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Articles 12211 - 12240 of 302419

Full-Text Articles in Physical Sciences and Mathematics

Why 6-Labels Uncertainty Scale In Geosciences: Probability-Based Explanation, Aaron Velasco, Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich Jul 2023

Why 6-Labels Uncertainty Scale In Geosciences: Probability-Based Explanation, Aaron Velasco, Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

To describe uncertainty in geosciences, several researchers have recently proposed a 6-labels uncertainty scale, in which one the labels corresponds to full certainty, one label to the absence of any knowledge, and the remaining four labels correspond to the degrees of confidence from the intervals [0,0.25], [0.25,0.5], [0.5,0.75], and [0.75,1]. Tests of this 6-labels scale indicate that it indeed conveys uncertainty information to geoscientists much more effectively than previously proposed uncertainty schemes. In this paper, we use probability-related techniques to explain this effectiveness.

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Fuzzy Mathematics Under Non-Minimal "And"-Operations (T-Norms): Equivalence Leads To Metric, Order Leads To Kinematic Metric, Topology Leads To Area Or Volume, Purbita Jana, Olga Kosheleva, Vladik Kreinovich Jul 2023

Fuzzy Mathematics Under Non-Minimal "And"-Operations (T-Norms): Equivalence Leads To Metric, Order Leads To Kinematic Metric, Topology Leads To Area Or Volume, Purbita Jana, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Most formulas analyzed in fuzzy mathematics assume -- explicitly or implicitly -- that the corresponding "and"-operation (t-norm) is the simplest minimum operation. In this paper, we analyze what happens if instead, we use other "and"-operations. It turns out that for such operations, a fuzzification of a mathematical theory naturally leads to a more complex mathematical setting: fuzzification of equivalence relation leads to metric, fuzzification of order leads to kinematic metric, and fuzzification of topology leads to area or volume.

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Complex Numbers Explain Why In Chinese Tradition, 4 Is Bad But 8 Is Good, Luc Longpre, Olga Kosheleva, Vladik Kreinovich Jul 2023

Complex Numbers Explain Why In Chinese Tradition, 4 Is Bad But 8 Is Good, Luc Longpre, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In the traditional Chinese culture, 4 is considered to be an unlucky number, while the number 8 is considered to be very lucky. In this paper, we show that both "badness" and "goodness" can be explained if we take into account the role of complex numbers in the analysis of general dynamical systems.

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Why Resilient Modulus Is Proportional To The Square Root Of Unconfined Compressive Strength (Ucs): A Qualitative Explanation, Edgar Daniel Rodriguez Velasquez, Vladik Kreinovich Jul 2023

Why Resilient Modulus Is Proportional To The Square Root Of Unconfined Compressive Strength (Ucs): A Qualitative Explanation, Edgar Daniel Rodriguez Velasquez, Vladik Kreinovich

Departmental Technical Reports (CS)

The strength of the pavement is determine by its resilient modulus, i.e., by its ability to withstand (practically) instantaneous stresses caused by the passing traffic. However, the resilient modulus is not easy to measure: its measurement requires a special expensive equipment that many labs do not have. So, instead of measuring it, practitioners often measure easier-to-measure Unconfined Compressive Strength (UCS) -- that describes the effect of a continuously applied force -- and estimate the resilient modulus based on the result of this measurement. An empirical formula shows that the resilient modulus is proportional to the square root of the Unconfined …

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How To Estimate Unknown Unknowns: From Cosmic Light To Election Polls, Talha Azfar, Vignesh Ponraj, Vladik Kreinovich, Nguyen Hoang Phuong Jul 2023

How To Estimate Unknown Unknowns: From Cosmic Light To Election Polls, Talha Azfar, Vignesh Ponraj, Vladik Kreinovich, Nguyen Hoang Phuong

Departmental Technical Reports (CS)

In two different areas of research -- in the study of space light and in the study of voting -- the observed value of the quantity of interest is twice larger than what we would expect. That the observed value is larger makes perfect sense: there are phenomena that we do not take into account in our estimations. However, the fact that the observed value is exactly twice larger deserves explanation. In this paper, we show that Laplace Indeterminacy Principle leads to such an explanation.

