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The Torch (Summer 2023), Crtp

Torch: The Civil Rights Team Project Newsletter

The Civil Rights Team Project Newsletter

"We help schools think and talk about issues related to race and skin color, national origin and ancestry, religion, disabilities, gender (including gender identity and expression), and sexual orientation."

• Civil Rights Team Spotlight
• Local Collaborations
• Civil Rights Team Shoutouts
• Thanking our Retiring Advisors
• Thanks for reading!

50 Years Of Title Ix And Women's Athletics At Holy Cross, Archives & Distinctive Collections, Lisa Villa

Exhibits

Two major events in 1972 brought major changes to the College of the Holy Cross: the passing of Title IX and the admission of women as students. This exhibit commmemorates the 50th anniversary of Title IX and continues the celebration of the 50th anniversary of coeducation at Holy Cross by highlighting the founding and growth of women’s athletics at the College.

The Effect Of China Retaliatory Tariffs On Donations From Farmers In The Central Region Of The United States, Jiayi Chen

Proceedings of the Jepson Undergraduate Conference on International Economics

The Trump administration launched a series of actions to raise import tariffs against major U.S. trading partners, particularly China. In response, China retaliated against the U.S. by imposing higher tariffs targeting exports produced in Republican-supporting counties. Soybeans and corn are two targeted agricultural exports with the same tariff rates. However, due to the drastic difference in export amount to China, farmers in counties dominating in producing soybeans would have more negative economic impacts than counties mainly producing corn. In this paper, I use individual farmers’ donations to examine the effect of this retaliatory tariff shock from the trade war on …

Clinician Satisfaction And Preference For Central Venous Catheter Systems Promoting Patient Safety, Ease-Of-Use And Reduced Clinician Error., Robert Wagner, Kimberly Alsbrooks, Erin Bacon, Matthew O'Brien, Klaus Hoerauf

HPD Articles

Objectives: Central venous catheters (CVC) are frequently utilized with limited data on user preferences. A simulation/survey-based study was conducted among anesthesia providers to evaluate attitudes toward general CVC system attributes, and satisfaction with elements of the most-commonly used and a novel CVC system. Methods: Forty providers completed a simulation using both CVC systems and a 29-item questionnaire, including multiple-choice, free-text, ranking, and Likert-like questions. Ranking scores were reported using a scale of 0 (least important/satisfactory) to 100 (most important/satisfactory). Statistical significances were evaluated via Wilcoxon signed-rank sum test. Results: Participants chose (mean±SD) patient safety (83.9 ± 25.3), ease-of-use (64.6 ± …

Digital Marketing Science, Stephanie Cobian

Title III Professional Development Reports

Marketing involves implementing diverse strategies to promote products and services, strengthen market presence, and attain business success. It combines advertising expertise, sales proficiency, and efficient product delivery. While traditional channels like print, TV, and radio remain relevant, the internet has transformed marketing through digital approaches. Digital marketing utilizes websites, social media, search engines, and applications, enabling interactive communication and incorporating customer feedback. It revolutionizes how businesses engage with consumers in a two-way interaction.

A Universal Unbiased Method For Classification From Aggregate Observations, Zixi Wei, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Xiaofeng Zhu, Heng Tao Shen

Machine Learning Faculty Publications

In conventional supervised classification, true labels are required for individual instances. However, it could be prohibitive to collect the true labels for individual instances, due to privacy concerns or unaffordable annotation costs. This motivates the study on classification from aggregate observations (CFAO), where the supervision is provided to groups of instances, instead of individual instances. CFAO is a generalized learning framework that contains various learning problems, such as multiple-instance learning and learning from label proportions. The goal of this paper is to present a novel universal method of CFAO, which holds an unbiased estimator of the classification risk for arbitrary …

Diversity-Enhancing Generative Network For Few-Shot Hypothesis Adaptation, Ruijiang Dong, Feng Liu, Haoang Chi, Tongliang Liu, Mingming Gong, Gang Niu, Masashi Sugiyama, Bo Han

