Papers
A Log-Domain Implementation of the Diffusion Network in Very Large Scale Integration
Yi-da Wu, Shi-jie Lin, Hsin Chen
A Markov-Chain Monte Carlo Approach to Simultaneous Localization and Mapping
Peter Torma, András György, Csaba Szepesvári
A Molecular Algorithm for Path Self-Assembly in 3 Dimensions
R. Schulman and B. Yurke
An Alternative Prior Process for Nonparametric Bayesian Clustering
Hanna Wallach, Shane Jensen, Lee Dicker et al.
An Alternative to Low-level-Sychrony-Based Methods for Speech Detection
Javier R. Movellan, Paul L. Ruvolo
Analysis and Control of a Dissipative Spring-Mass Hopper with Torque Actuation
M. M. Ankarali and U. Saranli
An analysis on negative curvature induced by singularity in multi-layer neural-network learning
Eiji Mizutani, Stuart Dreyfus
An Approximate Inference Approach to Temporal Optimization in Optimal Control
Konrad Rawlik, Marc Toussaint, Sethu Vijayakumar
An Efficient Explanation of Individual Classifications using Game Theory
Erik Štrumbelj, Igor Kononenko
An EM Algorithm on BDDs with Order Encoding for Logic-based Probabilistic Models
Masakazu Ishihata, Yoshitaka Kameya, Taisuke Sato et al.
A New Probabilistic Model for Rank Aggregation
Tao Qin, Xiubo Geng, Tie-yan Liu
An Exponential Model for Infinite Rankings
Marina Meilă
An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA
Matthias Hein, Thomas Bühler
An Investigation of Missing Data Methods for Classification Trees Applied to Binary Response Data
Yufeng Ding, Jeffrey S. Simonoff
A Non-invasive Real-Time Method for Measuring Variable Stiffness
G. Grioli and A. Bicchi
A novel family of non-parametric cumulative based divergences for point processes
Sohan Seth, Park Il, Austin Brockmeier et al.
A Novel Kernel for Learning a Neuron Model from Spike Train Data
Nicholas Fisher, Arunava Banerjee
A POMDP Extension with Belief-dependent Rewards
Mauricio Araya, Olivier Buffet, Vincent Thomas et al.
A Potential-based Framework for Online Multi-class Learning with Partial Feedback
Shijun Wang, Rong Jin, Hamed Valizadegan
Approximate Inference by Compilation to Arithmetic Circuits
Daniel Lowd, Pedro Domingos
Approximate inference in continuous time Gaussian-Jump processes
Manfred Opper, Andreas Ruttor, Guido Sanguinetti
Approximate Inference on Planar Graphs using Loop Calculus and Belief Propagation
Vicenç Gómez, Hilbert J. Kappen, Michael Chertkov
Approximate parameter inference in a stochastic reaction-diffusion model
Andreas Ruttor, Manfred Opper
Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes
Antti Honkela, Tapani Raiko, Mikael Kuusela et al.