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We Can Always Reduce A Non-Linear Dynamical System To Linear -- At Least Locally -- But Does It Help?, Orsolya Csiszar, Gábor Csiszar, Olga Kosheleva, Vladik Kreinovich, Nguyen Hoang Phuong Jul 2023

We Can Always Reduce A Non-Linear Dynamical System To Linear -- At Least Locally -- But Does It Help?, Orsolya Csiszar, Gábor Csiszar, Olga Kosheleva, Vladik Kreinovich, Nguyen Hoang Phuong

Departmental Technical Reports (CS)

Many real-life phenomena are described by dynamical systems. Sometimes, these dynamical systems are linear. For such systems, solutions are well known. In some cases, it is possible to transform a nonlinear system into a linear one by appropriately transforming its variables, and this helps to solve the original nonlinear system. For other nonlinear systems -- even for the simplest ones -- such transformation is not known. A natural question is: which nonlinear systems allow such transformations? In this paper, we show that we can always reduce a nonlinear system to a linear one -- but, in general, it does not …

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What Was More Frequently Used -- "And" Or "Or": Based On Analysis Of European Languages, Olga Kosheleva, Vladik Kreinovich Jul 2023

What Was More Frequently Used -- "And" Or "Or": Based On Analysis Of European Languages, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

Traditional logic has two main connectives: "and" and "or". A natural question is: which of the two is more frequently used? This question is easy to answer for the current usage of these connectives -- we can simply analyze all the texts, but what can we say about the past usage? To answer this question, we use the known linguistics fact that, in general, notions that are more frequently used are described by shorter words. It turns out that in most European languages, the word for "and" is shorter -- or of the same length -- as the word for …

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Why Bump Reward Function Works Well In Training Insulin Delivery Systems, Lehel Dénes-Fazakas, Lásló Szilágyi, Gyorgy Eigner, Olga Kosheleva, Vladik Kreinovich, Nguyen Hoang Phuong Jul 2023

Why Bump Reward Function Works Well In Training Insulin Delivery Systems, Lehel Dénes-Fazakas, Lásló Szilágyi, Gyorgy Eigner, Olga Kosheleva, Vladik Kreinovich, Nguyen Hoang Phuong

Departmental Technical Reports (CS)

Diabetes is a disease when the body can no longer properly regulate blood glucose level, which can lead to life-threatening situations. To avoid such situations and regulate blood glucose level, patients with severe form of diabetes need insulin injections. Ideally, the system should automatically decide when best to inject insulin and how much to inject. To find the optimal control, researchers applied machine learning with different reward functions. It turns out that the most effective learning occurred when they used the so-called bump function. In this paper, we provide a possible explanation for this empirical result.

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Understanding Mitochondrial Dysfunction In Neurodegenerative Diseases Using Novel Neuron Cell Models, Amy Apfelbaum, Anthony Grillo Phd, Raghav Dutta Phd, Alaa Hassan Jul 2023

Understanding Mitochondrial Dysfunction In Neurodegenerative Diseases Using Novel Neuron Cell Models, Amy Apfelbaum, Anthony Grillo Phd, Raghav Dutta Phd, Alaa Hassan

Annual Student Research Poster Session

This past summer I worked Dr. Anthony Grillo’s lab under my mentors Raghav Dutta and Alaa Hassan at the University of Cincinnati. The Grillo Lab is focused on understanding the mechanisms of mitochondrial complex 1 dysfunction in neurodegenerative diseases. It has been shown that an early feature of neurodegeneration is complex 1 dysfunction; we were trying to determine if this is a cause or an effect of these diseases. This summer, we focused on identifying different types of neuron subtypes in brain tissue samples, isolating primary neurons by first identifying and visualizing the types of brain cells present in brain …

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Identification Of Dialect For Eastern And Southwestern Ojibwe Words Using A Small Corpus, Kalvin Hartwig, Evan Lucas, Timothy C. Havens Jul 2023

Identification Of Dialect For Eastern And Southwestern Ojibwe Words Using A Small Corpus, Kalvin Hartwig, Evan Lucas, Timothy C. Havens

Michigan Tech Publications, Part 2

The Ojibwe language has several dialects that vary to some degree in both spoken and written form. We present a method of using support vector machines to classify two different dialects (Eastern and Southwestern Ojibwe) using a very small corpus of text. Classification accuracy at the sentence level is 90% across a five-fold cross validation and 72% when the sentence-trained model is applied to a data set of individual words. Our code and the word level data set are released openly at https://github.com/evanperson/OjibweDialect.

