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We propose a query learning algorithm for ordered multi-terminal binary decision diagrams (OMTBDDs) using at most n equivalence and 2n(l\lcei\log_2 m\rceil+ 3n) membership queries by extending the algorithm for ordered binary decision…

Machine Learning · Computer Science 2023-03-07 Atsuyoshi Nakamura

A long-investigated problem in circuit complexity theory is to decompose an $n$-input or $n$-variable Majority Boolean function (call it $M_n$) using $k$-input ones ($M_k$), $k < n$, where the objective is to achieve the decomposition using…

Logic in Computer Science · Computer Science 2025-04-07 Anupam Chattopadhyay , Debjyoti Bhattacharjee , Subhamoy Maitra

It is known that greedy methods perform well for maximizing monotone submodular functions. At the same time, such methods perform poorly in the face of non-monotonicity. In this paper, we show - arguably, surprisingly - that invoking the…

Machine Learning · Computer Science 2017-04-07 Moran Feldman , Christopher Harshaw , Amin Karbasi

Decision diagrams for classification have some notable advantages over decision trees, as their internal connections can be determined at training time and their width is not bound to grow exponentially with their depth. Accordingly,…

Machine Learning · Computer Science 2022-05-31 Alexandre M. Florio , Pedro Martins , Maximilian Schiffer , Thiago Serra , Thibaut Vidal

We consider a large distributed service system consisting of $n$ homogeneous servers with infinite capacity FIFO queues. Jobs arrive as a Poisson process of rate $\lambda n/k_n$ (for some positive constant $\lambda$ and integer $k_n$). Each…

Performance · Computer Science 2019-10-23 Martin Zubeldia

In distributed learning, the goal is to perform a learning task over data distributed across multiple nodes with minimal (expensive) communication. Prior work (Daume III et al., 2012) proposes a general model that bounds the communication…

Machine Learning · Computer Science 2012-04-17 Hal Daume , Jeff M. Phillips , Avishek Saha , Suresh Venkatasubramanian

Robustness to distributional shift is one of the key challenges of contemporary machine learning. Attaining such robustness is the goal of distributionally robust optimization, which seeks a solution to an optimization problem that is…

Machine Learning · Statistics 2020-03-24 Johannes Kirschner , Ilija Bogunovic , Stefanie Jegelka , Andreas Krause

Balanced incomplete block designs (BIBDs) are a class of designs with v treatments and b blocks of size k that are optimal with regards to a wide range of optimality criteria, but it is not clear which designs to choose for combinations of…

Statistics Theory · Mathematics 2019-02-13 Sera Aylin Cakiroglu , Peter J Cameron

In this paper, we present a novel and efficient algorithm to find the k longest (shortest) paths between sources and sinks in a directed acyclic graph (DAG). The algorithm does not enumerate paths therefore it is especially useful for very…

Data Structures and Algorithms · Computer Science 2013-01-03 Fatih Kocan

Over the last decade, PageRank has gained importance in a wide range of applications and domains, ever since it first proved to be effective in determining node importance in large graphs (and was a pioneering idea behind Google's search…

Distributed, Parallel, and Cluster Computing · Computer Science 2015-11-26 Atish Das Sarma , Anisur Rahaman Molla , Gopal Pandurangan , Eli Upfal

Boolean networks can be viewed as functions on the set of binary strings of a given length, described via logical rules. They were introduced as dynamic models into biology, in particular as logical models of intracellular regulatory…

Dynamical Systems · Mathematics 2025-04-16 J. García Galofre , M. Pérez Millán , A. Galarza Rial , R. Laubenbacher , A. Dickenstein

Distributionally robust optimization (DRO) has been introduced for solving stochastic programs where the distribution of the random parameters is unknown and must be estimated by samples from that distribution. A key element of DRO is the…

Optimization and Control · Mathematics 2019-01-09 Xi Chen , Qihang Lin , Guanglin Xu

Combinatorial algorithms for minimization of functions of many variables, which take their values in finite totally ordered sets, are developed. For that the decomposition of the functions by Boolean polynomials is used. The modified SFM…

Optimization and Control · Mathematics 2007-06-13 Boris Zalesky

We study the problem of partitioning a small sample of $n$ individuals from a mixture of $k$ product distributions over a Boolean cube $\{0, 1\}^K$ according to their distributions. Each distribution is described by a vector of allele…

Machine Learning · Computer Science 2008-02-21 Shuheng Zhou

We give the first polynomial-time algorithm for performing linear or polynomial regression resilient to adversarial corruptions in both examples and labels. Given a sufficiently large (polynomial-size) training set drawn i.i.d. from…

Machine Learning · Computer Science 2020-06-05 Adam Klivans , Pravesh K. Kothari , Raghu Meka

In many choice modeling applications, people demand is frequently characterized as multiple discrete, which means that people choose multiple items simultaneously. The analysis and prediction of people behavior in multiple discrete choice…

Econometrics · Economics 2023-06-08 Hung Tran , Tien Mai

Data-driven Distributionally Robust Optimization (DD-DRO) via optimal transport has been shown to encompass a wide range of popular machine learning algorithms. The distributional uncertainty size is often shown to correspond to the…

Machine Learning · Statistics 2021-05-12 Jose Blanchet , Yang Kang , Fan Zhang , Fei He , Zhangyi Hu

The problem "Given a Boolean function $f$ of $n$ variables by its truth table vector. Find (if exists) a vector $\alpha \in \{0,1\}^n$ of maximal (or minimal) weight, such that $f(\alpha)= 1$." is considered here. It is closely related to…

Discrete Mathematics · Computer Science 2020-02-17 Valentin Bakoev

In this paper we study polynomial identity testing of sums of $k$ read-once algebraic branching programs ($\Sigma_k$-RO-ABPs), generalizing the work in (Shpilka and Volkovich 2008,2009), who considered sums of $k$ read-once formulas…

Computational Complexity · Computer Science 2009-12-15 Maurice Jansen , Youming Qiao , Jayalal Sarma

This paper introduces new technique for efficient calculation of different Shannon information measures which operates Binary Decision Diagrams (BDDs). We offer an algorithm of BDD reordering which demonstrates the improvement of the…

Other Computer Science · Computer Science 2007-10-15 Denis V. Popel
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