
Pure Exploration in Multiarmed Bandits with Graph Side Information
We study pure exploration in multiarmed bandits with graph sideinforma...
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State and Topology Estimation for Unobservable Distribution Systems using Deep Neural Networks
Timesynchronized state estimation for reconfigurable distribution netwo...
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Graph Community Detection from Coarse Measurements: Recovery Conditions for the Coarsened Weighted Stochastic Block Model
We study the problem of community recovery from coarse measurements of a...
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Finding the Homology of Decision Boundaries with Active Learning
Accurately and efficiently characterizing the decision boundary of class...
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Differentiable Programming for Hyperspectral Unmixing using a Physicsbased Dispersion Model
Hyperspectral unmixing is an important remote sensing task with applicat...
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On the alphaloss Landscape in the Logistic Model
We analyze the optimization landscape of a recently introduced tunable c...
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On the Sample Complexity and Optimization Landscape for Quadratic Feasibility Problems
We consider the problem of recovering a complex vector x∈C^n from m quad...
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Regularization via Structural Label Smoothing
Regularization is an effective way to promote the generalization perform...
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Graph quilting: graphical model selection from partially observed covariances
We investigate the problem of conditional dependence graph estimation wh...
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A Tunable Loss Function for Classification
Recently, a parametrized class of loss functions called αloss, α∈ [1,∞]...
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Thresholding Graph Bandits with GrAPL
In this paper, we introduce a new online decision making paradigm that w...
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IdeoTrace: A Framework for Ideology Tracing with a Case Study on the 2016 U.S. Presidential Election
The 2016 United States presidential election has been characterized as a...
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MISSION: Ultra LargeScale Feature Selection using CountSketches
Feature selection is an important challenge in machine learning. It play...
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DeepCodec: Adaptive Sensing and Recovery via Deep Convolutional Neural Networks
In this paper we develop a novel computational sensing framework for sen...
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Multifidelity Bayesian Optimisation with Continuous Approximations
Bandit methods for blackbox optimisation, such as Bayesian optimisation...
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Multifidelity Gaussian Process Bandit Optimisation
In many scientific and engineering applications, we are tasked with the ...
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Active Learning Algorithms for Graphical Model Selection
The problem of learning the structure of a high dimensional graphical mo...
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S2: An Efficient Graph Based Active Learning Algorithm with Application to Nonparametric Classification
This paper investigates the problem of active learning for binary label ...
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Data Requirement for Phylogenetic Inference from Multiple Loci: A New Distance Method
We consider the problem of estimating the evolutionary history of a set ...
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Active Clustering: Robust and Efficient Hierarchical Clustering using Adaptively Selected Similarities
Hierarchical clustering based on pairwise similarities is a common tool ...
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Gautam Dasarathy
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