107 citations · 165 across the 24 of their papers we have counts for
8 papers · 1 filter
Online Semi-Supervised Learning with Bandit Feedback
Sohini Upadhyay, Mikhail Yurochkin, Mayank Agarwal +2
We formulate a new problem at the intersectionof semi-supervised learning and contextual bandits,motivated by several applications including clini-cal trials and ad recommendations…
Double-Linear Thompson Sampling for Context-Attentive Bandits
Djallel Bouneffouf, Raphaël Féraud, Sohini Upadhyay +2
In this paper, we analyze and extend an online learning framework known as Context-Attentive Bandit, motivated by various practical applications, from medical diagnosis to dialog s…
Spectral Clustering using Eigenspectrum Shape Based Nystrom Sampling
Djallel Bouneffouf
Spectral clustering has shown a superior performance in analyzing the cluster structure. However, its computational complexity limits its application in analyzing large-scale data.…
Contextual Bandit with Missing Rewards
Djallel Bouneffouf, Sohini Upadhyay, Yasaman Khazaeni
We consider a novel variant of the contextual bandit problem (i.e., the multi-armed bandit with side-information, or context, available to a decision-maker) where the reward associ…
Computing the Dirichlet-Multinomial Log-Likelihood Function
Djallel Bouneffouf
Dirichlet-multinomial (DMN) distribution is commonly used to model over-dispersion in count data. Precise and fast numerical computation of the DMN log-likelihood function is impor…
Solving Constrained CASH Problems with ADMM
Parikshit Ram, Sijia Liu, Deepak Vijaykeerthi +5
The CASH problem has been widely studied in the context of automated configurations of machine learning (ML) pipelines and various solvers and toolkits are available. However, CASH…