
Understanding Entropic Regularization in GANs
Generative Adversarial Networks are a popular method for learning distri...
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Pointwise Bounds for Distribution Estimation under Communication Constraints
We consider the problem of estimating a ddimensional discrete distribut...
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Batched Thompson Sampling
We introduce a novel anytime Batched Thompson sampling policy for multi...
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Asymptotic Performance of Thompson Sampling in the Batched MultiArmed Bandits
We study the asymptotic performance of the Thompson sampling algorithm i...
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Breaking The Dimension Dependence in Sparse Distribution Estimation under Communication Constraints
We consider the problem of estimating a ddimensional ssparse discrete ...
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OvertheAir Statistical Estimation
We study schemes and lower bounds for distributed minimax statistical es...
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Fisher Information and Mutual Information Constraints
We consider the processing of statistical samples X∼ P_θ by a channel p(...
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Adaptive Group Testing on Networks with Community Structure
Since the inception of the group testing problem in World War II, the pr...
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Asymptotic Convergence of Thompson Sampling
Thompson sampling has been shown to be an effective policy across a vari...
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Information Constrained Optimal Transport: From Talagrand, to Marton, to Cover
The optimal transport problem studies how to transport one measure to an...
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Breaking the CommunicationPrivacyAccuracy Trilemma
Two major challenges in distributed learning and estimation are 1) prese...
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Lower Bounds and a NearOptimal Shrinkage Estimator for Least Squares using Random Projections
In this work, we consider the deterministic optimization using random pr...
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Global Multiclass Classification from Heterogeneous Local Models
Multiclass classification problems are most often solved by either train...
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Fisher information under local differential privacy
We develop data processing inequalities that describe how Fisher informa...
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rTopk: A Statistical Estimation Approach to Distributed SGD
The large communication cost for exchanging gradients between different ...
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The CourtadeKumar Most Informative Boolean Function Conjecture and a Symmetrized LiMédard Conjecture are Equivalent
We consider the CourtadeKumar most informative Boolean function conject...
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Advances and Open Problems in Federated Learning
Federated learning (FL) is a machine learning setting where many clients...
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Minimax Bounds for Distributed Logistic Regression
We consider a distributed logistic regression problem where labeled data...
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Learning Distributions from their Samples under Communication Constraints
We consider the problem of learning highdimensional, nonparametric and ...
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Capacity Upper Bounds for the Relay Channel via Reverse Hypercontractivity
The primitive relay channel, introduced by Cover in 1987, is the simples...
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An Isoperimetric Result on HighDimensional Spheres
We consider an extremal problem for subsets of highdimensional spheres ...
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On the Optimality of the KautzSingleton Construction in Probabilistic Group Testing
We consider the probabilistic group testing problem where d random defec...
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Minimax Learning for Remote Prediction
The classical problem of supervised learning is to infer an accurate pre...
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Communication with CrystalFree Radios
We consider a communication channel where there is no common clock betwe...
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Geometric Lower Bounds for Distributed Parameter Estimation under Communication Constraints
We consider parameter estimation in distributed networks, where each nod...
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Ayfer Özgür
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