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NIPS
2004
9 years 12 months ago
Adaptive Manifold Learning
Recently, there have been several advances in the machine learning and pattern recognition communities for developing manifold learning algorithms to construct nonlinear low-dimen...
Jing Wang, Zhenyue Zhang, Hongyuan Zha
NIPS
2004
9 years 12 months ago
Identifying Protein-Protein Interaction Sites on a Genome-Wide Scale
Protein interactions typically arise from a physical interaction of one or more small sites on the surface of the two proteins. Identifying these sites is very important for drug ...
Haidong Wang, Eran Segal, Asa Ben-Hur, Daphne Koll...
NIPS
2004
9 years 12 months ago
Instance-Specific Bayesian Model Averaging for Classification
Classification algorithms typically induce population-wide models that are trained to perform well on average on expected future instances. We introduce a Bayesian framework for l...
Shyam Visweswaran, Gregory F. Cooper
NIPS
2004
9 years 12 months ago
Binet-Cauchy Kernels
We propose a family of kernels based on the Binet-Cauchy theorem and its extension to Fredholm operators. This includes as special cases all currently known kernels derived from t...
S. V. N. Vishwanathan, Alex J. Smola
NIPS
2004
9 years 12 months 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
9 years 12 months 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
9 years 12 months 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
9 years 12 months 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
9 years 12 months 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
9 years 12 months 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, ...
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