activity
20062026
most citedLearners that Use Little Information

42 citations · 147 across the 42 of their papers we have counts for

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Showing 2018Show all

6 papers · 1 filter

cs.LG2018★ 1 cited

Average-Case Information Complexity of Learning

Ido Nachum, Amir Yehudayoff

How many bits of information are revealed by a learning algorithm for a concept class of VC-dimension ? Previous works have shown that even for the amount of information m…

math.PR2018★ 20 cited

Anti-concentration in most directions

Anup Rao, Amir Yehudayoff

We prove anti-concentration bounds for the inner product of two independent random vectors. For example, we show that if are subsets of the cube with $|A| \cdot…

math.CO2018★ 2 cited

An isoperimetric inequality for Hamming balls and local expansion in hypercubes

Zilin Jiang, Amir Yehudayoff

We prove a vertex isoperimetric inequality for the -dimensional Hamming ball of radius . The isoperimetric inequality is sharp up to a constant factor for…

cs.LG2018

On the Perceptron's Compression

Shay Moran, Ido Nachum, Itai Panasoff +1

We study and provide exposition to several phenomena that are related to the perceptron's compression. One theme concerns modifications of the perceptron algorithm that yield bette…

cs.NE2018★ 22 cited

On the Covariance-Hessian Relation in Evolution Strategies

Ofer M. Shir, Amir Yehudayoff

We consider Evolution Strategies operating only with isotropic Gaussian mutations on positive quadratic objective functions, and investigate the covariance matrix when constructed…

cs.LG2018★ 1 cited

A Direct Sum Result for the Information Complexity of Learning

Ido Nachum, Jonathan Shafer, Amir Yehudayoff

How many bits of information are required to PAC learn a class of hypotheses of VC dimension ? The mathematical setting we follow is that of Bassily et al. (2018), where the val…