Y. David

most citedThe Max

K

-Armed Bandit: A PAC Lower Bound and tighter Algorithms

1 citations · 1 across the 3 of their papers we have counts for

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stat.ML2016

One-Shot Session Recommendation Systems with Combinatorial Items

Yahel David, Dotan Di Castro, Zohar Karnin

In recent years, content recommendation systems in large websites (or \emph{content providers}) capture an increased focus. While the type of content varies, e.g.\ movies, articles…

stat.ML2015

The Max $K$ -Armed Bandit: PAC Lower Bounds and Efficient Algorithms

Yahel David, Nahum Shimkin

We consider the Max $K$ -Armed Bandit problem, where a learning agent is faced with several stochastic arms, each a source of i.i.d. rewards of unknown distribution. At each time st…

stat.ML2015★ 1 cited

The Max $K$ -Armed Bandit: A PAC Lower Bound and tighter Algorithms

Yahel David, Nahum Shimkin

We consider the Max $K$ -Armed Bandit problem, where a learning agent is faced with several sources (arms) of items (rewards), and interested in finding the best item overall. At ea…

One-Shot Session Recommendation Systems with Combinatorial Items

The Max K-Armed Bandit: PAC Lower Bounds and Efficient Algorithms

The Max K-Armed Bandit: A PAC Lower Bound and tighter Algorithms

The Max $K$ -Armed Bandit: PAC Lower Bounds and Efficient Algorithms

The Max $K$ -Armed Bandit: A PAC Lower Bound and tighter Algorithms