Machine Learning Faculty Publications

Generating unlabeled data has been recently shown to help address the few-shot hypothesis adaptation (FHA) problem, where we aim to train a classifier for the target domain with a few labeled target-domain data and a well-trained source-domain classifier (i.e., a source hypothesis), for the additional information of the highly-compatible unlabeled data. However, the generated data of the existing methods are extremely similar or even the same. The strong dependency among the generated data will lead the learning to fail. In this paper, we propose a diversity-enhancing generative network (DEG-Net) for the FHA problem, which can generate diverse unlabeled data with …

Identifiability Of Label Noise Transition Matrix, Yang Liu, Hao Cheng, Kun Zhang

Machine Learning Faculty Publications

The noise transition matrix plays a central role in the problem of learning with noisy labels. Among many other reasons, a large number of existing solutions rely on the knowledge of it. Identifying and estimating the transition matrix without ground truth labels is a critical and challenging task. When label noise transition depends on each instance, the problem of identifying the instance-dependent noise transition matrix becomes substantially more challenging. Despite recently proposed solutions for learning from instance-dependent noisy labels, the literature lacks a unified understanding of when such a problem remains identifiable. The goal of this paper is to characterize …

Adaptive Compositional Continual Meta-Learning, Bin Wu, Jinyuan Fang, Xiangxiang Zeng, Shangsong Liang, Qiang Zhang

Machine Learning Faculty Publications

This paper focuses on continual meta-learning, where few-shot tasks are heterogeneous and sequentially available. Recent works use a mixture model for meta-knowledge to deal with the heterogeneity. However, these methods suffer from parameter inefficiency caused by two reasons: (1) the underlying assumption of mutual exclusiveness among mixture components hinders sharing meta-knowledge across heterogeneous tasks. (2) they only allow increasing mixture components and cannot adaptively filter out redundant components. In this paper, we propose an Adaptive Compositional Continual Meta-Learning (ACML) algorithm, which employs a compositional premise to associate a task with a subset of mixture components, allowing meta-knowledge sharing among heterogeneous …

Fast Rates For Maximum Entropy Exploration, Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Éric Moulines, Rémi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Ménard

Machine Learning Faculty Publications

We address the challenge of exploration in reinforcement learning (RL) when the agent operates in an unknown environment with sparse or no rewards. In this work, we study the maximum entropy exploration problem of two different types. The first type is visitation entropy maximization previously considered by Hazan et al. (2019) in the discounted setting. For this type of exploration, we propose a game-theoretic algorithm that has Oe(H3S2A/ε2) sample complexity thus improving the ε-dependence upon existing results, where S is a number of states, A is a number of actions, H is an episode length, and ε is a desired …

Evolving Semantic Prototype Improves Generative Zero-Shot Learning, Shiming Chen, Wenjin Hou, Ziming Hong, Xiaohan Ding, Yibing Song, Xinge You, Tongliang Liu, Kun Zhang

Machine Learning Faculty Publications

In zero-shot learning (ZSL), generative methods synthesize class-related sample features based on predefined semantic prototypes. They advance the ZSL performance by synthesizing unseen class sample features for better training the classifier. We observe that each class's predefined semantic prototype (also referred to as semantic embedding or condition) does not accurately match its real semantic prototype. So the synthesized visual sample features do not faithfully represent the real sample features, limiting the classifier training and existing ZSL performance. In this paper, we formulate this mismatch phenomenon as the visual-semantic domain shift problem. We propose a dynamic semantic prototype evolving (DSP) method …

Coco: A Coupled Contrastive Framework For Unsupervised Domain Adaptive Graph Classification, Nan Yin, Li Shen, Mengzhu Wang, Long Lan, Zeyu Ma, Chong Chen, Xian Sheng Hua, Xiao Luo

