

Decision-making and control

  • decision theory
  • reinforcement learning
  • planning
  • control theory

Reasoning about multiple agents

  • game theory
  • no-regret learning
  • mechanism design
  • multi-agent systems

Algorithms and applications

Computation and algorithms

  • combinatorial optimization, search
  • convex optimization
  • gradient-based optimization
  • numerical integration and summation
  • Monte Carlo methods
  • parallel and distributed algorithms
  • high performance architectures (clusters, clouds, GPGPUs, ...)
  • large scale learning systems

Applications and software

  • biology and genomics
  • brain computer interfaces, brain imaging
  • cognitive science
  • collaborative filtering
  • economics
  • finance
  • informatics
  • information retrieval
  • linguistics, natural language processing
  • medical imaging
  • network data analysis
  • neuroscience
  • robotics
  • scientific data analysis
  • scientific visualization
  • signal processing
  • software packages
  • statistical databases
  • vision, image processing
  • the web