23 papers · ranked by Valyu relevance
Michael Kearns, Yishay Mansour, Andrew Y. Ng
Assignment methods are at the heart of many algorithms for unsupervised learning and clustering - in particular, the well-known K -mean.! and E:z:pectation-Mazimi$ation (EM) algorithms. In this work, we study several different methods of assignment, including the "hard" assignments used by K-means and the "soft"…
Louis Mahon, Thomas Lukasiewicz
Online deep clustering refers to the joint use of a feature extraction network and a clustering model to assign cluster labels to each new data point or batch as it is processed. While faster and more versatile than offline methods, online clustering can easily reach the collapsed solution where the encoder maps all…
Salavat Ishbulatov
Personal and organizational planning systems maintain two records that drift apart: what was planned (a task's effort budget) and what was done (a logged action's duration and description). Existing systems bridge them with an exclusive, all-or-nothing link that strands genuinely related but unlinked effort and reports…
Ivan Stelmakh, Nihar B. Shah, Aarti Singh
We consider the problem of automated assignment of papers to reviewers in conference peer review, with a focus on fairness and statistical accuracy. Our fairness objective is to maximize the review quality of the most disadvantaged paper, in contrast to the commonly used objective of maximizing the total quality over…
Haris Aziz
We settle the complexity of computing a discrete CEEI (Competitive Equilibrium with Equal Incomes) assignment by showing it is strongly NP-hard. We then highlight a fairness notion (CEEI-FRAC) that is even stronger than CEEI for discrete assignments, is always Pareto optimal, and can be verified in polynomial time. We…
Sander Borst, Danish Kashaev
We study the online load balancing problem on unrelated machines, with the objective of minimizing the square of the ℓ 2 norm of the loads on the machines. The greedy algorithm of Awerbuch et al. (STOC'95) is optimal for deterministic algorithms and achieves a competitive ratio of 3 + 2 √ 2 ≈ 5.828, and an improved…
Simon Cullen, Daniel Oppenheimer
Despite strong evidence that autonomy enhances motivation and achievement, few interventions for promoting student autonomy in higher education have been developed and empirically tested. Here, we demonstrate how two autonomy-supportive policies effectively increase classroom attendance and subject mastery. First, in a…
Seiki Ubukata, Sebastian Ventura
Hard C-means (HCM; k-means) is one of the most widely used partitive clustering techniques. However, HCM is strongly affected by noise objects and cannot represent cluster overlap. To reduce the influence of noise objects, objects distant from cluster centers are rejected in some noise rejection approaches including…
Authors not listed
The value of generative artificial intelligence (AI) for teaching and learning is currently hotly debated. Concerns regarding the accuracy of information produced by generative AI as well as student over-reliance on this tool coexist with excitement about tailored opportunities that AI may provide for educational…
Katharina Voigt, Carsten Murawski, Sebastian Speer, Stefan Bode
Hard decisions between equally valued alternatives can result in preference changes, meaning that subsequent valuations for chosen items increase and decrease for rejected items. Previous research suggests that this phenomenon is a consequence of cognitive dissonance reduction after the decision, induced by the…
Jason D. Hartline, Liren Shan, Yingkai Li, Yifan Wu
This paper develops a framework for the design of scoring rules to optimally incentivize an agent to exert a multi-dimensional effort. This framework is a generalization to strategic agents of the classical knapsack problem (cf. Briest, Krysta, and V¨ocking, 2005; Singer, 2010) and it is foundational to applying…
Kyoung Whan Choe, Jalisha B. Jenifer, Christopher S. Rozek, Marc G. Berman + 1 more
'Marc G. Berman' 'Sian L. Beilock'] Math anxiety predicts how much effort people are willing to put into doing math.
Jiushu Xie, Zhi Lu, Ruiming Wang, Zhenguang G. Cai
Previous studies have found that bodily stimulation, such as hardness biases social judgment and evaluation via metaphorical association; however, it remains unclear whether bodily stimulation also affects cognitive functions, such as memory and creativity. The current study used metaphorical associations between…
Ilmari Määttänen, Emilia Makkonen, Markus Jokela, Johanna Närväinen + 4 more
The aim of this exploratory study was to create a behavioural measure for trait(s) that reflect the ability and motivation to continue an unpleasant behaviour, i.e. perseverance or persistence, and to measure its correlates to several variables. We utilised six different tasks with 54 subjects to measure the…
Maria Paula Armenta, Sébastien Hélie, Bjørn T. Bakken
While loss aversion is a well-established phenomenon, less is known about how repeated feedback in gain or loss contexts changes effortful decisions over time. We hypothesized that repeated loss framing may reduce the willingness to take risks to avoid losses. To test this hypothesis, participants completed 108 trials…
Authors not listed
Chemical hardness is one of the fundamental concepts in chemical reactivity theory, rigorously defined within the framework of Conceptual Density Functional Theory (CDFT). The associated maximum hardness principle (MHP), which postulates that, a favorable direction of reaction is towards the state of maximum hardness…
Authors not listed
Specifications grading is an alternative grading system that has been used with increasing frequency in higher education. Since first introduced by Linda Nilson in 2014, more than 91 publications on the design and implementation of specifications grading systems have been published. This work presents a systematic…
Henrikke Dybvik, Christian Kuster Erichsen, Chris Snider, Martin Steinert
'Martin Steinert'] This study used functional near-infrared spectroscopy (fNIRS), electroencephalography (EEG), electrocardiography (ECG), electrodermal activity (EDA), performance, and subjective self-reports to investigate cognitive load and stress in a complex, dynamically changing environment. A total of 30…
Juan P. Franco, Karlo Doroc, Nitin Yadav, Peter Bossaerts + 1 more
The survival of human organisms depends on our ability to solve complex tasks in the face of limited cognitive resources. However, little is known about the factors that drive the complexity of those tasks. Here, building on insights from computational complexity theory, we quantify the computational hardness of…
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Physics-based methods such as protein-ligand binding free energy calculations have been increasingly adopted in early-stage drug discovery to prioritize promising compounds for synthesis. However, the accuracy of these methods is highly dependent on details of the calculation and choices made while preparing the…
Claire A. Hales, Mason M. Silveira, Lucas Calderhead, Leili Mortazavi + 2 more
The rat Cognitive Effort Task (rCET), a rodent model of cognitive rather than physical effort, requires animals to choose between an easy or hard visuospatial discrimination, with a correct hard choice more highly rewarded. Like in humans, there is stable individual variation in choice behavior. In previous reports…
Iman Feghhi, John M. Franchak, David A. Rosenbaum
What makes a task hard or easy? The question seems easy, but answering it has been hard. The only consensus has been that, all else being equal, easy tasks can be performed by more individuals than hard tasks, and easy tasks are usually preferred over hard tasks. Feghhi and Rosenbaum (Journal of Experimental…
Anne Löffler, Ariel Zylberberg, Michael N. Shadlen, Daniel M. Wolpert
Deciding how difficult it is going to be to perform a task allows us to choose between tasks, allocate appropriate resources, and predict future performance. To be useful for planning, difficulty judgments should not require completion of the task. Here we examine the processes underlying difficulty judgments in a…