
Computationally and Statistically Efficient Truncated Regression
We provide a computationally and statistically efficient estimator for t...
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Optimal Approximation – Smoothness Tradeoffs for SoftMax Functions
A softmax function has two main efficiency measures: (1) approximation ...
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The Complexity of Constrained MinMax Optimization
Despite its important applications in Machine Learning, minmax optimiza...
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Truncated Linear Regression in High Dimensions
As in standard linear regression, in truncated linear regression, we are...
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Estimation and Inference with Trees and Forests in High Dimensions
We analyze the finite sample mean squared error (MSE) performance of reg...
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ConstantExpansion Suffices for Compressed Sensing with Generative Priors
Generative neural networks have been empirically found very promising in...
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A Topological Characterization of Modulop Arguments and Implications for Necklace Splitting
The classes PPAp have attracted attention lately, because they are the ...
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ConsensusHalving: Does it Ever Get Easier?
In the εConsensusHalving problem, a fundamental problem in fair divisi...
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ConsenusHalving: Does it Ever Get Easier?
In the εConsensusHalving problem, a fundamental problem in fair divisi...
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On the Complexity of Moduloq Arguments and the ChevalleyWarning Theorem
We study the search problem class PPA_q defined as a moduloq analog of ...
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Efficient Truncated Statistics with Unknown Truncation
We study the problem of estimating the parameters of a Gaussian distribu...
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Optimal Learning of Mallows Block Model
The Mallows model, introduced in the seminal paper of Mallows 1957, is o...
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Efficient Statistics, in High Dimensions, from Truncated Samples
We provide an efficient algorithm for the classical problem, going back ...
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PPPCompleteness with Connections to Cryptography
Polynomial Pigeonhole Principle (PPP) is an important subclass of TFNP w...
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Certified Computation in Crowdsourcing
A wide range of learning tasks require human input in labeling massive d...
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A Converse to Banach's Fixed Point Theorem and its CLS Completeness
Banach's fixed point theorem for contraction maps has been widely used t...
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Ten Steps of EM Suffice for Mixtures of Two Gaussians
The ExpectationMaximization (EM) algorithm is a widely used method for ...
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Manolis Zampetakis
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