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NIPS
2007
14 years 1 months ago
Learning the 2-D Topology of Images
Nicolas Le Roux, Yoshua Bengio, Pascal Lamblin, Ma...
NIPS
2007
14 years 1 months ago
Random Features for Large-Scale Kernel Machines
To accelerate the training of kernel machines, we propose to map the input data to a randomized low-dimensional feature space and then apply existing fast linear methods. The feat...
Ali Rahimi, Benjamin Recht
NIPS
2007
14 years 1 months ago
The Distribution Family of Similarity Distances
Assessing similarity between features is a key step in object recognition and scene categorization tasks. We argue that knowledge on the distribution of distances generated by sim...
Gertjan J. Burghouts, Arnold W. M. Smeulders, Jan-...
NIPS
2007
14 years 1 months ago
Theoretical Analysis of Learning with Reward-Modulated Spike-Timing-Dependent Plasticity
Reward-modulated spike-timing-dependent plasticity (STDP) has recently emerged as a candidate for a learning rule that could explain how local learning rules at single synapses su...
Robert A. Legenstein, Dejan Pecevski, Wolfgang Maa...
NIPS
2007
14 years 1 months ago
Spatial Latent Dirichlet Allocation
In recent years, the language model Latent Dirichlet Allocation (LDA), which clusters co-occurring words into topics, has been widely applied in the computer vision field. Howeve...
Xiaogang Wang, Eric Grimson
NIPS
2007
14 years 1 months ago
Feature Selection Methods for Improving Protein Structure Prediction with Rosetta
Rosetta is one of the leading algorithms for protein structure prediction today. It is a Monte Carlo energy minimization method requiring many random restarts to find structures ...
Ben Blum, Michael I. Jordan, David Kim, Rhiju Das,...
NIPS
2007
14 years 1 months ago
Non-parametric Modeling of Partially Ranked Data
Statistical models on full and partial rankings of n items are often of limited practical use for large n due to computational consideration. We explore the use of non-parametric ...
Guy Lebanon, Yi Mao
NIPS
2007
14 years 1 months ago
A Randomized Algorithm for Large Scale Support Vector Learning
This paper investigates the application of randomized algorithms for large scale SVM learning. The key contribution of the paper is to show that, by using ideas random projections...
Krishnan Kumar, Chiru Bhattacharyya, Ramesh Hariha...
NIPS
2007
14 years 1 months ago
Nearest-Neighbor-Based Active Learning for Rare Category Detection
Rare category detection is an open challenge for active learning, especially in the de-novo case (no labeled examples), but of significant practical importance for data mining - ...
Jingrui He, Jaime G. Carbonell
NIPS
2007
14 years 1 months ago
A Bayesian Framework for Cross-Situational Word-Learning
Michael Frank, Noah Goodman, Joshua B. Tenenbaum