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Advances in Neural Information Processing Systems 19
Graph-Based Visual Saliency
edited_book
Publication date:
2007
Publisher:
The MIT Press
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Recursive Rule based Visual Categorization
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Book Chapter
Publication date:
2007
DOI:
10.7551/mitpress/7503.003.0073
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c1af70d9-9464-4d9f-a116-e055d306309f
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Book chapters
Learning with Hypergraphs:Clustering, Classification, and Embedding
An Application of Reinforcement Learning to Aerobatic Helicopter Flight
Boosting Structured Prediction for Imitation Learning
Approximate inference using planar graph decomposition
Modeling Dyadic Data with Binary Latent Factors
Manifold Denoising
TrueSkill: A Bayesian Skill Rating System
A Kernel Method for the Two-Sample-Problem
Speakers optimize information density through syntactic reduction
Near-Uniform Sampling of Combinatorial Spaces Using XOR Constraints
Linearly-solvable Markov decision problems
Modeling Human Motion Using Binary Latent Variables
Learning to Rank with Nonsmooth Cost Functions
Differential Entropic Clustering of Multivariate Gaussians
Logarithmic Online Regret Bounds for Undiscounted Reinforcement Learning
Blind Motion Deblurring Using Image Statistics
Balanced Graph Matching
Learning from Multiple Sources
Large Margin Component Analysis
Modelling transcriptional regulation using Gaussian processes
Analysis of Representations for Domain Adaptation
Efficient sparse coding algorithms
Doubly Stochastic Normalization for Spectral Clustering
Correcting Sample Selection Bias by Unlabeled Data
N on-rigid point set registration: Coherent Point Drift
Efficient Learning of Sparse Representations with an Energy-Based Model
Graph-Based Visual Saliency
Greedy Layer-Wise Training of Deep Networks
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