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Proximal nested sampling was introduced recently to open up Bayesian model selection for high-dimensional problems such as computational imaging. The framework is suitable for models with a log-convex likelihood, which are ubiquitous in the…

Methodology · Statistics 2023-07-31 Jason D. McEwen , Tobías I. Liaudat , Matthew A. Price , Xiaohao Cai , Marcelo Pereyra

We study the Convex Set Disjointness (CSD) problem, where two players have input sets taken from an arbitrary fixed domain~$U\subseteq \mathbb{R}^d$ of size $\lvert U\rvert = n$. Their mutual goal is to decide using minimum communication…

Data Structures and Algorithms · Computer Science 2019-09-10 Mark Braverman , Gillat Kol , Shay Moran , Raghuvansh R. Saxena

Federated learning (FL) learns a model jointly from a set of participating devices without sharing each other's privately held data. The characteristics of non-i.i.d. data across the network, low device participation, high communication…

Machine Learning · Computer Science 2024-01-02 Zhaonan Qu , Kaixiang Lin , Zhaojian Li , Jiayu Zhou , Zhengyuan Zhou

We consider online fractional covering problems with a convex objective, where the covering constraints arrive over time. Formally, we want to solve $\min\,\{f(x) \mid Ax\ge \mathbf{1},\, x\ge 0\},$ where the objective function…

Data Structures and Algorithms · Computer Science 2014-12-30 Niv Buchbinder , Shahar Chen , Anupam Gupta , Viswanath Nagarajan , Joseph , Naor

The online problem of computing the top eigenvector is fundamental to machine learning. In both adversarial and stochastic settings, previous results (such as matrix multiplicative weight update, follow the regularized leader, follow the…

Machine Learning · Computer Science 2017-09-19 Zeyuan Allen-Zhu , Yuanzhi Li

We work in the adaptive query model, where one is given a point set $P \subset \mathbb{R}^d$ and seeks to construct a data structure that can answer correctly and efficiently a sequence of adaptive queries. In this model, an adversary…

The goal of this work is to replace objects in an RGB-D scene with corresponding 3D models from a library. We approach this problem by first detecting and segmenting object instances in the scene using the approach from Gupta et al. [13].…

Computer Vision and Pattern Recognition · Computer Science 2015-02-17 Saurabh Gupta , Pablo Arbeláez , Ross Girshick , Jitendra Malik

The problem of pursuing a moving target is always one of the main topics in navigation. In the literatures, there are two well-known algorithms called Pure Pursuit and Pure Rendezvous navigation in the 3-dimensional space $\mathbb{R}^3$. In…

Differential Geometry · Mathematics 2012-07-11 Hassan Attarchi , Behroz Bidabad , Morteza MirMohammad Rezaii

In the (discrete) CNN problem, online requests appear as points in $\mathbb{R}^2$. Each request must be served before the next one is revealed. We have a server that can serve a request simply by aligning either its $x$ or $y$ coordinate…

Data Structures and Algorithms · Computer Science 2012-06-20 John Augustine , Nick Gravin

We consider linear search for an escaping target whose speed and initial position are unknown to the searcher. A searcher (an autonomous mobile agent) is initially placed at the origin of the real line and can move with maximum speed $1$ in…

Discrete Mathematics · Computer Science 2024-04-24 Jared Coleman , Dmitry Ivanov , Evangelos Kranakis , Danny Krizanc , Oscar Morales-Ponce

We discuss how well a given convex body B in a real d-dimensional vector space V can be approximated by a set X for which the membership question: ``given an x in V, does x belong to X?'' can be answered efficiently (in time polynomial in…

Metric Geometry · Mathematics 2007-05-23 Alexander Barvinok , Ellen Veomett

This paper addresses the problem of localization, which is inherently non-convex and non-smooth in a federated setting where the data is distributed across a multitude of devices. Due to the decentralized nature of federated environments,…

Machine Learning · Computer Science 2023-09-04 Reza Mirzaeifard , Naveen K. D. Venkategowda , Stefan Werner

We study the online convex covering problem and online convex packing problem. The (offline) convex covering problem is modeled by the following convex program: $\min_{x \in R_+^n} f(x) \ \text{s.t}\ A x \ge 1$, where $f : R_+^n \mapsto…

Data Structures and Algorithms · Computer Science 2015-04-15 T-H. Hubert Chan , Zhiyi Huang , Ning Kang

We consider the problem of adversarial bandit convex optimization, that is, online learning over a sequence of arbitrary convex loss functions with only one function evaluation for each of them. While all previous works assume known and…

Machine Learning · Computer Science 2022-02-15 Haipeng Luo , Mengxiao Zhang , Peng Zhao

We propose a new algorithm for the optimization of convex functions over a polyhedral set in Rn. The algorithm extends the spectral projected-gradient method with limited-memory BFGS iterates restricted to the present face whenever…

Optimization and Control · Mathematics 2016-11-18 Ewout van den Berg

We consider an online version of the geometric minimum hitting set problem that can be described as a game between an adversary and an algorithm. For some integers $d$ and $N$, let $P$ be the set of points in $(0, N)^d$ with integral…

Data Structures and Algorithms · Computer Science 2023-09-06 Shanli Alefkhani , Nima Khodaveisi , Mathieu Mari

We study the competitive facility location problem, where a firm aims to establish new facilities in a market already occupied by competitors. In this problem, customer behavior is crucial for making optimal location decisions. We explore a…

Optimization and Control · Mathematics 2024-08-07 Ba Luat Le , Tien Mai , Thuy Anh Ta , Minh Hoang Ha , Duc Minh Vu

In order to manipulate a deformable object, such as rope or cloth, in unstructured environments, robots need a way to estimate its current shape. However, tracking the shape of a deformable object can be challenging because of the object's…

Robotics · Computer Science 2020-11-03 Yixuan Wang , Dale McConachie , Dmitry Berenson

This work presents a novel Convolutional Neural Network (CNN) architecture and a training procedure to enable robust and accurate pose estimation of a noncooperative spacecraft. First, a new CNN architecture is introduced that has scored a…

Computer Vision and Pattern Recognition · Computer Science 2019-09-04 Tae Ha Park , Sumant Sharma , Simone D'Amico

With the development of robotics, there are growing needs for real time motion planning. However, due to obstacles in the environment, the planning problem is highly non-convex, which makes it difficult to achieve real time computation…

Optimization and Control · Mathematics 2018-05-22 Changliu Liu , Chung-Yen Lin , Masayoshi Tomizuka