Poster session information will become available in the future.
A Collapsed Variational Bayesian Inference Algorithm for Latent Dirichlet Allocation
Yee Whye Teh ⋅ David Newman ⋅ Max Welling
An Information Theoretic Framework for Eukaryotic Gradient Sensing
Joseph Kimmel ⋅ Richard Salter ⋅ Peter Thomas
A Nonparametric Approach to Bottom-Up Visual Saliency
Wolf Kienzle ⋅ Felix A Wichmann ⋅ Bernhard Schölkopf ⋅ Matthias Franz
A Nonparametric Bayesian Method for Inferring Features From Similarity Judgments
Daniel Navarro ⋅ Tom Griffiths
A Probabilistic Algorithm Integrating Source Localization and Noise Suppression for MEG and EEG data
Johanna M Zumer ⋅ Hagai Attias ⋅ Kensuke Sekihara ⋅ Srikantan Nagarajan
Attentional Processing on a Spike-Based VLSI Neural Network
Yingxue Wang ⋅ Rodney J Douglas ⋅ Shih-Chii Liu
Attribute-efficient learning of linear threshold functions under unconcentrated distributions
Phil Long ⋅ Rocco A Servedio
Automated Hierarchy Discovery for Planning in Partially Observable Domains
Laurent Charlin ⋅ Pascal Poupart ⋅ Romy Shioda
Branch and Bound for Semi-Supervised Support Vector Machines
Olivier Chapelle ⋅ Vikas Sindhwani ⋅ Sathiya Selvaraj Keerthi
Comparative Gene Prediction using Conditional Random Fields
Jade P Vinson ⋅ David DeCaprio ⋅ Stacey Luoma ⋅ James Galagan
Conditional Random Sampling: A Sketch-based Sampling Technique for Sparse Data
Ping Li ⋅ Kenneth W Church ⋅ Trevor Hastie
Context Effects in Category Learning: An Investigation of Four Probabilistic Models
Michael Mozer ⋅ Michael Jones ⋅ Michael Shettel
Distributed Inference in Dynamical Systems
Stanislav Funiak ⋅ Carlos Guestrin ⋅ Mark A Paskin ⋅ Rahul Sukthankar
Efficient sparse coding algorithms, end-stopping and nCRF surround suppression
Honglak Lee ⋅ Alexis Battle ⋅ Raina Rajat ⋅ Andrew Y Ng
Efficient Structure Learning of Markov Networks using L1-Regularization
Su-In Lee ⋅ Varun Ganapathi ⋅ Daphne Koller
Estimating Observation Functions in Dynamical Systems Using Unsupervised Regression
ali rahimi ⋅ Benjamin Recht
Gaussian Process Models for Discriminative Link Prediction
Kai Yu ⋅ Wei Chu ⋅ Shipeng Yu ⋅ Volker Tresp ⋅ Zhao Xu
Graph Regularization for Maximum Variance Unfolding with an Application to Sensor Localization
Kilian Q Weinberger ⋅ Fei Sha ⋅ Qihui Zhu ⋅ Lawrence Saul
iLSTD: Convergence, Eligibility Traces, and Mountain Car
Alborz Geramifard ⋅ Michael Bowling ⋅ Martin A Zinkevich ⋅ Richard Sutton
Image Retrieval and Classification Using Local Distance Functions
Andrea Frome ⋅ Yoram Singer ⋅ Jitendra Malik
implicit Online Learning with Kernels
Li Cheng ⋅ Vishwanathan S V N ⋅ Dale Schuurmans ⋅ Shaojun Wang ⋅ Terry Caelli
Kernel Maximum Entropy Data Transformation and an Enhanced Spectral Clustering Algorithm
Robert Jenssen ⋅ Torbjorn Eltoft ⋅ Mark A Girolami ⋅ Deniz Erdogmus
Large Margin Multi-channel Analog-to-Digital Conversion with Applications to Neural P
Amit Gore ⋅ Shantanu Chakrabartty
Learning Nonparametric Models for Probabilistic Imitation
David Grimes ⋅ Daniel Rashid ⋅ Rajesh PN Rao
Learning with Hypergraphs: Clustering, Classification, and Embedding
Denny Zhou ⋅ Jiayuan Huang ⋅ Bernhard Schölkopf
Multi-Robot Negotiation: Approximating the Set of Subgame Perfect Equilibria in General Sum Stochastic Games
Chris D Murray ⋅ Geoffrey Gordon
Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints
Carla Gomes ⋅ Ashish Sabharwal ⋅ Bart Selman
Randomized PCA Algorithms with Regret Bounds that are Logarithmic in the Dimension
Manfred K. Warmuth ⋅ Dima Kuzmin
Training Conditional Random Fields for Maximum Parse Accuracy
Samuel Gross ⋅ Olga Russakovsky ⋅ Chuong B Do ⋅ Serafim Batzoglou