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Related papers: Tree Search With Predictions

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Inferences in directed acyclic graphs associated with probability sets and probability intervals are NP-hard, even for polytrees. In this paper we focus on such inferences, and propose: 1) a substantial improvement on Tessems A / R…

Artificial Intelligence · Computer Science 2012-12-21 Jose Carlos Ferreira da Rocha , Fabio Gagliardi Cozman , Cassio Polpo de Campos

The $k$-d tree is one of the oldest and most widely used data structures for nearest neighbor search. It partitions Euclidean space into axis-aligned rectangular cells. There are two standard ways to find the nearest neighbor to a query in…

Data Structures and Algorithms · Computer Science 2026-05-13 Marco Bazzani , Sanjoy Dasgupta

We consider the problem of finding an edge in a hidden undirected graph $G = (V, E)$ with $n$ vertices, in a model where we only allowed queries that ask whether or not a subset of vertices contains an edge. We study the non-adaptive model…

Data Structures and Algorithms · Computer Science 2022-07-07 Ron Kupfer , Noam Nisan

In this paper we describe an algorithm that embeds a graph metric $(V,d_G)$ on an undirected weighted graph $G=(V,E)$ into a distribution of tree metrics $(T,D_T)$ such that for every pair $u,v\in V$, $d_G(u,v)\leq d_T(u,v)$ and…

Data Structures and Algorithms · Computer Science 2017-05-29 Guy E. Blelloch , Yan Gu , Yihan Sun

Long-horizon planning in realistic environments requires the ability to reason over sequential tasks in high-dimensional state spaces with complex dynamics. Classical motion planning algorithms, such as rapidly-exploring random trees, are…

Robotics · Computer Science 2020-10-14 Brian Ichter , Pierre Sermanet , Corey Lynch

Levin Tree Search (LTS) is a search algorithm that makes use of a policy (a probability distribution over actions) and comes with a theoretical guarantee on the number of expansions before reaching a goal node, depending on the quality of…

Machine Learning · Computer Science 2024-11-13 Laurent Orseau , Marcus Hutter , Levi H. S. Lelis

In collective tree exploration, a team of $k$ mobile agents is tasked to go through all edges of an unknown tree as fast as possible. An edge of the tree is revealed to the team when one agent becomes adjacent to that edge. The agents start…

Data Structures and Algorithms · Computer Science 2023-11-01 Romain Cosson

This paper presents enhancements to the projection pursuit tree classifier and visual diagnostic methods for assessing their impact in high dimensions. The original algorithm uses linear combinations of variables in a tree structure where…

Machine Learning · Statistics 2026-03-16 Natalia da Silva , Dianne Cook , Eun-Kyung Lee

Learned indexes leverage machine learning models to accelerate query answering in databases, showing impressive practical performance. However, theoretical understanding of these methods remains incomplete. Existing research suggests that…

Databases · Computer Science 2024-10-23 Luis Croquevielle , Guang Yang , Liang Liang , Ali Hadian , Thomas Heinis

The key challenge in neural architecture search (NAS) is designing how to explore wisely in the huge search space. We propose a new NAS method called TNAS (NAS with trees), which improves search efficiency by exploring only a small number…

Artificial Intelligence · Computer Science 2022-04-12 Guocheng Qian , Xuanyang Zhang , Guohao Li , Chen Zhao , Yukang Chen , Xiangyu Zhang , Bernard Ghanem , Jian Sun

We study the Short Path Packing problem which asks, given a graph $G$, integers $k$ and $\ell$, and vertices $s$ and $t$, whether there exist $k$ pairwise internally vertex-disjoint $s$-$t$ paths of length at most $\ell$. The problem has…

Data Structures and Algorithms · Computer Science 2024-04-17 Michael Kiran Huber

Let $T$ be a tree space (or tree network) represented by a weighted tree with $t$ vertices, and $S$ be a set of $n$ stochastic points in $T$, each of which has a fixed location with an independent existence probability. We investigate two…

Computational Geometry · Computer Science 2016-12-16 Jie Xue , Yuan Li

{\em Algorithms with predictions} incorporate machine learning predictions into algorithm design. A plethora of recent works incorporated predictions to improve on worst-case optimal bounds for online problems. In this paper, we initiate…

Data Structures and Algorithms · Computer Science 2023-09-12 Monika Henzinger , Barna Saha , Martin P. Seybold , Christopher Ye

Several problems that are NP-hard on general graphs are efficiently solvable on graphs with bounded treewidth. Efforts have been made to generalize treewidth and the related notion of pathwidth to digraphs. Directed treewidth, DAG-width and…

Data Structures and Algorithms · Computer Science 2026-05-22 Shiva Kintali , Nishad Kothari , Akash Kumar

Based on decision trees, many fields have arguably made tremendous progress in recent years. In simple words, decision trees use the strategy of "divide-and-conquer" to divide the complex problem on the dependency between input features and…

Machine Learning · Computer Science 2021-01-22 Jinxiong Zhang

Given a directed graph, G=(V,E), a path query, path(u,v), returns whether there is a directed path from u to v in G, for u,v vertices in V. Given only V, exactly learning all the edges in G using path queries is often impossible, since path…

Data Structures and Algorithms · Computer Science 2022-08-09 Ramtin Afshar , Michael T. Goodrich

In this paper, we consider the problem of compressing a trie while supporting the powerful \emph{locate} queries: to return the pre-order identifiers of all nodes reached by a path labeled with a given query pattern. Our result builds on…

Data Structures and Algorithms · Computer Science 2020-12-18 Nicola Prezza

Given a rooted tree and a ranking of its leaves, what is the minimum number of inversions of the leaves that can be attained by ordering the tree? This variation of the problem of counting inversions in arrays originated in mathematical…

Data Structures and Algorithms · Computer Science 2024-07-02 Ivan Hu , Dieter van Melkebeek , Andrew Morgan

Optimal path planning requires finding a series of feasible states from the starting point to the goal to optimize objectives. Popular path planning algorithms, such as Effort Informed Trees (EIT*), employ effort heuristics to guide the…

Recent papers have shown optimally-competitive on-line strategies for a robot traveling from a point $s$ to a point $t$ in certain unknown geometric environments. We consider the question: Having gained some partial information about the…

Combinatorics · Mathematics 2016-09-06 Avrim Blum , Prasad Chalasani