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Boosting Trees are one of the most successful statistical learning approaches that involve sequentially growing an ensemble of simple regression trees (i.e., "weak learners"). However, gradient boosted trees are not yet available for…

Speculative decoding is a technique to leverage hardware concurrency in order to enable multiple steps of token generation in a single forward pass, thus improving the efficiency of large-scale autoregressive (AR) Transformer models.…

Machine Learning · Computer Science 2025-10-29 Yangchao Wu , Zongyue Qin , Alex Wong , Stefano Soatto

We study the problem of constructing universal Steiner trees for undirected graphs. Given a graph $G$ and a root node $r$, we seek a single spanning tree $T$ of minimum {\em stretch}, where the stretch of $T$ is defined to be the maximum…

Data Structures and Algorithms · Computer Science 2015-03-03 Costas Busch , Chinmoy Dutta , Jaikumar Radhakrishnan , Rajmohan Rajaraman , Srivathsan Srinivasagopalan

The class of self-nested trees presents remarkable compression properties because of the systematic repetition of subtrees in their structure. In this paper, we provide a better combinatorial characterization of this specific family of…

Data Structures and Algorithms · Computer Science 2018-10-26 Romain Azaïs , Jean-Baptiste Durand , Christophe Godin

Decision trees and randomized forests are widely used in computer vision and machine learning. Standard algorithms for decision tree induction optimize the split functions one node at a time according to some splitting criteria. This greedy…

Machine Learning · Computer Science 2015-11-13 Mohammad Norouzi , Maxwell D. Collins , Matthew Johnson , David J. Fleet , Pushmeet Kohli

In the field of decision trees, most previous studies have difficulty ensuring the statistical optimality of a prediction of new data and suffer from overfitting because trees are usually used only to represent prediction functions to be…

Machine Learning · Computer Science 2023-06-13 Yuta Nakahara , Shota Saito , Naoki Ichijo , Koki Kazama , Toshiyasu Matsushima

Decision tree learning is a widely used approach in machine learning, favoured in applications that require concise and interpretable models. Heuristic methods are traditionally used to quickly produce models with reasonably high accuracy.…

Dynamic tree data structures maintain a forest while supporting insertion and deletion of edges and a broad set of queries in $O(\log n)$ time per operation. Such data structures are at the core of many modern algorithms. Recent work has…

Data Structures and Algorithms · Computer Science 2025-06-23 Humza Ikram , Andrew Brady , Daniel Anderson , Guy Blelloch

We discuss several connections between discrete and continuous random trees. In the discrete setting, we focus on Galton-Watson trees under various conditionings. In particular, we present a simple approach to Aldous' theorem giving the…

Probability · Mathematics 2007-05-23 Jean-Francois Le Gall

We focus on the average-case analysis: A function w : V -> Z+ is given which defines the likelihood for a node to be the one marked, and we want the strategy that minimizes the expected number of queries. Prior to this paper, very little…

Data Structures and Algorithms · Computer Science 2009-08-10 Ferdinando Cicalese , Tobias Jacobs , Eduardo Laber , Marco Molinaro

In this paper, we propose an explicit, non-strict representation of search trees in constraint-logic object-oriented programming. Our search tree representation includes both the non-deterministic and deterministic behaviour during…

Programming Languages · Computer Science 2020-09-23 Jan C. Dageförde , Finn Teegen

Software-Defined Networking (SDN) enables flexible network resource allocations for traffic engineering, but at the same time the scalability problem becomes more serious since traffic is more difficult to be aggregated. Those crucial…

Networking and Internet Architecture · Computer Science 2014-05-09 Liang-Hao Huang , Hui-Ju Hung , Chih-Chung Lin , De-Nian Yang

Motion Planning is necessary for robots to complete different tasks. Rapidly-exploring Random Tree (RRT) and its variants have been widely used in robot motion planning due to their fast search in state space. However, they perform not well…

Robotics · Computer Science 2022-05-19 Zhirui Sun , Jiankun Wang , Max Q. -H. Meng

We propose dynamical systems trees (DSTs) as a flexible class of models for describing multiple processes that interact via a hierarchy of aggregating parent chains. DSTs extend Kalman filters, hidden Markov models and nonlinear dynamical…

Machine Learning · Computer Science 2012-07-19 Andrew Howard , Tony S. Jebara

In 1996, Bodlaender showed the celebrated result that an optimal tree decomposition of a graph of bounded treewidth can be found in linear time. The algorithm is based on an algorithm of Bodlaender and Kloks that computes an optimal tree…

Data Structures and Algorithms · Computer Science 2020-03-19 Ernst Althaus , Sarah Ziegler

We consider the model of random trees introduced by Devroye [SIAM J. Comput. 28 (1999) 409-432]. The model encompasses many important randomized algorithms and data structures. The pieces of data (items) are stored in a randomized fashion…

Probability · Mathematics 2012-11-05 Nicolas Broutin , Cecilia Holmgren

Binary search trees (BSTs) are fundamental data structures whose performance is largely governed by tree height. We introduce a block model for constructing BSTs by embedding internal BSTs into the nodes of an external BST -- a structure…

Probability · Mathematics 2026-03-17 John Peca-Medlin , Chenyang Zhong

Ordinals can help prove termination for dependently typed programs. Brouwer trees are a particular ordinal notation that make it very easy to assign sizes to higher order data structures. They extend natural numbers with a limit…

Programming Languages · Computer Science 2023-12-13 Joseph Eremondi

Recently proposed budding tree is a decision tree algorithm in which every node is part internal node and part leaf. This allows representing every decision tree in a continuous parameter space, and therefore a budding tree can be jointly…

Machine Learning · Computer Science 2014-12-22 Ozan İrsoy , Ethem Alpaydın

Taking into account future risk is essential for an autonomously operating robot to find online not only the best but also a safe action to execute. In this paper, we build upon the recently introduced formulation of probabilistic…

Artificial Intelligence · Computer Science 2024-11-12 Andrey Zhitnikov , Vadim Indelman