44 citations · 143 across the 23 of their papers we have counts for
8 papers · 1 filter
Consistency of Interpolation with Laplace Kernels is a High-Dimensional Phenomenon
Alexander Rakhlin, Xiyu Zhai
We show that minimum-norm interpolation in the Reproducing Kernel Hilbert Space corresponding to the Laplace kernel is not consistent if input dimension is constant. The lower boun…
Just Interpolate: Kernel "Ridgeless" Regression Can Generalize
Tengyuan Liang, Alexander Rakhlin
In the absence of explicit regularization, Kernel "Ridgeless" Regression with nonlinear kernels has the potential to fit the training data perfectly. It has been observed empirical…
Does data interpolation contradict statistical optimality?
Mikhail Belkin, Alexander Rakhlin, Alexandre B. Tsybakov
We show that learning methods interpolating the training data can achieve optimal rates for the problems of nonparametric regression and prediction with square loss.
Angiodysplasia Detection and Localization Using Deep Convolutional Neural Networks
Alexey Shvets, Vladimir Iglovikov, Alexander Rakhlin +1
Accurate detection and localization for angiodysplasia lesions is an important problem in early stage diagnostics of gastrointestinal bleeding and anemia. Gold-standard for angiody…
Deep Convolutional Neural Networks for Breast Cancer Histology Image Analysis
Alexander Rakhlin, Alexey Shvets, Vladimir Iglovikov +1
Breast cancer is one of the main causes of cancer death worldwide. Early diagnostics significantly increases the chances of correct treatment and survival, but this process is tedi…
Online Learning: Sufficient Statistics and the Burkholder Method
Dylan J. Foster, Alexander Rakhlin, Karthik Sridharan
We uncover a fairly general principle in online learning: If regret can be (approximately) expressed as a function of certain "sufficient statistics" for the data sequence, then th…