citedonpage3
OnFeatureLearninginthePresenceofSpurious Correlations
Ontheotherhand,wefindthatstrong regularization is not necessary for learning high-quality feature representations.
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks > Deep Learning (0.46)
Gradient-FreeMethodsforDeterministicand StochasticNonsmoothNonconvexOptimization
Thus a gap has arisen between theory and practice.
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- North America > Canada > Ontario > Toronto (0.04)
Technology:
Last-IterateConvergenceofOptimisticGradient MethodforMonotoneVariationalInequalities
In 1weintroduce ourmotivations, ourmain results and discuss the related work.
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- Asia > Russia (0.14)
- North America > Canada (0.04)
- Europe > Russia > Central Federal District > Moscow Oblast > Moscow (0.04)
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2ea07a4acbf7e38913062fd69a70805f-Paper-Conference.pdf
By identifying an instrumental variable correlated with the variableX butunrelated tothe confounders, researchers can isolate the exogenous variation inX and estimate acausal relationship betweenX andY.
Technology:
SparseFourierBackpropagationinCryo-EM Reconstruction
Thepresence of multiple structural states in the data represents a major bottleneck in existing processing pipelines, often requiring expert user supervision.
Technology: Information Technology > Artificial Intelligence > Machine Learning > Neural Networks (0.46)