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Polygonal Faults In The Austin Chalk: Invariance Of Scale From Mud Cracks To Polygons With Implications Of Structural, Geomorphic And Isotopic Data On Polygonal Fault Geometry And Origin., Kun Shang Jul 2023

Polygonal Faults In The Austin Chalk: Invariance Of Scale From Mud Cracks To Polygons With Implications Of Structural, Geomorphic And Isotopic Data On Polygonal Fault Geometry And Origin., Kun Shang

Earth Sciences Theses and Dissertations

The Cretaceous Austin Chalk contains large numbers of fractures and normal faults whose orientations have been attributed to either regional stresses (e.g., the Balcones fault trend) or, by analogy with the mudrocks, to polygonal faulting resulting from compaction. In this study, we present geomorphic data, field study, and stable isotope data to support that the majority of these faults in North Texas are polygonal. Field-measured fault orientations suggest randomly distributed fault strikes, indicating a polygonal fault structure. Using geomorphologic data (topographic and DEM data) on stream orientations suggests that the polygonal fault patterns are best reflected in the headwater (1st …

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Hypo-Osmotic Stress And Pore-Forming Toxins Adjust The Lipid Order In Sheep Red Blood Cell Membranes, Rose Whiting, Sevio Stanton, Maryna Kucheriava, Aviana R. Smith, Matt Pitts, Daniel Robertson, Jacob Kammer, Zhiyu Li, Daniel Fologea Jul 2023

Hypo-Osmotic Stress And Pore-Forming Toxins Adjust The Lipid Order In Sheep Red Blood Cell Membranes, Rose Whiting, Sevio Stanton, Maryna Kucheriava, Aviana R. Smith, Matt Pitts, Daniel Robertson, Jacob Kammer, Zhiyu Li, Daniel Fologea

Physics Faculty Publications and Presentations

Lipid ordering in cell membranes has been increasingly recognized as an important factor in establishing and regulating a large variety of biological functions. Multiple investigations into lipid organization focused on assessing ordering from temperature-induced phase transitions, which are often well outside the physiological range. However, particular stresses elicited by environmental factors, such as hypo-osmotic stress or protein insertion into membranes, with respect to changes in lipid status and ordering at constant temperature are insufficiently described. To fill these gaps in our knowledge, we exploited the well-established ability of environmentally sensitive membrane probes to detect intramembrane changes at the molecular level. …

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Fuzzy Techniques Explain The Effectiveness Of Relu Activation Function In Deep Learning, Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich Jul 2023

Fuzzy Techniques Explain The Effectiveness Of Relu Activation Function In Deep Learning, Julio C. Urenda, Olga Kosheleva, Vladik Kreinovich

Departmental Technical Reports (CS)

In the last decades, deep learning has led to spectacular successes. One of the reasons for these successes was the fact that deep neural networks use a special Rectified Linear Unit (ReLU) activation function s(x) = max(0,x). Why this activation function is so successful is largely a mystery. In this paper, we show that common sense ideas -- as formalized by fuzzy logic -- can explain this mysterious effectiveness.

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Amyloid-Beta Protein Concentration Dependence Of Reversible Aggregation Using Gold Colloid Particles, Renee Spencer, Lila Kocieniewski, Bryan Martinez, Kazushige Yokoyama Jul 2023

Amyloid-Beta Protein Concentration Dependence Of Reversible Aggregation Using Gold Colloid Particles, Renee Spencer, Lila Kocieniewski, Bryan Martinez, Kazushige Yokoyama

McNair Scholars Program

Although Alzheimer’s and COVID-19 are different diseases, the commonality between them is during the process of them developing in a person by fibrillogenesis. The product of fibrillogenesis results in the development of these diseases. We study the first stage of fibrillogenesis where the amyloid-beta peptide monomers are assembled into an oligomer. We want to isolate this oligomer using gold colloids because this step can be reversed. Utilizing gold colloids allows us to freeze fibrillogenesis in the first step by folding and unfolding the protein repeatedly through a series of pH changes from 4 or below to 10 or higher. At …

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Development And Reliability Analysis Of A Split-Administration Test Of The Math Epistemic Games Survey, Stephen Hackler, E. Elliott, M. Eichenlaub, A. M. Sweeney Jul 2023

Development And Reliability Analysis Of A Split-Administration Test Of The Math Epistemic Games Survey, Stephen Hackler, E. Elliott, M. Eichenlaub, A. M. Sweeney

Physics & Astronomy Faculty Works

The increasing and diversifying student enrollments in introductory physics courses make reliable, valid, and usable instruments for measuring student skills and gains ever more important. In introductory physics, in addition to teaching facts about mechanics, we also seek to teach our students the skills of “thinking like a physicist,” or expertise in and intuition for physical problem solving. How and when these expert, intuitive problem-solving skills emerge during a STEM education, or what the most effective teaching methods might be, are not certain. A facile survey to measure students’ “physics-thinking” skills in a pretest and post-test format is therefore desirable …

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Model Transferability With Responsive Decision Subjects, Yatong Chen, Zeyu Tang, Kun Zhang, Yang Liu Jul 2023

