61 citations · 179 across the 39 of their papers we have counts for
10 papers · 1 filter
Adaptivity in Adaptive Submodularity
Hossein Esfandiari, Amin Karbasi, Vahab Mirrokni
Adaptive sequential decision making is one of the central challenges in machine learning and artificial intelligence. In such problems, the goal is to design an interactive policy…
Locality-Sensitive Hashing for f-Divergences: Mutual Information Loss and Beyond
Lin Chen, Hossein Esfandiari, Thomas Fu +1
Computing approximate nearest neighbors in high dimensional spaces is a central problem in large-scale data mining with a wide range of applications in machine learning and data sc…
Prophets, Secretaries, and Maximizing the Probability of Choosing the Best
Hossein Esfandiari, MohammadTaghi HajiAghayi, Brendan Lucier +1
Suppose a customer is faced with a sequence of fluctuating prices, such as for airfare or a product sold by a large online retailer. Given distributional information about what pri…
Streaming Balanced Clustering
Hossein Esfandiari, Vahab Mirrokni, Peilin Zhong
Clustering of data points in metric space is among the most fundamental problems in computer science with plenty of applications in data mining, information retrieval and machine l…
Near-Optimal Massively Parallel Graph Connectivity
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari +2
Identifying the connected components of a graph, apart from being a fundamental problem with countless applications, is a key primitive for many other algorithms. In this paper, we…
Regret Bounds for Batched Bandits
Hossein Esfandiari, Amin Karbasi, Abbas Mehrabian +1
We present simple and efficient algorithms for the batched stochastic multi-armed bandit and batched stochastic linear bandit problems. We prove bounds for their expected regrets t…
Massively Parallel Computation via Remote Memory Access
Soheil Behnezhad, Laxman Dhulipala, Hossein Esfandiari +3
We introduce the Adaptive Massively Parallel Computation (AMPC) model, which is an extension of the Massively Parallel Computation (MPC) model. At a high level, the AMPC model stre…
Seeding with Costly Network Information
Dean Eckles, Hossein Esfandiari, Elchanan Mossel +1
We study the task of selecting nodes, in a social network of size , to seed a diffusion with maximum expected spread size, under the independent cascade model with cascade p…
Categorical Feature Compression via Submodular Optimization
MohammadHossein Bateni, Lin Chen, Hossein Esfandiari +3
In the era of big data, learning from categorical features with very large vocabularies (e.g., 28 million for the Criteo click prediction dataset) has become a practical challenge…
Online Pandora's Boxes and Bandits
Hossein Esfandiari, MohammadTaghi Hajiaghayi, Brendan Lucier +1
We consider online variations of the Pandora's box problem (Weitzman. 1979), a standard model for understanding issues related to the cost of acquiring information for decision-mak…