Konstantin KutzkovinTowards Data ScienceMachine Learning on Graphs, Part 4Learning discrete node embeddingsNov 29, 2022Nov 29, 2022
Konstantin KutzkovinTowards Data ScienceLearning to hashHow to design data representation techniques with applications to fast retrieval tasksOct 21, 2021Oct 21, 2021
Konstantin KutzkovinTowards Data ScienceMaximum inner product search using nearest neighbor search algorithmsA simple reduction that allows using libraries for nearest neighbor search for the efficient detection of vectors with large inner productOct 13, 20211Oct 13, 20211
Konstantin KutzkovinTowards Data ScienceBilinear pooling for fine-grained visual recognition and multi-modal deep learningAdvanced neural network architectures work by learning feature interactionsOct 7, 2021Oct 7, 2021
Konstantin KutzkovinTowards Data ScienceMachine Learning on Graphs, Part 3Graph kernels methods that are easy to implement and yield models that can be efficiently trainedOct 1, 2021Oct 1, 2021
Konstantin KutzkovinTowards Data ScienceEfficiently computing the variance in massive and distributed datasetsScalable data summarization techniques for one of the most fundamental problems in data analysisSep 24, 2021Sep 24, 2021
Konstantin KutzkovinTowards Data ScienceMachine Learning on Graphs, Part 2Node embeddings.Sep 22, 2021Sep 22, 2021
Konstantin KutzkovinTowards Data ScienceMachine Learning on Graphs, Part 1Collecting basic statisticsSep 9, 20211Sep 9, 20211
Konstantin KutzkovinTowards Data ScienceWhat does word2vec actually learn?And how to train embeddings from similarity functionsSep 6, 20213Sep 6, 20213
Konstantin KutzkovinTowards Data ScienceExplicit feature maps for non-linear kernel functionsIt is all about finding the right spaceSep 2, 20211Sep 2, 20211