most citedEfficient Learning with Partially Observed Attributes

59 citations · 108 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG20124 cited

Learning the Experts for Online Sequence Prediction

Elad Eban, Aharon Birnbaum, Shai Shalev-Shwartz +1

Online sequence prediction is the problem of predicting the next element of a sequence given previous elements. This problem has been extensively studied in the context of individu…

cs.LG20125 cited

The Kernelized Stochastic Batch Perceptron

Andrew Cotter, Shai Shalev-Shwartz, Nathan Srebro

We present a novel approach for training kernel Support Vector Machines, establish learning runtime guarantees for our method that are better then those of any other known kerneliz…

cs.LG201238 cited

Near-Optimal Algorithms for Online Matrix Prediction

Elad Hazan, Satyen Kale, Shai Shalev-Shwartz

In several online prediction problems of recent interest the comparison class is composed of matrices with bounded entries. For example, in the online max-cut problem, the comparis…

cs.LG20102 cited

Learning Kernel-Based Halfspaces with the Zero-One Loss

Shai Shalev-Shwartz, Ohad Shamir, Karthik Sridharan

We describe and analyze a new algorithm for agnostically learning kernel-based halfspaces with respect to the \emph{zero-one} loss function. Unlike most previous formulations which…

cs.LG201059 cited

Efficient Learning with Partially Observed Attributes

Nicolò Cesa-Bianchi, Shai Shalev-Shwartz, Ohad Shamir

We describe and analyze efficient algorithms for learning a linear predictor from examples when the learner can only view a few attributes of each training example. This is the cas…