Flavio Chierichetti
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View article: Man, these New York Times games are hard! A computational perspective
Man, these New York Times games are hard! A computational perspective Open
The New York Times (NYT) games have found widespread popularity in recent years and reportedly account for an increasing fraction of the newspaper's readership. In this paper, we bring the computational lens to the study of New York Times …
View article: Discrete Choice and Applications
Discrete Choice and Applications Open
Modern machine learning and AI have revolutionized the generation of ranking and recommendations across many domains, taking data-driven approaches to inferring the candidate items a user is most likely to select. The theory of discrete ch…
View article: Information foraging with an oracle
Information foraging with an oracle Open
During ecological decisions, such as when foraging for food or selecting a weekend activity, we often have to balance the costs and benefits of exploiting known options versus exploring novel ones. Here, we ask how individuals address such…
View article: Approximating a RUM from Distributions on k-Slates
Approximating a RUM from Distributions on k-Slates Open
In this work we consider the problem of fitting Random Utility Models (RUMs) to user choices. Given the winner distributions of the subsets of size $k$ of a universe, we obtain a polynomial-time algorithm that finds the RUM that best appro…
View article: On the number of trials needed to distinguish similar alternatives
On the number of trials needed to distinguish similar alternatives Open
A/B testing is widely used to tune search and recommendation algorithms, to compare product variants as efficiently and effectively as possible, and even to study animal behavior. With ongoing investment, due to diminishing returns, the it…
View article: The Gibbs-Rand Model
The Gibbs-Rand Model Open
Due to its many applications, the clustering ensemble problem has been subject of intense algorithmic study over the last two decades. The input to this problem is a set of clusterings; its goal is to output a clustering that minimizes the…
View article: Correlation Clustering Reconstruction in Semi-Adversarial Models
Correlation Clustering Reconstruction in Semi-Adversarial Models Open
Correlation Clustering is an important clustering problem with many applications. We study the reconstruction version of this problem in which one is seeking to reconstruct a latent clustering that has been corrupted by random noise and ad…
View article: Spectral Robustness for Correlation Clustering Reconstruction in Semi-Adversarial Models
Spectral Robustness for Correlation Clustering Reconstruction in Semi-Adversarial Models Open
Correlation Clustering is an important clustering problem with many applications. We study the reconstruction version of this problem in which one is seeking to reconstruct a latent clustering that has been corrupted by random noise and ad…
View article: Motif Counting Beyond Five Nodes
Motif Counting Beyond Five Nodes Open
This is the preprint version of an ACM TKDD paper, https://doi.org/10.1145/3186586.
View article: Matroids, Matchings and Fairness
Matroids, Matchings and Fairness Open
The need for fairness in machine learning algorithms is increasingly critical. A recent focus has been on developing fair versions of classical algorithms, such as those for bandit learning, regression, and clustering. We extend this line …
View article: Learning a Mixture of Two Multinomial Logits
Learning a Mixture of Two Multinomial Logits Open
The classical Multinomial Logit (MNL) is a behavioral model for user choice. In this model, a user is offered a slate of choices (a subset of a finite universe of 𝑛n items), and selects exactly one item from the slate, each with probabilit…
View article: Approximate Submodularity
Approximate Submodularity Open
A real-valued set function is (additively) approximately submodular if it satisfies the submodularity conditions with an additive error. Approximate submodularity arises in many settings, especially in machine learning, where the function …
View article: On Additive Approximate Submodularity
On Additive Approximate Submodularity Open
A real-valued set function is (additively) approximately submodular if it satisfies the submodularity conditions with an additive error. Approximate submodularity arises in many settings, especially in machine learning, where the function …
View article: Asymptotic Behavior of Sequence Models
Asymptotic Behavior of Sequence Models Open
In this paper we study the limiting dynamics of a sequential process that generalizes Polya's urn. This process has been studied also in the context of language generation, discrete choice, repeat consumption, and models for the web graph.…
View article: On the Distortion of Locality Sensitive Hashing
On the Distortion of Locality Sensitive Hashing Open
