Search Results for author: Frederik Mallmann-Trenn

Found 8 papers, 0 papers with code

Beyond Impossibility: Balancing Sufficiency, Separation and Accuracy

no code implementations24 May 2022 Limor Gultchin, Vincent Cohen-Addad, Sophie Giffard-Roisin, Varun Kanade, Frederik Mallmann-Trenn

Among the various aspects of algorithmic fairness studied in recent years, the tension between satisfying both \textit{sufficiency} and \textit{separation} -- e. g. the ratios of positive or negative predictive values, and false positive or false negative rates across groups -- has received much attention.


On the Power of Louvain in the Stochastic Block Model

no code implementations NeurIPS 2020 Vincent Cohen-Addad, Adrian Kosowski, Frederik Mallmann-Trenn, David Saulpic

A classic problem in machine learning and data analysis is to partition the vertices of a network in such a way that vertices in the same set are densely connected and vertices in different sets are loosely connected.

BIG-bench Machine Learning Stochastic Block Model

Online Page Migration with ML Advice

no code implementations9 Jun 2020 Piotr Indyk, Frederik Mallmann-Trenn, Slobodan Mitrović, Ronitt Rubinfeld

In contrast, we show that if the algorithm is given a prediction of the input sequence, then it can achieve a competitive ratio that tends to $1$ as the prediction error rate tends to $0$.

Learning Hierarchically Structured Concepts

no code implementations10 Sep 2019 Nancy Lynch, Frederik Mallmann-Trenn

Our main goal is to introduce a general framework for these tasks and prove formally how both (recognition and learning) can be achieved.

Clustering Redemption–Beyond the Impossibility of Kleinberg’s Axioms

no code implementations NeurIPS 2018 Vincent Cohen-Addad, Varun Kanade, Frederik Mallmann-Trenn

In this work, we take a different approach, based on the observation that the consistency axiom fails to be satisfied when the “correct” number of clusters changes.

Instance-Optimality in the Noisy Value-and Comparison-Model --- Accept, Accept, Strong Accept: Which Papers get in?

no code implementations21 Jun 2018 Vincent Cohen-Addad, Frederik Mallmann-Trenn, Claire Mathieu

In this paper, we show optimal worst-case query complexity for the \textsc{max},\textsc{threshold-$v$} and \textsc{Top}-$k$ problems.

Recommendation Systems

Hierarchical Clustering Beyond the Worst-Case

no code implementations NeurIPS 2017 Vincent Cohen-Addad, Varun Kanade, Frederik Mallmann-Trenn

Hiererachical clustering, that is computing a recursive partitioning of a dataset to obtain clusters at increasingly finer granularity is a fundamental problem in data analysis.

General Classification Multi-class Classification

Hierarchical Clustering: Objective Functions and Algorithms

no code implementations7 Apr 2017 Vincent Cohen-Addad, Varun Kanade, Frederik Mallmann-Trenn, Claire Mathieu

For similarity-based hierarchical clustering, Dasgupta showed that the divisive sparsest-cut approach achieves an $O(\log^{3/2} n)$-approximation.

Combinatorial Optimization Stochastic Block Model

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