7 citations · 13 across the 6 of their papers we have counts for
6 papers
The Elliptical Potential Lemma for General Distributions with an Application to Linear Thompson Sampling
Nima Hamidi, Mohsen Bayati
In this note, we introduce a general version of the well-known elliptical potential lemma that is a widely used technique in the analysis of algorithms in sequential learning and d…
On Frequentist Regret of Linear Thompson Sampling
Nima Hamidi, Mohsen Bayati
This paper studies the stochastic linear bandit problem, where a decision-maker chooses actions from possibly time-dependent sets of vectors in and receives noisy re…
The Unreasonable Effectiveness of Greedy Algorithms in Multi-Armed Bandit with Many Arms
Mohsen Bayati, Nima Hamidi, Ramesh Johari +1
We investigate a Bayesian -armed bandit problem in the \emph{many-armed} regime, where and represents the time horizon. Initially, and aligned with recent…
A General Theory of the Stochastic Linear Bandit and Its Applications
Nima Hamidi, Mohsen Bayati
Recent growing adoption of experimentation in practice has led to a surge of attention to multiarmed bandits as a technique to reduce the opportunity cost of online experiments. In…
Multi-scale Embedded CNN for Music Tagging (MsE-CNN)
Nima Hamidi, Mohsen Vahidzadeh, Stephen Baek
Convolutional neural networks (CNN) recently gained notable attraction in a variety of machine learning tasks: including music classification and style tagging. In this work, we pr…
On Low-rank Trace Regression under General Sampling Distribution
Nima Hamidi, Mohsen Bayati
In this paper, we study the trace regression when a matrix of parameters B* is estimated via the convex relaxation of a rank-regularized regression or via regularized non-convex op…