Digital Commons Network^™

M 326.01: Number Theory, Frederick Peck

University of Montana Course Syllabi, 2021-2025

No abstract provided.

M 485.01: Graph Theory, Mark Kayll

University of Montana Course Syllabi, 2021-2025

No abstract provided.

M 562.01: Advanced Theoretical Data Analytics, Johnathan M. Bardsley

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Stat 342.01: Probability And Simulation, Jakob B. Oetinger

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Bridging Expert Knowledge With Deep Learning Techniques For Just-In-Time Defect Prediction, Xin Zhou, Donggyun Han, David Lo

Research Collection School Of Computing and Information Systems

Just-In-Time (JIT) defect prediction aims to automatically predict whether a commit is defective or not, and has been widely studied in recent years. In general, most studies can be classified into two categories: 1) simple models using traditional machine learning classifiers with hand-crafted features, and 2) complex models using deep learning techniques to automatically extract features from commit contents. Hand-crafted features used by simple models are based on expert knowledge but may not fully represent the semantic meaning of the commits. On the other hand, deep learning-based features used by complex models represent the semantic meaning of commits but may …

Proactive Conversational Ai: A Comprehensive Survey Of Advancements And Opportunities, Yang Deng, Lizi Liao, Wenqiang Lei, Grace Hui Yang, Wai Lam, Tat-Seng Chua

Research Collection School Of Computing and Information Systems

Dialogue systems are designed to offer human users social support or functional services through natural language interactions. Traditional conversation research has put significant emphasis on a system's response-ability, including its capacity to understand dialogue context and generate appropriate responses. However, the key element of proactive behavior-a crucial aspect of intelligent conversations-is often overlooked in these studies. Proactivity empowers conversational agents to lead conversations towards achieving pre-defined targets or fulfilling specific goals on the system side. Proactive dialogue systems are equipped with advanced techniques to handle complex tasks, requiring strategic and motivational interactions, thus representing a significant step towards artificial general …

Loco: Low-Bit Communication Adaptor For Large-Scale Model Training, Xingyu Xie, Zhijie Lin, Kim-Chuan Toh, Pan Zhou

Research Collection School Of Computing and Information Systems

To efficiently train large-scale models, low-bit gradient communication compresses full-precision gradients on local GPU nodes into low-precision ones for higher gradient synchronization efficiency among GPU nodes. However, it often degrades training quality due to compression information loss. To address this, we propose the Low-bit Communication Adaptor (LoCo), which compensates gradients on local GPU nodes before compression, ensuring efficient synchronization without compromising training quality. Specifically, LoCo designs a moving average of historical compensation errors to stably estimate concurrent compression error and then adopts it to compensate for the concurrent gradient compression, yielding a less lossless compression. This mechanism allows it to …

Siniel: Distributed Privacy-Preserving Zksnark, Yunbo Yang, Yuejia Cheng, Kailun Wang, Xiaoguo Li, Jianfei Sun, Jiachen Shen, Xiaolei Dong, Zhenfu Cao, Guomin Yang, Robert H. Deng

Research Collection School Of Computing and Information Systems

Zero-knowledge Succinct Non-interactive Argument of Knowledge (zkSNARK) is a powerful cryptographic primitive, in which a prover convinces a verifier that a given statement is true without leaking any additional information. However, existing zkSNARKs suffer from high computation overhead in the proof generation. This limits the applications of zkSNARKs, such as private payments, private smart contracts, and anonymous credentials. Private delegation has become a prominent way to accelerate proof generation. In this work, we propose Siniel, an efficient private delegation framework for zkSNARKs constructed from polynomial interactive oracle proof (PIOP) and polynomial commitment scheme (PCS). Our protocol allows a computationally limited …

Human‑Ai And Human‑Robot Collaboration In The Age Of Generative Ai, Agentic Ai, And Artificial General Intelligence: Opportunities And Challenges, Keng Siau

Research Collection School Of Computing and Information Systems

The advancement of Artificial Intelligence (AI) has been exponential, especially in the past few years. Most, if not all, of the AI systems we encounter and are exposed to at this point are Artificial Narrow Intelligence (ANI). ANI specializes in one area and solves problems in one area. Generative AI (GenAI) and Agentic AI (i.e., independent AI agent), at the current stage of development, are regarded as ANI. The race is currently on to develop Artificial General Intelligence (AGI). AGI refers to AI systems as smart as humans across a wide range of cognitive tasks. Recently, OpenAI’s o3 system received …

Proving The Future In Criminal Cases, Christopher Slobogin

Vanderbilt Law School Faculty Publications

Expert opinion about dangerousness—the risk of reoffending—is commonly introduced at sentencing, criminal commitment proceedings, and some types of pretrial detention hearings. This Essay argues that the rules governing the admissibility of scientific evidence should apply to this testimony and that, on that assumption, such evidence must be (1) “material” (logically relevant, empirically generalizable, and epistemologically germane), (2) “probative” (a measure of accuracy, which is more stringent when the evidence is from an expert), (3) helpful to the factfinder (through promoting “incremental validity”), and (4) presented in a non-prejudicial manner (i.e., in a way that minimizes the possibility it will be …

