conftrace_
← Core Methods
Machine Learning › Core Methods ›

Representation Learning

20,822 papers

Papers per year

2
9
101
309
2011
2283
'00
'05
'10
'15
'20
'25

Papers

A Brain-Machine Interface Operating with a Real-Time Spiking Neural Network Control Algorithm NIPS 2011
Understanding the Intrinsic Memorability of Images NIPS 2011
Two is better than one: distinct roles for familiarity and recollection in retrieving palimpsest memories NIPS 2011
Structure Learning for Optimization NIPS 2011
Testing a Bayesian Measure of Representativeness Using a Large Image Database NIPS 2011
Dimensionality Reduction Using the Sparse Linear Model NIPS 2011
Data Skeletonization via Reeb Graphs NIPS 2011
Learning Sparse Representations of High Dimensional Data on Large Scale Dictionaries NIPS 2011
A Non-Parametric Approach to Dynamic Programming NIPS 2011
Kernel Bayes' Rule NIPS 2011
Divide-and-Conquer Matrix Factorization NIPS 2011
Bayesian Spike-Triggered Covariance Analysis NIPS 2011
Similarity-based Learning via Data Driven Embeddings NIPS 2011
Maximum Margin Multi-Label Structured Prediction NIPS 2011
Selecting Receptive Fields in Deep Networks NIPS 2011
Multi-View Learning of Word Embeddings via CCA NIPS 2011
Signal Estimation Under Random Time-Warpings and Nonlinear Signal Alignment NIPS 2011
Sequence learning with hidden units in spiking neural networks NIPS 2011
Learning in Hilbert vs. Banach Spaces: A Measure Embedding Viewpoint NIPS 2011
Nonnegative dictionary learning in the exponential noise model for adaptive music signal representation NIPS 2011
Generalised Coupled Tensor Factorisation NIPS 2011
Portmanteau Vocabularies for Multi-Cue Image Representation NIPS 2011
Efficient anomaly detection using bipartite k-NN graphs NIPS 2011
Select and Sample - A Model of Efficient Neural Inference and Learning NIPS 2011
On Learning Discrete Graphical Models using Greedy Methods NIPS 2011