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We consider the problem of probably approximately correct (PAC) ranking $n$ items by adaptively eliciting subset-wise preference feedback. At each round, the learner chooses a subset of $k$ items and observes stochastic feedback indicating…

Machine Learning · Computer Science 2019-03-06 Aadirupa Saha , Aditya Gopalan

$k$-Clustering in $\mathbb{R}^d$ (e.g., $k$-median and $k$-means) is a fundamental machine learning problem. While near-linear time approximation algorithms were known in the classical setting for a dataset with cardinality $n$, it remains…

Quantum Physics · Physics 2023-06-06 Yecheng Xue , Xiaoyu Chen , Tongyang Li , Shaofeng H. -C. Jiang

We are given $n$ balls and an unknown coloring of them with two colors. Our goal is to find a ball that belongs to the larger color class, or show that the color classes have the same size. We can ask sets of $k$ balls as queries, and the…

Combinatorics · Mathematics 2023-06-22 Dániel Gerbner , Máté Vizer

Motivated by the mode estimation problem of an unknown multivariate probability density function, we study the problem of identifying the point with the minimum k-th nearest neighbor distance for a given dataset of n points. We study the…

Machine Learning · Statistics 2020-10-27 Anirudh Singhal , Subham Pirojiwala , Nikhil Karamchandani

The expected number of pairwise comparisons needed to learn a partial order on n elements is shown to be at least n*n/4-o(n*n), and an algorithm is given that needs only n*n/4+o(n*n) comparisons on average. In addition, the optimal strategy…

Combinatorics · Mathematics 2007-05-23 Jobst Heitzig

Given an undirected graph representing similarities between a set of items and an additive measure evaluating the items, we treat the position of a special subset of items in an ordinal ranking through a collection of combinatorial…

Data Structures and Algorithms · Computer Science 2026-05-05 Samuel Boardman

Polytrees are a subclass of Bayesian networks that seek to capture the conditional dependencies between a set of $n$ variables as a directed forest and are motivated by their more efficient inference and improved interpretability. Since the…

Data Structures and Algorithms · Computer Science 2026-05-06 Juha Harviainen , Frank Sommer , Manuel Sorge

We propose a framework for Semi-Supervised Active Clustering framework (SSAC), where the learner is allowed to interact with a domain expert, asking whether two given instances belong to the same cluster or not. We study the query and…

Machine Learning · Computer Science 2016-11-23 Hassan Ashtiani , Shrinu Kushagra , Shai Ben-David

Partitioning a set of elements into subsets of a priori unknown sizes is essential in many applications. These subset sizes are rarely explicitly learned - be it the cluster sizes in clustering applications or the number of shared versus…

Machine Learning · Computer Science 2023-06-23 Thomas M. Sutter , Laura Manduchi , Alain Ryser , Julia E. Vogt

Sorting is a foundational problem in computer science that is typically employed on sequences or total orders. More recently, a more general form of sorting on partially ordered sets (or posets), where some pairs of elements are…

Data Structures and Algorithms · Computer Science 2022-06-03 Jishnu Roychoudhury , Jatin Yadav

Overlapping clusters are common in models of many practical data-segmentation applications. Suppose we are given $n$ elements to be clustered into $k$ possibly overlapping clusters, and an oracle that can interactively answer queries of the…

Machine Learning · Computer Science 2019-10-29 Wasim Huleihel , Arya Mazumdar , Muriel Médard , Soumyabrata Pal

Consider the problem: we are given $n$ boxes, labeled $\{1,2,\ldots, n\}$ by an adversary, each containing a single number chosen from an unknown distribution; these $n$ distributions are not necessarily identical. We are also given an…

Data Structures and Algorithms · Computer Science 2024-05-13 Mohammad Taghi Hajiaghayi , Dariusz R. Kowalski , Piotr Krysta , Jan Olkowski

In this paper, we consider the problem of learning an unknown graph via queries on groups of nodes, with the result indicating whether or not at least one edge is present among those nodes. While learning arbitrary graphs with $n$ nodes and…

Information Theory · Computer Science 2020-01-07 Zihan Li , Matthias Fresacher , Jonathan Scarlett

We present prior robust algorithms for a large class of resource allocation problems where requests arrive one-by-one (online), drawn independently from an unknown distribution at every step. We design a single algorithm that, for every…

Data Structures and Algorithms · Computer Science 2019-03-12 Nikhil R. Devanur , Kamal Jain , Balasubramanian Sivan , Christopher A. Wilkens

Causal discovery from interventional data is an important problem, where the task is to design an interventional strategy that learns the hidden ground truth causal graph $G(V,E)$ on $|V| = n$ nodes while minimizing the number of performed…

Machine Learning · Computer Science 2023-06-12 Davin Choo , Kirankumar Shiragur

We study the query complexity of quantum learning problems in which the oracles form a group $G$ of unitary matrices. In the simplest case, one wishes to identify the oracle, and we find a description of the optimal success probability of a…

Computational Complexity · Computer Science 2021-03-10 Daniel Copeland , Jamie Pommersheim

Efficiently counting or detecting defective items is a crucial task in various fields ranging from biological testing to quality control to streaming algorithms. The \emph{group testing estimation problem} concerns estimating the number of…

Data Structures and Algorithms · Computer Science 2023-12-08 Nader H. Bshouty , Tsun-Ming Cheung , Gergely Harcos , Hamed Hatami , Anthony Ostuni

We study the problem of reaching agreement in a synchronous distributed system by $n$ autonomous parties, when the communication links from/to faulty parties can omit messages. The faulty parties are selected and controlled by an adaptive,…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-05-27 Mohammad T. Hajiaghayi , Dariusz R. Kowalski , Jan Olkowski

The paper presents complexity results and performance guaranties for a family of approximation algorithms for an optimisation problem arising in software testing and manufacturing. The problem is formulated as a partitioning of a set where…

Data Structures and Algorithms · Computer Science 2022-12-13 Yakov Zinder , Bertrand M. T. Lin , Joanna Berlińska

A classical theorem of Baranyai states that, given integers $2\leq k < n$ such that $k$ divides $n$, one can find a family of ${n-1\choose k-1}$ partitions of $[n]$ into $k$-element subsets such that every subset appears in exactly one…

Combinatorics · Mathematics 2024-10-14 Zoe Xi
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