NIPS papers by title-- my selection

My selection (solely based on the title) grouped according to my inference about their content. I will look at the abstracts soon (hopefully), and then look at some of these more carefully.

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# Modeling the effects of memory on human online sentence processing with particle filters
R. Levy, F. Reali, T. Griffiths
# Analyzing human feature learning as nonparametric Bayesian inference
J. Austerweil, T. Griffiths
# An ideal observer model of infant object perception
C. Kemp, F. Xu
# A rational model of preference learning and choice prediction by children
C. Lucas, T. Griffiths, F. Xu, C. Fawcett

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# One sketch for all: Theory and Application of Conditional Random Sampling
P. Li, K. Church, T. Hastie
# Bounds on marginal probability distributions
J. Mooij, H. Kappen
# Rademacher Complexity Bounds for Non-I.I.D. Processes
M. Mohri, A. Rostamizadeh
# Domain Adaptation with Multiple Sources
Y. Mansour, M. Mohri, A. Rostamizadeh
# Comparing model predictions of response bias and variance in cue combination
R. Natarajan, I. Murray, L. Shams, R. Zemel
# Beyond Novelty Detection: Incongruent Events, when General and Specific Classifiers Disagree
D. Weinshall, H. Hermansky, A. Zweig, J. Luo, H. Jimison, F. Ohl, M. Pavel
# Accelerating Bayesian Inference over Nonlinear Differential Equations with Gaussian Processes
B. Calderhead, M. Girolami, N. Lawrence
# Generative and Discriminative Learning with Unknown Labeling Bias
M. Dudik, S. Phillips

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# Relative Performance Guarantees for Approximate Inference in Latent Dirichlet Allocation
I. Mukherjee, D. Blei
# Learning Taxonomies by Dependence Maximization
M. Blaschko, A. Gretton
# DiscLDA: Discriminative Learning for Dimensionality Reduction and Classification
S. Lacoste-Julien, F. Sha, M. Jordan
# Deflation Methods for Sparse PCA
L. Mackey
# Bayesian Exponential Family PCA
S. Mohamed, K. Heller, Z. Ghahramani

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# SDL: Supervised Dictionary Learning
J. Mairal, F. Bach, J. Ponce, G. Sapiro, A. Zisserman
# Cascaded Classification Models: Combining Models for Holistic Scene Understanding
G. Heitz, S. Gould, A. Saxena, D. Koller
# A "Shape Aware" Model for semi-supervised Learning of Objects and its Context
A. Gupta, J. Shi, L. Davis