
Agnostic Proper Learning of Halfspaces under Gaussian Marginals
We study the problem of agnostically learning halfspaces under the Gauss...
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Convergence and Sample Complexity of SGD in GANs
We provide theoretical convergence guarantees on training Generative Adv...
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Optimal Private Median Estimation under Minimal Distributional Assumptions
We study the fundamental task of estimating the median of an underlying ...
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Computationally and Statistically Efficient Truncated Regression
We provide a computationally and statistically efficient estimator for t...
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A Polynomial Time Algorithm for Learning Halfspaces with Tsybakov Noise
We study the problem of PAC learning homogeneous halfspaces in the prese...
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Fast and Simple Modular Subset Sum
We revisit the Subset Sum problem over the finite cyclic group ℤ_m for s...
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Efficient Parameter Estimation of Truncated Boolean Product Distributions
We study the problem of estimating the parameters of a Boolean product d...
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NonConvex SGD Learns Halfspaces with Adversarial Label Noise
We study the problem of agnostically learning homogeneous halfspaces in ...
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Learning Halfspaces with Tsybakov Noise
We study the efficient PAC learnability of halfspaces in the presence of...
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Menusize Complexity and Revenue Continuity of Buymany Mechanisms
We study the multiitem mechanism design problem where a monopolist sell...
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Blackbox Methods for Restoring Monotonicity
In many practical applications, heuristic or approximation algorithms ar...
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Learning Halfspaces with Massart Noise Under Structured Distributions
We study the problem of learning halfspaces with Massart noise in the di...
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Robust Mean Estimation under Coordinatelevel Corruption
Data corruption, systematic or adversarial, may skew statistical estimat...
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Learning Optimal Search Algorithms from Data
Classical algorithm design is geared towards worst case instances and fa...
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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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The Complexity of BlackBox Mechanism Design with Priors
We study blackbox reductions from mechanism design to algorithm design ...
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DistributionIndependent PAC Learning of Halfspaces with Massart Noise
We study the problem of distributionindependent PAC learning of halfsp...
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Diversity and Exploration in Social Learning
In consumer search, there is a set of items. An agent has a prior over h...
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Learning to Prune: Speeding up Repeated Computations
It is common to encounter situations where one must solve a sequence of ...
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Buymany mechanisms are not much better than item pricing
Multiitem mechanisms can be very complex offering many different bundle...
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Reasonable multiitem mechanisms are not much better than item pricing
Multiitem mechanisms can be very complex offering many different bundle...
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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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Anaconda: A NonAdaptive Conditional Sampling Algorithm for Distribution Testing
We investigate distribution testing with access to nonadaptive conditio...
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Fast Modular Subset Sum using Linear Sketching
Given n positive integers, the Modular Subset Sum problem asks if a subs...
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Actively Avoiding Nonsense in Generative Models
A generative model may generate utter nonsense when it is fit to maximiz...
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Capacitated Dynamic Programming: Faster Knapsack and Graph Algorithms
One of the most fundamental problems in Theoretical Computer Science is ...
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Combinatorial Assortment Optimization
Assortment optimization refers to the problem of designing a slate of pr...
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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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Truthful Facility Location with Additive Errors
We address the problem of locating facilities on the [0,1] interval base...
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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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Christos Tzamos
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