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NIPS
2004
14 years 29 days ago
Supervised Graph Inference
We formulate the problem of graph inference where part of the graph is known as a supervised learning problem, and propose an algorithm to solve it. The method involves the learni...
Jean-Philippe Vert, Yoshihiro Yamanishi
NIPS
2004
14 years 29 days ago
Synergies between Intrinsic and Synaptic Plasticity in Individual Model Neurons
This paper explores the computational consequences of simultaneous intrinsic and synaptic plasticity in individual model neurons. It proposes a new intrinsic plasticity mechanism ...
Jochen Triesch
NIPS
2004
14 years 29 days ago
Spike-timing Dependent Plasticity and Mutual Information Maximization for a Spiking Neuron Model
We derive an optimal learning rule in the sense of mutual information maximization for a spiking neuron model. Under the assumption of small fluctuations of the input, we find a s...
Taro Toyoizumi, Jean-Pascal Pfister, Kazuyuki Aiha...
NIPS
2004
14 years 29 days ago
Contextual Models for Object Detection Using Boosted Random Fields
We seek to both detect and segment objects in images. To exploit both local image data as well as contextual information, we introduce Boosted Random Fields (BRFs), which use boos...
Antonio Torralba, Kevin P. Murphy, William T. Free...
NIPS
2004
14 years 29 days ago
Heuristics for Ordering Cue Search in Decision Making
Simple lexicographic decision heuristics that consider cues one at a time in a particular order and stop searching for cues as soon as a decision can be made have been shown to be...
Peter M. Todd, Anja Dieckmann
NIPS
2004
14 years 29 days ago
Sharing Clusters among Related Groups: Hierarchical Dirichlet Processes
We propose the hierarchical Dirichlet process (HDP), a nonparametric Bayesian model for clustering problems involving multiple groups of data. Each group of data is modeled with a...
Yee Whye Teh, Michael I. Jordan, Matthew J. Beal, ...
NIPS
2004
14 years 29 days ago
Temporal-Difference Networks
Richard S. Sutton, Brian Tanner
NIPS
2004
14 years 29 days ago
Distributed Occlusion Reasoning for Tracking with Nonparametric Belief Propagation
We describe a three
Erik B. Sudderth, Michael I. Mandel, William T. Fr...
NIPS
2004
14 years 29 days ago
Constraining a Bayesian Model of Human Visual Speed Perception
It has been demonstrated that basic aspects of human visual motion perception are qualitatively consistent with a Bayesian estimation framework, where the prior probability distri...
Alan Stocker, Eero P. Simoncelli
NIPS
2004
14 years 29 days ago
Modelling Uncertainty in the Game of Go
Go is an ancient oriental game whose complexity has defeated attempts to automate it. We suggest using probability in a Bayesian sense to model the uncertainty arising from the va...
David H. Stern, Thore Graepel, David J. C. MacKay