Model Transferability With Responsive Decision Subjects, Yatong Chen, Zeyu Tang, Kun Zhang, Yang Liu

Machine Learning Faculty Publications

Given an algorithmic predictor that is accurate on some source population consisting of strategic human decision subjects, will it remain accurate if the population respond to it? In our setting, an agent or a user corresponds to a sample (X, Y ) drawn from a distribution D and will face a model h and its classification result h(X). Agents can modify X to adapt to h, which will incur a distribution shift on (X, Y ). Our formulation is motivated by applications where the deployed machine learning models are subjected to human agents, and will ultimately face responsive and interactive …

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Detecting Out-Of-Distribution Data Through In-Distribution Class Prior, Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han Jul 2023

Detecting Out-Of-Distribution Data Through In-Distribution Class Prior, Xue Jiang, Feng Liu, Zhen Fang, Hong Chen, Tongliang Liu, Feng Zheng, Bo Han

Machine Learning Faculty Publications

Given a pre-trained in-distribution (ID) model, the inference-time out-of-distribution (OOD) detection aims to recognize OOD data during the inference stage. However, some representative methods share an unproven assumption that the probability that OOD data belong to every ID class should be the same, i.e., these OOD-to-ID probabilities actually form a uniform distribution. In this paper, we show that this assumption makes the above methods incapable when the ID model is trained with class-imbalanced data. Fortunately, by analyzing the causal relations between ID/OOD classes and features, we identify several common scenarios where the OOD-to-ID probabilities should be the ID-class-prior distribution and …

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Algebraic Approach To Relativistic Landau Levels In The Symmetric Gauge, Ulrich D. Jentschura Jul 2023

Algebraic Approach To Relativistic Landau Levels In The Symmetric Gauge, Ulrich D. Jentschura

Physics Faculty Research & Creative Works

We use an algebraic approach to the calculation of Landau levels for a uniform magnetic field in the symmetric gauge with a vector potential A→=12(B→xr→), where B→ is assumed to be constant. The magnetron quantum number constitutes the degeneracy index. An overall complex phase of the wave function, given in terms of Laguerre polynomials, is a consequence of the algebraic structure. The relativistic generalization of the treatment leads to fully relativistic bispinor Landau levels in the symmetric gauge, in a representation which writes the relativistic states in terms of their nonrelativistic limit, and an algebraically accessible lower bispinor component. Negative-energy …

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Memory-Multi-Fractional Brownian Motion With Continuous Correlations, Wei Wang, Michał Balcerek, Krzysztof Burnecki, Aleksei V. Chechkin, Skirmantas Janušonis, Jakub Ślȩzak, Thomas Vojta, Agnieszka Wyłomańska, Ralf Metzler Jul 2023

Memory-Multi-Fractional Brownian Motion With Continuous Correlations, Wei Wang, Michał Balcerek, Krzysztof Burnecki, Aleksei V. Chechkin, Skirmantas Janušonis, Jakub Ślȩzak, Thomas Vojta, Agnieszka Wyłomańska, Ralf Metzler

Physics Faculty Research & Creative Works

We propose a generalization of the widely used fractional Brownian motion (FBM), memory-multi-FBM (MMFBM), to describe viscoelastic or persistent anomalous diffusion with time-dependent memory exponent α(t) in a changing environment. In MMFBM the built-in, long-range memory is continuously modulated by α(t). We derive the essential statistical properties of MMFBM such as its response function, mean-squared displacement (MSD), autocovariance function, and Gaussian distribution. In contrast to existing forms of FBM with time-varying memory exponents but a reset memory structure, the instantaneous dynamic of MMFBM is influenced by the process history, e.g., we show that after a steplike change of α(t) the …

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Sound Salmon Solutions, Chloe Lindstrom Jul 2023

Sound Salmon Solutions, Chloe Lindstrom

College of the Environment Internship Reports

explored the wetland ecosystem of the Edmonds Marsh, and got the opportunity to look into water quality as well. The camp took place at the Sound Salmon Solutions hatchery, which is also known as the Willow Creek Salmon and Watershed Education Center located in Edmonds, Washington. Sound Salmon Solutions works with hands-on stewardship, habitat restoration efforts, and interactive education to expand on the relationship between the environment and people to assist in the recovery of pacific northwest salmon.