Given a notion of pairwise similarity between objects, locality sensitive hashing (LSH) aims to construct a hash function family over the universe of objects such that the probability two objects hash to the same value is their similarity.…
View article: A Reduction for Efficient LDA Topic Reconstruction
A Reduction for Efficient LDA Topic Reconstruction Open
We present a novel approach for LDA (Latent Dirichlet Allocation) topic reconstruction. The main technical idea is to show that the distribution over the documents generated by LDA can be transformed into a distribution for a much simpler …
View article: Mallows Models for Top-k Lists
Mallows Models for Top-k Lists Open
The classic Mallows model is a widely-used tool to realize distributions on per- mutations. Motivated by common practical situations, in this paper, we generalize Mallows to model distributions on top-k lists by using a suitable distance m…
View article: Motif Counting Beyond Five Nodes
Motif Counting Beyond Five Nodes Open
Counting graphlets is a well-studied problem in graph mining and social network analysis. Recently, several papers explored very simple and natural algorithms based on Monte Carlo sampling of Markov Chains (MC), and reported encouraging re…
View article: Rumor Spreading and Conductance
Rumor Spreading and Conductance Open
In this article, we study the completion time of the PUSH-PULL variant of rumor spreading, also known as randomized broadcast. We show that if a network has n nodes and conductance ϕ then, with high probability, PUSH-PULL will deliver the …
View article: Fair Clustering Through Fairlets
Fair Clustering Through Fairlets Open
We study the question of fair clustering under the {\em disparate impact} doctrine, where each protected class must have approximately equal representation in every cluster. We formulate the fair clustering problem under both the $k$-cente…
View article: Discrete Choice, Permutations, and Reconstruction
Discrete Choice, Permutations, and Reconstruction Open
In this paper we study the well-known family of Random Utility Models, developed over 50 years ago to codify rational user behavior in choosing one item from a finite set of options. In this setting each user draws i.i.d. from some distrib…
View article: Discrete Choice, Permutations, and Reconstruction
Discrete Choice, Permutations, and Reconstruction Open
In this paper we study the well-known family of Random Utility Models, developed over 50 years ago to codify rational user behavior in choosing one item from a finite set of options. In this setting each user draws i.i.d. from some distrib…
View article: On the Complexity of Sampling Vertices Uniformly from a Graph
On the Complexity of Sampling Vertices Uniformly from a Graph Open
We study a number of graph exploration problems in the following natural scenario: an algorithm starts exploring an undirected graph from some seed vertex; the algorithm, for an arbitrary vertex v that it is aware of, can ask an oracle to …
View article: On the Complexity of Sampling Nodes Uniformly from a Graph
On the Complexity of Sampling Nodes Uniformly from a Graph Open
We study a number of graph exploration problems in the following natural scenario: an algorithm starts exploring an undirected graph from some seed node; the algorithm, for an arbitrary node $v$ that it is aware of, can ask an oracle to re…
View article: On the Power Laws of Language
On the Power Laws of Language Open
About eight decades ago, Zipf postulated that the word frequency distribution of languages is a power law, i.e., it is a straight line on a log-log plot. Over the years, this phenomenon has been documented and studied extensively. For many…
View article: Algorithms for $\ell_p$ Low Rank Approximation
Algorithms for $\ell_p$ Low Rank Approximation Open
We consider the problem of approximating a given matrix by a low-rank matrix so as to minimize the entrywise $\ell_p$-approximation error, for any $p \geq 1$; the case $p = 2$ is the classical SVD problem. We obtain the first provably good…
View article: Counting Graphlets
Counting Graphlets Open
Counting graphlets is a well-studied problem in graph mining and social network analysis. Recently, several papers explored very simple and natural approaches based on Monte Carlo sampling of Markov Chains (MC), and reported encouraging re…
View article: The Distortion of Locality Sensitive Hashing
The Distortion of Locality Sensitive Hashing Open
Given a pairwise similarity notion between objects, locality sensitive hashing (LSH) aims to construct a hash function family over the universe of objects such that the probability two objects hash to the same value is their similarity. LS…
View article: On The Distortion of Locality Sensitive Hashing
On The Distortion of Locality Sensitive Hashing Open
Given a notion of pairwise similarity between objects, locality sensitive hashing (LSH) aims to construct a hash function family over the universe of objects such that the probability two objects hash to the same value is their similarity.…