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We give polynomial-time algorithms for the exact computation of lowest-energy (ground) states, worst margin violators, log partition functions, and marginal edge probabilities in certain binary undirected graphical models. Our approach…

Machine Learning · Computer Science 2009-09-29 Nicol N. Schraudolph , Dmitry Kamenetsky

It follows from the Marcus-Spielman-Srivastava proof of the Kadison-Singer conjecture that if $G=(V,E)$ is a $\Delta$-regular dense expander then there is an edge-induced subgraph $H=(V,E_H)$ of $G$ of constant maximum degree which is also…

Distributed, Parallel, and Cluster Computing · Computer Science 2021-03-09 Luca Becchetti , Andrea Clementi , Emanuele Natale , Francesco Pasquale , Luca Trevisan

Quantum key distribution promises unconditionally secure communications. However, as practical devices tend to deviate from their specifications, the security of some practical systems is no longer valid. In particular, an adversary can…

Quantum Physics · Physics 2015-06-16 Marcos Curty , Feihu Xu , Wei Cui , Charles Ci Wen Lim , Kiyoshi Tamaki , Hoi-Kwong Lo

Distributed model fitting refers to the process of fitting a mathematical or statistical model to the data using distributed computing resources, such that computing tasks are divided among multiple interconnected computers or nodes, often…

Computation · Statistics 2024-06-04 Xiaofei Wu , Rongmei Liang , Fabio Roli , Marcello Pelillo , Jing Yuan

We study the problem of allocating indivisible items on a path among agents. The objective is to find a fair and efficient allocation in which each agent's bundle forms a contiguous block on the line. We say that an instance is \emph{$(a,…

Computer Science and Game Theory · Computer Science 2025-01-14 Yasushi Kawase , Bodhayan Roy , Mohammad Azharuddin Sanpui

The construction of a well tuned probability distributions is illustrated in synthetic way, these probability distributions produce faithful realizations of the impact point distributions for particles in silicon strip detector. Their use…

Instrumentation and Detectors · Physics 2016-05-17 Gregorio Landi , Giovanni E. Landi

Diffusion-based generative models learn to iteratively transfer unstructured noise to a complex target distribution as opposed to Generative Adversarial Networks (GANs) or the decoder of Variational Autoencoders (VAEs) which produce samples…

Machine Learning · Computer Science 2022-10-26 Sarthak Mittal , Guillaume Lajoie , Stefan Bauer , Arash Mehrjou

In many applications, the curvature of the space supporting the data makes the statistical modelling challenging. In this paper we discuss the construction and use of probability distributions wrapped around manifolds using exponential…

Methodology · Statistics 2022-10-11 Emmanuel Chevallier , Didong Li , Yulong Lu , David B. Dunson

Edge inference has become more widespread, as its diverse applications range from retail to wearable technology. Clusters of networked resource-constrained edge devices are becoming common, yet no system exists to split a DNN across these…

Networking and Internet Architecture · Computer Science 2022-10-25 Arjun Parthasarathy , Bhaskar Krishnamachari

In this paper, we prove a general hardness amplification scheme for optimization problems based on the technique of direct products. We say that an optimization problem $\Pi$ is direct product feasible if it is possible to efficiently…

Computational Complexity · Computer Science 2019-08-28 Elazar Goldenberg , Karthik C. S.

Multimodal tasks, such as image-text retrieval and generation, require embedding data from diverse modalities into a shared representation space. Aligning embeddings from heterogeneous sources while preserving shared and modality-specific…

Machine Learning · Computer Science 2024-12-03 Dongfang Zhao

In many distributed learning problems, the heterogeneous loading of computing machines may harm the overall performance of synchronous strategies. In this paper, we propose an effective asynchronous distributed framework for the…

Machine Learning · Statistics 2017-05-23 Bikash Joshi , Franck Iutzeler , Massih-Reza Amini

This paper considers the inverse problem of scattering of time-harmonic acoustic and electromagnetic plane waves by a bounded, inhomogeneous, penetrable obstacle with embedded objects inside. A new method is proposed to prove that the…

Analysis of PDEs · Mathematics 2017-06-14 Jiaqing Yang , Bo Zhang , Haiwen Zhang

We generalize the polynomial-time solvability of $k$-\textsc{Diverse Minimum s-t Cuts} (De Berg et al., ISAAC'23) to a wider class of combinatorial problems whose solution sets have a distributive lattice structure. We identify three…

Data Structures and Algorithms · Computer Science 2025-04-04 Mark de Berg , Andrés López Martínez , Frits Spieksma

Statistical inference from high-dimensional data with low-dimensional structures has recently attracted lots of attention. In machine learning, deep generative modeling approaches implicitly estimate distributions of complex objects by…

Statistics Theory · Mathematics 2022-02-21 Rong Tang , Yun Yang

We give a number of approximation metatheorems for monotone maximization problems expressible in the first-order logic, in substantially more general settings than the previously known. We obtain * constant-factor approximation algorithm in…

Discrete Mathematics · Computer Science 2021-10-12 Zdeněk Dvořák

On-device inference holds great potential for increased energy efficiency, responsiveness, and privacy in edge ML systems. However, due to less capable ML models that can be embedded in resource-limited devices, use cases are limited to…

This article is concerned with the time-harmonic electromagnetic (EM) scattering from a generic inhomogeneous medium. It is shown that if there is a right corner on the support of the medium, then it scatters every pair of incident EM…

Analysis of PDEs · Mathematics 2016-11-15 Hongyu Liu , Jingni Xiao

The Renyi, Shannon and Fisher spreading lengths of the classical or hypergeometric orthogonal polynomials, which are quantifiers of their distribution all over the orthogonality interval, are defined and investigated. These…

Mathematical Physics · Physics 2009-11-11 P. Sánchez-Moreno , J. S. Dehesa , D. Manzano , R. Yáñez

Belief propagation is known to perform extremely well in many practical statistical inference and learning problems using graphical models, even in the presence of multiple loops. The iterative use of belief propagation algorithm on loopy…

Information Theory · Computer Science 2013-02-13 Xiangqiong Shi , Dan Schonfeld , Daniela Tuninetti