A Simple LP-Based Approximation Algorithm for the Matching Augmentation Problem

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This paper introduces a distributed operational solution for integrated transmission-distribution (ITD) system management. A fundamental challenge in designing distributed approaches for AC optimal power flow (OPF) problems in ITD systems is the nonconvexi ...

Community structure is a key feature omnipresent in real-world network data. Plethora of methods have been proposed to reveal subsets of densely interconnected nodes using criteria such as the modularity index. These approaches have been successful for und ...

We investigate group fairness regularizers in federated learning, aiming to train a globally fair model in a distributed setting. Ensuring global fairness in distributed training presents unique challenges, as fairness regularizers typically involve probab ...

As the applications of biometric recognition systems are increasing rapidly, there is a growing need to secure the sensitive data used within these systems. Considering privacy challenges in such systems, different biometric template protection (BTP) schem ...

The adaptive social learning paradigm helps model how networked agents are able to form opinions on a state of nature and track its drifts in a changing environment. In this framework, the agents repeatedly update their beliefs based on private observation ...

The arise of disagreement is an emergent phenomenon that can be observed within a growing social group and, beyond a certain threshold, can lead to group fragmentation. To better understand how disagreement emerges, we introduce an analytically tractable m ...

Large deep neural network (DNN) models pose the key challenge to energy efficiency due to the significantly higher energy consumption of off-chip DRAM accesses than arithmetic or SRAM operations. It motivates the intensive research on model compression wit ...

Loop closure detection helps simultaneous localization and mapping systems reduce map and state uncertainty via recognizing previously visited places along the path of a mobile robot. However, visual loop closure detection is susceptible to scenes with dyn ...

Existing works for depth estimation and image deblurring in the presence of depth-dependent blur work with the assumption of a multi-layered scene wherein each layer is modeled in the form of a fronto-parallel plane. In this work, we attempt to relax these ...

Principal Component Analysis (PCA) is a powerful tool in statistics and machine learning. While existing study of PCA focuses on the recovery of principal components and their associated eigenvalues, there are few precise characterizations of individual pr ...

The use of attributed quotes is the most direct and least filtered pathway of information propagation in news. Consequently, quotes play a central role in the conception, reception, and analysis of news stories. Since quotes provide a more direct window in ...

Convolutional neural networks (CNNs) have been demonstrated to be highly effective in the field of pulmonary nodule detection. However, existing CNN based pulmonary nodule detection methods lack the ability to capture long-range dependencies, which is vita ...

Background. Latencies of motor evoked potentials (MEPs) can provide insights into the motor neuronal pathways activated by transcranial magnetic stimulation. Notwithstanding its clinical relevance, accurate, unbiased methods to automatize latency detection ...

The RESTRICTED ASSIGNMENT problem is a prominent special case of SCHEDULING ON UNRELATED PARALLEL MACHINES. For the strongest known linear programming relaxation, the configuration LP, we improve the nonconstructive bound on its integrality gap from 1.9412 ...

Internet-of-Things (IoT) devices and applications are being deployed in our homes and workplaces. These devices often rely on continuous data collection to feed machine learning models. However, this approach introduces several privacy and efficiency chall ...

Knapsack problems give a simple framework for decision making. A classical example is the min-knapsack problem (MinKnap): choose a subset of items with minimum total cost, whose total profit is above a given threshold. While this model successfully general ...

This article studies the Cauchy problem for systems of semi-linear wave equations on R3+1 with nonlinear terms satisfying the null conditions. We construct future global-in-time classical solutions with arbitrarily large initial energy. The choice of the l ...

Nowadays, diffractive optical elements are used for a variety of applications because of their high design flexibility, compact size, and mass productivity. At the same time, they require having high and complex optical functionalities such as a large numb ...

A medical student learning to perform a laparoscopic procedure or a recently paralyzed user of a powered wheelchair must learn to operate machinery via interfaces that translate their actions into commands for an external device. Since the user’s actions a ...

It is often desirable for humanoid robots to have dexterous hands and perform human-like grasps. This requires a deliberate design of hands, in addition to a good actuation system and an efficient 3D vision system. In this paper, we present a simple method ...

A Simple LP-Based Approximation Algorithm for the Matching Augmentation Problem

Chattez avec Graph Search

Advancing Distributed AC Optimal Power Flow for Integrated Transmission-Distribution Systems

Community detection for directed networks revisited using bimodularity

Global Group Fairness in Federated Learning via Function Tracking

Measuring Linkability of Protected Biometric Templates Using Maximal Leakage

Discovering Influencers in Opinion Formation Over Social Graphs

Disagreement and fragmentation in growing groups

Non-Structured DNN Weight Pruning--Is It Beneficial in Any Platform?

PlaceNet: A multi-scale semantic-aware model for visual loop closure detection

Multi-planar geometry and latent image recovery from a single motion-blurred image

AN l(p) THEORY OF PCA AND SPECTRAL CLUSTERING

Quote Erat Demonstrandum: AWeb Interface for Exploring the Quotebank Corpus

LSSANet: A Long Short Slice-Aware Network for Pulmonary Nodule Detection

An automatized method to determine latencies of motor-evoked potentials under physiological and pathophysiological conditions

A Quasi-Polynomial Approximation For The Restricted Assignment Problem

A Hybrid Deep Learning Architecture for Privacy-Preserving Mobile Analytics

On approximation algorithms and polyhedral relaxations for knapsack problems, and clustered planarity testing

On Classical Global Solutions of Nonlinear Wave Equations with Large Data

Design and Analysis of Binary Fan-out Gratings based on Step-Transition Perturbation Approach

The dynamics of motor learning through the formation of internal models

Design of a Flexible Articulated Robotic Hand for a Humanoid Robot