Search Results for author: Abbas Mehrabian

Found 10 papers, 1 papers with code

Regret Bounds for Batched Bandits

no code implementations11 Oct 2019 Hossein Esfandiari, Amin Karbasi, Abbas Mehrabian, Vahab Mirrokni

We present simple and efficient algorithms for the batched stochastic multi-armed bandit and batched stochastic linear bandit problems.

Multi-Armed Bandits

Old Dog Learns New Tricks: Randomized UCB for Bandit Problems

1 code implementation11 Oct 2019 Sharan Vaswani, Abbas Mehrabian, Audrey Durand, Branislav Kveton

We propose $\tt RandUCB$, a bandit strategy that builds on theoretically derived confidence intervals similar to upper confidence bound (UCB) algorithms, but akin to Thompson sampling (TS), it uses randomization to trade off exploration and exploitation.

A Practical Algorithm for Multiplayer Bandits when Arm Means Vary Among Players

no code implementations4 Feb 2019 Etienne Boursier, Emilie Kaufmann, Abbas Mehrabian, Vianney Perchet

We study a multiplayer stochastic multi-armed bandit problem in which players cannot communicate, and if two or more players pull the same arm, a collision occurs and the involved players receive zero reward.

Nearly tight sample complexity bounds for learning mixtures of Gaussians via sample compression schemes

no code implementations NeurIPS 2018 Hassan Ashtiani, Shai Ben-David, Nicholas Harvey, Christopher Liaw, Abbas Mehrabian, Yaniv Plan

We prove that ϴ(k d^2 / ε^2) samples are necessary and sufficient for learning a mixture of k Gaussians in R^d, up to error ε in total variation distance.

Multiplayer bandits without observing collision information

no code implementations25 Aug 2018 Gabor Lugosi, Abbas Mehrabian

We give the first theoretical guarantees for the second model: an algorithm with a logarithmic regret, and an algorithm with a square-root regret type that does not depend on the gaps between the means.

Some techniques in density estimation

no code implementations11 Jan 2018 Hassan Ashtiani, Abbas Mehrabian

Density estimation is an interdisciplinary topic at the intersection of statistics, theoretical computer science and machine learning.

Density Estimation

Near-optimal Sample Complexity Bounds for Robust Learning of Gaussians Mixtures via Compression Schemes

no code implementations14 Oct 2017 Hassan Ashtiani, Shai Ben-David, Nick Harvey, Christopher Liaw, Abbas Mehrabian, Yaniv Plan

We prove that $\tilde{\Theta}(k d^2 / \varepsilon^2)$ samples are necessary and sufficient for learning a mixture of $k$ Gaussians in $\mathbb{R}^d$, up to error $\varepsilon$ in total variation distance.

Sample-Efficient Learning of Mixtures

no code implementations6 Jun 2017 Hassan Ashtiani, Shai Ben-David, Abbas Mehrabian

Let $\mathcal F$ be an arbitrary class of probability distributions, and let $\mathcal{F}^k$ denote the class of $k$-mixtures of elements of $\mathcal F$.

Density Estimation

Nearly-tight VC-dimension and pseudodimension bounds for piecewise linear neural networks

no code implementations8 Mar 2017 Peter L. Bartlett, Nick Harvey, Chris Liaw, Abbas Mehrabian

We prove new upper and lower bounds on the VC-dimension of deep neural networks with the ReLU activation function.

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