M 429.01: History Of Mathematics, Bharath Sriraman

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Phsx 205n.00: College Physics I, David M. Cornelison

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Retrenchment By Diversion: The New Politics Of Parental Rights, Mary Ziegler, Maxine Eichner, Naomi Cahn

Michigan Law Review

For the past century, the Supreme Court has repeatedly affirmed the importance of parents’ rights to direct their children’s upbringing and education. Yet suddenly the rhetoric of parental rights is being used to ground a broad range of claims on issues such as what can be taught in public schools, when minors can access gender-affirming care, or who will be punished for helping minors travel for abortion care. Why have parental-rights claims surged so visibly in contemporary law and politics? And are all the new arguments made under the banner of parental rights equally rooted in constitutional precedent?

This Article …

Vaxbot-Hpv: A Gpt-Based Chatbot For Answering Hpv Vaccine-Related Questions, Yiming Li, Jianfu Li, Manqi Li, Evan Yu, Danniel Rhee, Muhammad Amith, Lu Tang, Lara S Savas, Licong Cui, Cui Tao

Faculty, Staff and Student Publications

OBJECTIVE: Human Papillomavirus (HPV) vaccine is an effective measure to prevent and control the diseases caused by HPV. However, widespread misinformation and vaccine hesitancy remain significant barriers to its uptake. This study focuses on the development of VaxBot-HPV, a chatbot aimed at improving health literacy and promoting vaccination uptake by providing information and answering questions about the HPV vaccine.

METHODS: We constructed the knowledge base (KB) for VaxBot-HPV, which consists of 451 documents from biomedical literature and web sources on the HPV vaccine. We extracted 202 question-answer pairs from the KB and 39 questions generated by GPT-4 for training and …

Performance Comparison Of 10 State-Of-The-Art Machine Learning Algorithms For Outcome Prediction Modeling Of Radiation-Induced Toxicity, Ramon M Salazar, Saurabh S Nair, Alexandra O Leone, Ting Xu, Raymond P Mumme, Jack D Duryea, Brian De, Kelsey L Corrigan, Michael K Rooney, Matthew S Ning, Prajnan Das, Emma B Holliday, Zhongxing Liao, Laurence E Court, Joshua S Niedzielski

Faculty, Staff and Student Publications

Purpose: To evaluate the efficacy of prominent machine learning algorithms in predicting normal tissue complication probability using clinical data obtained from 2 distinct disease sites and to create a software tool that facilitates the automatic determination of the optimal algorithm to model any given labeled data set.

Methods and materials: We obtained 3 sets of radiation toxicity data (478 patients) from our clinic: gastrointestinal toxicity, radiation pneumonitis, and radiation esophagitis. These data comprised clinicopathological and dosimetric information for patients diagnosed with non-small cell lung cancer and anal squamous cell carcinoma. Each data set was modeled using 11 commonly employed machine …

M 105.50: Contemporary Mathematics, Michael L. Bruner

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Anty 208.50: Anthropological Statistics, Randall R. Skelton

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Anty 508.50: Applied Anthropological Statistics, Randall R. Skelton

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Cjus 488.01: Forensic Science - The Crime Lab And Beyond, Randall R. Skelton

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Csci 361.01: Computer Architecture, Jesse V. Johnson

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Csci 432.01: Advanced Algorithm Topics, Lucia G. Williams

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Csci 491.04: Computers In Cognitive Neuroscience, Lucy L. Owen

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Csci 532.01: Advanced Algorithm Topics, Lucia G. Williams

University of Montana Course Syllabi, 2021-2025

No abstract provided.

Csci 577.01: Simulation Modeling, Jesse V. Johnson

University of Montana Course Syllabi, 2021-2025

No abstract provided.

M 105.02: Contemporary Math With Corequisite Support, Ian Gonzales

University of Montana Course Syllabi, 2021-2025

No abstract provided.

M 105.04: Contemporary Math, Ian Gonzales

University of Montana Course Syllabi, 2021-2025

No abstract provided.

M 105.51: Contemporary Math With Corequisite Support, Sara N. Killeen

University of Montana Course Syllabi, 2021-2025

No abstract provided.

M 115.08: Probability And Linear Mathematics, Scott Davis

University of Montana Course Syllabi, 2021-2025

No abstract provided.

M 115.09: Probability And Linear Mathematics, Ian Gonzales

University of Montana Course Syllabi, 2021-2025

No abstract provided.

M 115.Vh1: Probablilty And Linear Mathematics, Jamie C. Middleton

University of Montana Course Syllabi, 2021-2025

No abstract provided.