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We give lower bounds for the density $p_T(x,y)$ of the law of $X_t$, the solution of $dX_t=\sigma (X_t) dB_t+b(X_t) dt,X_0=x,$ under the following local ellipticity hypothesis: there exists a deterministic differentiable curve $x_t, 0\leq…

Probability · Mathematics 2007-05-23 Vlad Bally

Interpretability of AI models allows for user safety checks to build trust in such AIs. In particular, Decision Trees (DTs) provide a global look at the learned model and transparently reveal which features of the input are critical for…

Machine Learning · Computer Science 2024-01-23 Hector Kohler , Riad Akrour , Philippe Preux

Random forests construct each tree with a different, randomised representation of the feature space. Their uniform voting cannot correct errors in regions where trees with incorrect representations probabilistically outnumber correct ones,…

Machine Learning · Computer Science 2026-05-28 Youngjoon Park

Short spanning trees subject to additional constraints are important building blocks in various approximation algorithms. Especially in the context of the Traveling Salesman Problem (TSP), new techniques for finding spanning trees with…

Data Structures and Algorithms · Computer Science 2023-09-13 Martin Nägele , Rico Zenklusen

This paper considers the $\varepsilon$-differentially private (DP) release of an approximate cumulative distribution function (CDF) of the samples in a dataset. We assume that the true (approximate) CDF is obtained after lumping the data…

Information Theory · Computer Science 2024-10-07 V. Arvind Rameshwar , Anshoo Tandon , Abhay Sharma

We investigate the problem of best policy identification in discounted linear Markov Decision Processes in the fixed confidence setting under a generative model. We first derive an instance-specific lower bound on the expected number of…

Machine Learning · Computer Science 2022-08-12 Jerome Taupin , Yassir Jedra , Alexandre Proutiere

We consider dynamic random trees constructed using an attachment function $f : \mathbb{N} \to \mathbb{R}_+$ where, at each step of the evolution, a new vertex attaches to an existing vertex $v$ in the current tree with probability…

Probability · Mathematics 2022-08-17 Sayan Banerjee , Shankar Bhamidi , Iain Carmichael

We consider random walks indexed by arbitrary finite random or deterministic trees. We derive a simple sufficient criterion which ensures that the maximal displacement of the tree-indexed random walk is determined by a single large jump.…

Probability · Mathematics 2018-06-20 Pascal Maillard

While obtaining optimal algorithms for the most important problems in the LOCAL model has been one of the central goals in the area of distributed algorithms since its infancy, tight complexity bounds are elusive for many problems even when…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-05-06 Sebastian Brandt , Ananth Narayanan

This paper considers limit theorems associated with subgraph counts in the age-dependent random connection model. First, we identify regimes where the count of sub-trees converges weakly to a stable random variable under suitable…

Probability · Mathematics 2024-09-10 Christian Hirsch , Takashi Owada

Consider an inhomogeneous multi-species TASEP with drift to the left, and define a height function which equals the maximum species number to the left of a lattice site. For each fixed time, the multi-point distributions of these height…

Probability · Mathematics 2020-12-17 Jeffrey Kuan

We explore the tree limits recently defined by Elek and Tardos. In particular, we find tree limits for many classes of random trees. We give general theorems for three classes of conditional Galton-Watson trees and simply generated trees,…

Probability · Mathematics 2021-07-01 Svante Janson

In the critical beta-splitting model of a random $n$-leaf rooted tree, clades are recursively split into sub-clades, and a clade of $m$ leaves is split into sub-clades containing $i$ and $m-i$ leaves with probabilities $\propto 1/(i(m-i))$.…

Probability · Mathematics 2024-12-18 David Aldous , Svante Janson

We prove that several natural graph classes have tree-decompositions with minimum width such that each bag has bounded treewidth. For example, every planar graph has a tree-decomposition with minimum width such that each bag has treewidth…

Combinatorics · Mathematics 2025-12-01 Kevin Hendrey , David R. Wood

The depth-weighted tree DWT($f$) with weight function $f:\{0,1,2,\ldots\}\to (0,\infty)$ is a dynamic random tree grown from a root $r$ where vertices arrive consecutively and every new vertex attaches to a parent $u$ with probability…

Probability · Mathematics 2026-02-18 Lyuben Lichev , Amitai Linker , Bas Lodewijks , Dieter Mitsche

Given a graph $G$ and a real number $0\le p\le 1$, we define the random set $B_p(G)\subset V(G)$ by including each vertex independently and with probability $p$. We investigate the probability that the random set $B_p(G)$ is a zero forcing…

Combinatorics · Mathematics 2022-08-30 Bryan Curtis , Luyining Gan , Jamie Haddock , Rachel Lawrence , Sam Spiro

Let $\mathcal{B}$ be the set of rooted trees containing an infinite binary subtree starting at the root. This set satisfies the metaproperty that a tree belongs to it if and only if its root has children $u$ and $v$ such that the subtrees…

Probability · Mathematics 2020-06-11 Tobias Johnson , Moumanti Podder , Fiona Skerman

We discuss a notion of convergence for binary trees that is based on subtree sizes. In analogy to recent developments in the theory of graphs, posets and permutations we investigate some general aspects of the topology, such as a…

Combinatorics · Mathematics 2024-02-14 Rudolf Grübel

Proximal policy optimization (PPO) is one of the most successful deep reinforcement-learning methods, achieving state-of-the-art performance across a wide range of challenging tasks. However, its optimization behavior is still far from…

Machine Learning · Computer Science 2020-01-15 Yuhui Wang , Hao He , Chao Wen , Xiaoyang Tan

Large Language Models (LLMs) have shown remarkable reasoning capabilities through Reinforcement Learning with Verifiable Rewards (RLVR) methods. However, a key limitation of existing approaches is that rewards defined at the full trajectory…

Machine Learning · Computer Science 2025-09-30 Zhicheng Yang , Zhijiang Guo , Yinya Huang , Xiaodan Liang , Yiwei Wang , Jing Tang