Machine Learning Faculty Publications

Although graph neural networks (GNNs) have achieved impressive achievements in graph classification, they often need abundant task-specific labels, which could be extensively costly to acquire. A credible solution is to explore additional labeled graphs to enhance unsupervised learning on the target domain. However, how to apply GNNs to domain adaptation remains unsolved owing to the insufficient exploration of graph topology and the significant domain discrepancy. In this paper, we propose Coupled Contrastive Graph Representation Learning (CoCo), which extracts the topological information from coupled learning branches and reduces the domain discrepancy with coupled contrastive learning. CoCo contains a graph convolutional network …

Convergence Of Proximal Point And Extragradient-Based Methods Beyond Monotonicity: The Case Of Negative Comonotonicity, Eduard Gorbunov, Adrien Taylor, Samuel Horváth, Gauthier Gidel

Machine Learning Faculty Publications

Algorithms for min-max optimization and variational inequalities are often studied under monotonicity assumptions. Motivated by non-monotone machine learning applications, we follow the line of works (Diakonikolas et al., 2021; Lee & Kim, 2021; Pethick et al., 2022; Böhm, 2022) aiming at going beyond monotonicity by considering the weaker negative comonotonicity assumption. In this work, we provide tight complexity analyses for the Proximal Point (PP), Extragradient (EG), and Optimistic Gradient (OG) methods in this setup, closing several questions on their working guarantees beyond monotonicity. In particular, we derive the first non-asymptotic convergence rates for PP under negative comonotonicity and star-negative comonotonicity …

Unleashing Mask: Explore The Intrinsic Out-Of-Distribution Detection Capability, Jianing Zhu, Hengzhuang Li, Jiangchao Yao, Tongliang Liu, Jianliang Xu, Bo Han

Machine Learning Faculty Publications

Out-of-distribution (OOD) detection is an indispensable aspect of secure AI when deploying machine learning models in real-world applications. Previous paradigms either explore better scoring functions or utilize the knowledge of outliers to equip the models with the ability of OOD detection. However, few of them pay attention to the intrinsic OOD detection capability of the given model. In this work, we generally discover the existence of an intermediate stage of a model trained on in-distribution (ID) data having higher OOD detection performance than that of its final stage across different settings, and further identify one critical data-level attribution to be …

Issue Assignment Delay Of Early-View Articles: Impact On Subscribers Through An Aggregator Database, Benjamin L. Hockenberry

Lavery Library Faculty/Staff Publications

Journal articles are often made available prior to assignment to an issue, using labels like “early view,” “advanced online publication,” “ahead of print,” “online first,” or “in press.” While making articles available before an issue can speed up the scholarly communications cycle, a negative effect can be observed when full text is delivered through aggregator databases like EBSCO, ProQuest, or Gale products. This study assessed issue assignment delays across 18 journals which have full text aggregated in EBSCO's CINAHL Ultimate. Results show that articles published first in an early-view state are only available in the aggregator after they have been …

Center For Grassland Studies, July 2023

Center for Grassland Studies: Newsletters

Center for Grassland Studies newsletter (July 2023)

Contents

23rd Annual Nebraska Grazing Conference August 8-9, 2023 by Daren Redfearn

Center for Grassland Studies Policy Advisory Committee

Director’s Column by Jerry Volesky

New Barta Brothers Ranch Manager

Congratulations 2023 Graduates!

Grassland Ecology and Management Major – Jay Cleveland, Kyle Griger, and Cole Laible

Grassland Ecology and Management Minor – Benjamin Janssen

Grazing Livestock Systems Major – Boone Svoboda

Grazing Livestock Systems Minor – Caitlin Buck and Kelsey Swantek

Other Range Club Members – Erik Henry (Environmental Science, Fisheries, and Wildlife) and Lydia Regier (Plant Biology)

Bison Conservation in a Changing Climate …

Summer Therapy And Coaching Resource Notebook, Kelli J. Pease

IPS/BAS 495 Undergraduate Capstone Projects

This project aims to fulfill the need for an easily accessible and well-organized resource notebook for summer Educational Therapy and Academic Coaching that our organization has talked about doing for some time now but has always lacked the manpower to make happen. I desire to have this be a stepping stone towards offering a valuable, well-defined service for our administration to offer to our students and families in the future.

