2013
Diffusion Maps for Signal Processing: A Deeper Look at Manifold-Learning Techniques Based on Kernels and Graphs
Talmon R, Cohen I, Gannot S, Coifman R. Diffusion Maps for Signal Processing: A Deeper Look at Manifold-Learning Techniques Based on Kernels and Graphs. IEEE Signal Processing Magazine 2013, 30: 75-86. DOI: 10.1109/msp.2013.2250353.Peer-Reviewed Original ResearchParametric statistical inferenceDigital signal processing systemsMachine-learning approachesKernel-based methodsSignal processingManifold learning techniquesComputational capabilitiesSignal processing systemGraphical modelsStatistical inferenceMore computationSignal processing methodsBayesian networkDSP systemsEfficient algorithmProcessing systemComputational burdenLinear filterDiffusion mapsAlgorithmProcessing methodsTraditional methodsProcessingNetworkGraph
1995
On local orthonormal bases for classification and regression
Saito N, Coifman R. On local orthonormal bases for classification and regression. 2013 IEEE International Conference On Acoustics, Speech And Signal Processing 1995, 3: 1529-1532 vol.3. DOI: 10.1109/icassp.1995.479852.Peer-Reviewed Original ResearchOrthonormal basisRegression problemsLocal orthonormal basisRelative entropyRegression errorsStatistical methodsSynthetic examplesSignificant coordinatesBasis functionsLinear discriminant analysisRegression methodEnergy distributionRegression treesProblemClassification problemTime-frequency planeSignal classificationEntropyTraditional methodsCoordinatesDimensionalityTime-frequency energy distributionSmall number