
Parallel Graph Algorithms in Constant Adaptive Rounds: Theory meets Practice
We study fundamental graph problems such as graph connectivity, minimum ...
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Contextual Reserve Price Optimization in Auctions
We study the problem of learning a linear model to set the reserve price...
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Adaptivity in Adaptive Submodularity
Adaptive sequential decision making is one of the central challenges in ...
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LocalitySensitive Hashing for fDivergences: Mutual Information Loss and Beyond
Computing approximate nearest neighbors in high dimensional spaces is a ...
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NearOptimal Massively Parallel Graph Connectivity
Identifying the connected components of a graph, apart from being a fund...
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Batched MultiArmed Bandits with Optimal Regret
We present a simple and efficient algorithm for the batched stochastic m...
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Prophets, Secretaries, and Maximizing the Probability of Choosing the Best
Suppose a customer is faced with a sequence of fluctuating prices, such ...
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Streaming Balanced Clustering
Clustering of data points in metric space is among the most fundamental ...
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Massively Parallel Computation via Remote Memory Access
We introduce the Adaptive Massively Parallel Computation (AMPC) model, w...
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Seeding with Costly Network Information
The spread of behavior over social networks depends on the contact struc...
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Categorical Feature Compression via Submodular Optimization
In the era of big data, learning from categorical features with very lar...
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Online Pandora's Boxes and Bandits
We consider online variations of the Pandora's box problem (Weitzman. 19...
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Parallel and Streaming Algorithms for KCore Decomposition
The kcore decomposition is a fundamental primitive in many machine lear...
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Metric Sublinear Algorithms via Linear Sampling
In this work we provide a new technique to design fast approximation alg...
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Online Allocation with Traffic Spikes: Mixing Adversarial and Stochastic Models
Motivated by Internet advertising applications, online allocation proble...
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Hossein Esfandiari
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