This approach will address the frustration of having data and information scattered between our three schools, departments, and people. It will also take current resources, information, and opinions from other …

Parenting Perspective Podcast Capstone Project, Daniel P. Perttula

IPS/BAS 495 Undergraduate Capstone Projects

The Dads That Talk Podcast is a Capstone Project that intends to help parents, including myself, learn new parenting styles or techniques that they could not be otherwise aware of. This is being accomplished by solving the problem statement, how might I improve my parenting skills and the parenting skills of my peers by producing a podcast that reviews real life parenting challenges in today’s society. I focus on discussing different styles of parenting to establish a foundation of understanding on the many different approaches and styles that a parent can leverage. Listeners have an easy to consume source of …

A Unified Optimization Framework Of Ann-Snn Conversion: Towards Optimal Mapping From Activation Values To Firing Rates, Haiyan Jiang, Srinivas Anumasa, Giulia De Masi, Huan Xiong, Bin Gu

Machine Learning Faculty Publications

Spiking Neural Networks (SNNs) have gained significant attention for their energy-efficient and fast-inference capabilities, but training SNNs from scratch can be challenging due to the discrete nature of spikes. One alternative method is to convert an Artificial Neural Network (ANN) into an SNN, known as ANN-SNN conversion. Currently, existing ANN-SNN conversion methods often involve redesigning the ANN with a new activation function, rather than utilizing the traditional ReLU, and converting it to an SNN. However, these methods do not take into account the potential performance loss between the regular ANN with ReLU and the tailored ANN. In this work, we …

Addressing Work-Related Traumatic Stress Nebraska - Key Findings, Quality Improvement Center For Workforce Development

Other QIC-WD Products

Background

Nebraska’s Department of Child and Family Services (DCFS) started working with the QIC-WD in 2017 to better understand its turnover problem and found that, among workers who left the agency in 2017, it typically happened within the first two years and the turnover rate in 2017 was about 30%. The team examined many contributing factors through a needs assessment and designed CFS Strong to improve employee retention by addressing work-related traumatic stress among the child welfare workforce.

According to the Secondary Traumatic Stress (STS) scale administered in December 2017, the overall presence of STS symptoms in DCFS staff was …

Helen Friel, Katt Marshall

Communication Design: Design Pioneers

As the foundation of design is laid down early in a designer’s career, it is the process of creatingwithin limited parameters which develops their style. Many designers begin with a broad rangeof skills that are honed as they navigate working with clients. Applying their unique approach tohe project at hand, it is at this time when design peers create a niche market. The designer’stouch becomes a recognizable signature upon their body of work. With a comprehensiveportfolio, the designer can present their approach to tackling challenging concepts. Paperengineer and illustrator Helen Friel is a designer with a diverse body of work, …

Three Hundred Years Of Helping Others: Maria Gaetana Agnesi On The Product Rule, Kenneth M. Monks

Calculus

No abstract provided.

Library & Knowledge Services Newsletter - Summer 2023, Baystate Health Sciences Library

Library Newsletters

Baystate Library & Knowledge Services Newsletter - Summer 2023

Family Dining: Food And Drink In The Sopranos – A Gastrocritical Approach, Lisa Davies

Dissertations

This thesis uses gastrocriticism to explore food and drink in the 86 episodes of the long-form narrative HBO television series The Sopranos. Gastrocriticism is an emerging branch of literary criticism that draws on scholarship from a range of disciplines such as sociology, anthropology and cultural studies. A deeper understanding of the series was gained by using a structured framework of enquiry to explore narrative, setting, characterisation and genre through the lens of food and foodways. The Sopranos is a story of an Italian-American crime family and food is abundant in the series and bound up with the identity of …

Linear Classifier: An Often-Forgotten Baseline For Text Classification, Yu Chen Lin, Si An Chen, Jie Jyun Liu, Chih Jen Lin

