Jordan_M: 73 documents, from the least to the most
probable paper
Perplexity score: Contribution score: Title
1609.849502 -0.542 An Orthogonally Persistent
Java
1386.694577 -0.471 Link Analysis, Eigenvectors and
Stability
1385.962008 -0.572 Software Configuration Management
in an Object Oriented Database
1337.010276 -0.264 Perceptual Distortion Contributes
to the Curvature of Human Reaching Movements
1319.155159 -0.196 Are arm trajectories planned in
kinematic or dynamic coordinates? An adaptation study
1218.513983
- Early
Experiences with Persistent Java
1175.728822 -0.210 On Discriminative vs. Generative
classifiers: A comparison of logistic regression and naive Bayes
1098.836939 -0.145 Computational structure of
coordinate transformations: A generalization study
1082.466010 -0.245 Orthogonal Persistence for Java -
A Mid-term Report
1065.512168 -0.267 Triangulation by Continuous
Embedding
1038.933083 -0.439 Defining and Handling Transient
Fields in PJama
836.780746
0.084 Latent Dirichlet
Allocation
821.360414
-0.184 Convergence
rates of the Voting Gibbs classifier, with application to Bayesian feature
selection
793.245979 -0.048 Thin Junction Trees
784.000880 -1.000 The Modula-3 Type System
756.378756 -0.225 On Spectral Clustering: Analysis
and an algorithm
724.958745
-0.353 Stable
Algorithms for Link Analysis
666.679995
-0.310 PEGASUS: A
policy search method for large MDPs and POMDPs
601.597267 -0.214 Kernel Independent Component
Analysis
583.962497 -0.155 Variational MCMC
583.962497 -0.238 Variational MCMC
576.252888 -0.200 Computational Models of
Sensorimotor Integration
576.252888
-0.193 Computational
Models of Sensorimotor Integration
517.364447 -0.168 Variational methods and the QMR-DT
database
496.093502 -0.228 Local Linear Perceptrons for
Classification
494.914451
0.005 Learning in
Boltzmann Trees
483.993843
-0.118 Hidden Markov
decision trees
483.468058
-0.114 Triangulation
by Continuous Embedding
483.281600
-0.196 Convergence of
Stochastic Iterative Dynamic Programming Algorithms
471.430985 -0.139 Mean Field Theory for Sigmoid
Belief Networks
444.566717
-0.236 Probabilistic
Independence Networks for Hidden Markov Probability Models
434.069940 0.110 Computing upper and lower bounds
on likelihoods in intractable networks
427.708955 -0.103 Learning Without State-Estimation
in Partially Observable Markovian Decision Processes
419.485437 0.404 Probabilistic Independence
Networks for Hidden Markov Probability Models
417.586009 -0.203 Reinforcement Learning with Soft
State Aggregation
411.912723
-0.014 Estimating
Dependency Structure as a Hidden Variable
402.596728 -0.176 Loopy Belief Propagation for
Approximate Inference: An Empirical Study
401.258514 -0.224 Mean Field Theory for Sigmoid
Belief Networks
395.573789
0.089 Hidden Markov
decision trees
387.912488
0.090 Learning Fine
Motion by Markov Mixtures of Experts
380.726791 -0.065 On the Convergence of Stochastic
Iterative Dynamic Programming Algorithms
372.392604 -0.207 Attractor Dynamics in Feedforward
Neural Networks
363.836248
-0.019 Mixture
Representations for Inference and Learning in Boltzmann Machines
329.074444 -0.213 Approximating Posterior
Distributions in Belief Networks using Mixtures
328.369863 -0.052 Improving the Mean Field
Approximation via the Use of Mixture Distributions
327.343189 -0.133 Reinforcement Learning Algorithm
for Partially Observable Markov Decision Problems
326.949906 0.348 Hierarchical mixtures of experts
and the EM algorithm
321.149847
0.086 Estimating
Dependency Structure as a Hidden Variable
311.282332 -0.064 Exploiting Tractable Substructures
in Intractable Networks
302.054298
0.009 Learning with
Mixtures of Trees
301.675730
-0.061 Convergence
results for the EM approach to mixtures of experts architectures
296.674091 -0.260 Active Learning with Statistical
Models
294.232003 0.487 Active Learning with Statistical
Models
291.959706 -0.253 Variational Probabilistic
Inference and the QMR-DT Network
288.718219
-0.072 Factorial
Hidden Markov Models
280.193320
0.020 A Mean Field
Learning Algorithm For Unsupervised Neural Networks
265.909809 -0.075 Factorial Hidden Markov
Models
261.263839 0.360 Neural Networks
251.228796 -0.185 Convergence study and improvement
of variational methods with MCMC
250.996174
-0.119 Bayesian
parameter estimation via variational methods
250.469224 -0.144 Active Learning with Statistical
Models
244.360996 0.066 Convergence results for the EM
approach to mixtures of experts architectures
238.395076 0.059 Reinforcement Learning by
Probability Matching
229.424767
-0.140 A variational
approach to Bayesian logistic regression models and their extensions
218.493626 -0.222 Bayesian parameter estimation
through variational methods
214.843671
0.346 Learning From
Incomplete Data
214.551533
- A
Statistical Approach to Decision Tree Modeling
212.504398 0.087 Estimating Dependency Structure as
a Hidden Variable
205.916077
-0.192 A variational
approach to Bayesian logistic regression models and their extensions
198.780343 -0.036 Factorial hidden Markov
models
191.069825 0.320 Factorial Hidden Markov
Models
180.020788 -0.236 On Convergence Properties of the
EM Algorithm for Gaussian Mixtures
178.966371 -0.110 Supervised learning from
incomplete data via an EM approach