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The Nature Conservancy And Sca Intern, Kathryn Hoerauf Jul 2023

The Nature Conservancy And Sca Intern, Kathryn Hoerauf

College of the Environment Internship Reports

The main project we contributed to was the vegetation monitoring program connected to the Port Susan Bay restoration efforts. Most of the summer was spent in the marsh using GPS units to follow various elevationbased transects, gathering plot data, and entering that data into larger Excel spreadsheets. These data contributed to a larger body of data collection that spans almost 10 years, allowing TNC to see measurable change in the marsh related to their efforts to reconnect freshwater supply to the marsh via the Stillaguamish River. Since 2012, TNC has worked with multiple tribal and state agencies to take down …

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Nooksack Salmon Enhancement Association Camp Educator, Mae Brenneman Jul 2023

Nooksack Salmon Enhancement Association Camp Educator, Mae Brenneman

College of the Environment Internship Reports

Some of my main objectives from the start of this position were to gain leadership skills in environmental education, learn more about salmon ecology, and apply the knowledge gained in my WWU Environmental Science courses to this internship. In addition to these, I wanted to speak effectively to students about ecology and conservation and gain more knowledge on local environmental issues by working with an organization that strives to support the restoration of salmon habitats in Washington. This position allowed me to meet my learning objectives by giving me an opportunity to lead lessons and develop curriculum in environmental education, …

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Institute For Watershed Studies Research Assistant, Savannah Samuelson Jul 2023

Institute For Watershed Studies Research Assistant, Savannah Samuelson

College of the Environment Internship Reports

In the summer of 2023, I assisted Kathryn “Katey” Queen, a M.S. candidate in Environmental Science at Western Washington University. Dr. Angela Strecker advises Katey’s aquatic ecological research master’s thesis. This thesis work focuses on the successional development of ponds and surrounding habitats that formed following the 1980 volcanic eruption of Mount St. Helens. The eruption had varied impacts on the surrounding area; closest to the crater where trees were entirely removed, to more distant locations where the force leveled trees, to the outer edges of the blast area where the force was not powerful enough to knock trees down …

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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 Jul 2023

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 …

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Interpolation Problems And The Characterization Of The Hilbert Function, Bryant Xie Jul 2023

Interpolation Problems And The Characterization Of The Hilbert Function, Bryant Xie

Mathematical Sciences Undergraduate Honors Theses

In mathematics, it is often useful to approximate the values of functions that are either too awkward and difficult to evaluate or not readily differentiable or integrable. To approximate its values, we attempt to replace such functions with more well-behaving examples such as polynomials or trigonometric functions. Over the algebraically closed field C, a polynomial passing through r distinct points with multiplicities m1, ..., mr on the affine complex line in one variable is determined by its zeros and the vanishing conditions up to its mi − 1 derivative for each point. A natural question would then be to consider …

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Linear Classifier: An Often-Forgotten Baseline For Text Classification, Yu Chen Lin, Si An Chen, Jie Jyun Liu, Chih Jen Lin Jul 2023

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 …

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Reinforcement Learning For Sequential Decision Making With Constraints, Jiajing Ling Jul 2023

Reinforcement Learning For Sequential Decision Making With Constraints, Jiajing Ling

Dissertations and Theses Collection (Open Access)

Reinforcement learning is a widely used approach to tackle problems in sequential decision making where an agent learns from rewards or penalties. However, in decision-making problems that involve safety or limited resources, the agent's exploration is often limited by constraints. To model such problems, constrained Markov decision processes and constrained decentralized partially observable Markov decision processes have been proposed for single-agent and multi-agent settings, respectively. A significant challenge in solving constrained Dec-POMDP is determining the contribution of each agent to the primary objective and constraint violations. To address this issue, we propose a fictitious play-based method that uses Lagrangian Relaxation …

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Product Question Answering In E-Commerce: A Survey, Yang Deng, Wenxuan Zhang, Qian Yu, Wai Lam Jul 2023

Product Question Answering In E-Commerce: A Survey, Yang Deng, Wenxuan Zhang, Qian Yu, Wai Lam

Research Collection School Of Computing and Information Systems

Product question answering (PQA), aiming to automatically provide instant responses to customer’s questions in E-Commerce platforms, has drawn increasing attention in recent years. Compared with typical QA problems, PQA exhibits unique challenges such as the subjectivity and reliability of user-generated contents in E-commerce platforms. Therefore, various problem settings and novel methods have been proposed to capture these special characteristics. In this paper, we aim to systematically review existing research efforts on PQA. Specifically, we categorize PQA studies into four problem settings in terms of the form of provided answers. We analyze the pros and cons, as well as present existing …

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A Universal Unbiased Method For Classification From Aggregate Observations, Zixi Wei, Lei Feng, Bo Han, Tongliang Liu, Gang Niu, Xiaofeng Zhu, Heng Tao Shen Jul 2023

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 …

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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 Jul 2023

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 …

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