Machine Learning Faculty Publications

Large-scale pre-trained language models such as BERT are popular solutions for text classification. Due to the superior performance of these advanced methods, nowadays, people often directly train them for a few epochs and deploy the obtained model. In this opinion paper, we point out that this way may only sometimes get satisfactory results. We argue the importance of running a simple baseline like linear classifiers on bag-of-words features along with advanced methods. First, for many text data, linear methods show competitive performance, high efficiency, and robustness. Second, advanced models such as BERT may only achieve the best results if properly …

Improving Decision Support Systems With Machine Learning: Identifying Barriers To Adoption, Skye Brugler, Maaz Gardezi, Ali Dadkhah, Donna M. Rizzo, Asim Zia, Sharon A. Clay

Agronomy, Horticulture and Plant Science Faculty Publications

Precision agriculture (PA) has been defined as a “management strategy that gathers, processes and analyzes temporal, spatial and individual data and combines it with other information to support management decisions according to estimated variability for improved resource use efficiency, productivity, quality, profitability and sustainability of agricultural production.” This definition suggests that because PA should simultaneously increase food production and reduce the environmental footprint, the barriers to adoption of PA should be explored. These barriers include: 1) the financial constraints associated with adopting DSS, 2) the hesitancy of farmers to change from their trusted advisor to a computer program often behaves …

Discovery Of Extraordinary X-Ray Emission From Magnetospheric Interaction In The Unique Binary Stellar System Ε Lupi, B. Das, V. Petit, Y. Nazé, M. F. Corcoran, David H. Cohen, A. Biswas, P. Chandra, A. David-Uraz, M. A. Leutenegger, C. Neiner, H. Pablo, E. Paunzen, M. E. Shultz, A. Ud-Doula, G. A. Wade

Physics & Astronomy Faculty Works

We report detailed X-ray observations of the unique binary system ϵ Lupi, the only known short-period binary consisting of two magnetic early-type stars. The components have comparably strong, but anti-aligned magnetic fields. The orbital and magnetic properties of the system imply that the magnetospheres overlap at all orbital phases, suggesting the possibility of variable inter-star magnetospheric interaction due to the non-negligible eccentricity of the orbit. To investigate this effect, we observed the X-ray emission from ϵ Lupi, both near and away from periastron passage, using the Neutron Star Interior Composition Explorer mission (NICER) X-ray Telescope. We find that the system …

Supporting Motor, Cognitive, And Psychosocial Functions For Children And Youth With Acquired Brain Injury: A Scoping Review, Quandra Shanks, Angela Labrie Blackwell

Summer 2023 Virtual OTD Capstone Symposium

Acquired brain injury (ABI) refers to an injury to the brain that is not hereditary, congenital, degenerative, or induced by birth trauma (Brain Injury Association [BIA], 2023). ABI is an umbrella term for all brain injuries, typically classified as traumatic (e.g., sports injury, fall) or non-traumatic (e.g., stroke, infection) (Wales et al., 2021). It is considered one of the leading causes of death and disability for individuals of all ages (Riccardi & Lundine, 2022). The BIA (2023) reports that ages 0-4 and 15-19 are at greater risk for brain injury. The severity of ABI among pediatrics is more severe than …

Staff Council Financial Statement July 2023, Staff Council

Staff Advisory Council Treasurer Reports

No abstract provided.

Frontline Job Redesign Louisiana - Key Findings, Quality Improvement Center For Workforce Development

Other QIC-WD Products

Background

In 2017, the QIC-WD began working with the Louisiana Department of Children and Family Services (DCFS). At that time DCFS had an average turnover rate of 24% across the state with one region having a rate of 51% and another with a low of 8%. A thorough needs assessment identified that high caseloads and a large number of administrative tasks were barriers to caseworkers’ ability to effectively engage in the clinical aspects of their work and led to the decision to redesign the frontline caseworker job.

The intervention created a new job, the Child Welfare Team Specialist (CWTS), …