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Decision Trees (DTs) are commonly used for many machine learning tasks due to their high degree of interpretability. However, learning a DT from data is a difficult optimization problem, as it is non-convex and non-differentiable.…

Machine Learning · Computer Science 2024-08-20 Sascha Marton , Stefan Lüdtke , Christian Bartelt , Heiner Stuckenschmidt

Identifying optimal basic feasible solutions to linear programming problems is a critical task for mixed integer programming and other applications. The crossover method, which aims at deriving an optimal extreme point from a suboptimal…

Optimization and Control · Mathematics 2025-12-23 Dongdong Ge , Chengwenjian Wang , Zikai Xiong , Yinyu Ye

Our work addresses the well-known open problem of distributed computing of bilinear functions of two correlated sources ${\bf A}$ and ${\bf B}$. In a setting with two nodes, with the first node having access to ${\bf A}$ and the second to…

Information Theory · Computer Science 2026-05-12 Derya Malak

This paper investigates the a-posteriori analysis of Branch-and-Bound~(BB) trees to extract structural information about the feasible region of mixed-binary linear programs. We introduce three novel outer approximations of the feasible…

Optimization and Control · Mathematics 2025-10-14 Marius Roland , Nagisa Sugishita , Alexandre Forel , Youssouf Emine , Ricardo Fukasawa , Thibaut Vidal

In this paper, we introduce an achievability bound on the frame error rate of random tree code ensembles under a sequential decoding algorithm with a hard computational limit and consider the optimization of the random tree code ensembles…

Information Theory · Computer Science 2025-01-23 B. Tan Bacinoglu

A lossy compression algorithm for binary redundant memoryless sources is presented. The proposed scheme is based on sparse graph codes. By introducing a nonlinear function, redundant memoryless sequences can be compressed. We propose a…

Information Theory · Computer Science 2011-08-19 Kazushi Mimura

We address the problem of learning binary decision trees that partition data for some downstream task. We propose to learn discrete parameters (i.e., for tree traversals and node pruning) and continuous parameters (i.e., for tree split…

Machine Learning · Computer Science 2021-06-15 Valentina Zantedeschi , Matt J. Kusner , Vlad Niculae

The {\sc Directed Maximum Leaf Out-Branching} problem is to find an out-branching (i.e. a rooted oriented spanning tree) in a given digraph with the maximum number of leaves. In this paper, we improve known parameterized algorithms and…

Data Structures and Algorithms · Computer Science 2007-07-10 Noga Alon , Fedor V. Fomin , Gregory Gutin , Michael Krivelevich , Saket Saurabh

Let $P = \{p(i)\}$ be a measure of strictly positive probabilities on the set of nonnegative integers. Although the countable number of inputs prevents usage of the Huffman algorithm, there are nontrivial $P$ for which known methods find a…

Information Theory · Computer Science 2016-11-17 Michael B. Baer

We study the problem of computing the tightest upper and lower bounds on the probability that the sum of $n$ dependent Bernoulli random variables exceeds an integer $k$. Under knowledge of all pairs of bivariate distributions denoted by a…

Optimization and Control · Mathematics 2019-10-16 Divya Padmanabhan , Karthik Natarajan

The network coding problem asks whether data throughput in a network can be increased using coding (compared to treating bits as commodities in a flow). While it is well-known that a network coding advantage exists in directed graphs, the…

Computational Complexity · Computer Science 2025-10-22 Mark Braverman , Zhongtian He

We consider random binary trees that appear as the output of certain standard algorithms for sorting and searching if the input is random. We introduce the subtree size metric on search trees and show that the resulting metric spaces…

Probability · Mathematics 2014-05-06 Rudolf Grübel

We solve a problem of Krivelevich, Kwan and Sudakov [SIAM Journal on Discrete Mathematics 31 (2017), 155-171] concerning the threshold for the containment of all bounded degree spanning trees in the model of randomly perturbed dense graphs.…

Combinatorics · Mathematics 2019-02-19 Julia Böttcher , Jie Han , Yoshiharu Kohayakawa , Richard Montgomery , Olaf Parczyk , Yury Person

We consider the problem of learning optimal binary classification trees. Literature on the topic has burgeoned in recent years, motivated both by the empirical suboptimality of heuristic approaches and the tremendous improvements in…

Machine Learning · Statistics 2020-05-14 Sina Aghaei , Andres Gomez , Phebe Vayanos

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

Graphical data arises naturally in several modern applications, including but not limited to internet graphs, social networks, genomics and proteomics. The typically large size of graphical data argues for the importance of designing…

Information Theory · Computer Science 2021-07-20 Payam Delgosha , Venkat Anantharam

The problem of stabilizing an unstable plant over a noisy communication link is an increasingly important one that arises in applications of networked control systems. Although the work of Schulman and Sahai over the past two decades, and…

Information Theory · Computer Science 2012-02-28 Ravi Teja Sukhavasi , Babak Hassibi

Assuming iterative decoding for binary erasure channels (BECs), a novel tree-based technique for upper bounding the bit error rates (BERs) of arbitrary, finite low-density parity-check (LDPC) codes is provided and the resulting bound can be…

Information Theory · Computer Science 2007-07-13 Chih-Chun Wang , Sanjeev R. Kulkarni , H. Vincent Poor

We present a compressed representation of tries based on top tree compression [ICALP 2013] that works on a standard, comparison-based, pointer machine model of computation and supports efficient prefix search queries. Namely, we show how to…

Data Structures and Algorithms · Computer Science 2019-09-23 Philip Bille , Inge Li Gørtz , Paweł Gawrychowski , Gad M. Landau , Oren Weimann

We present a new lossy compressor for discrete sources. For coding a source sequence $x^n$, the encoder starts by assigning a certain cost to each reconstruction sequence. It then finds the reconstruction that minimizes this cost and…

Information Theory · Computer Science 2009-01-19 Shirin Jalali , Andrea Montanari , Tsachy Weissman