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Why are Adaptive Methods Good for Attention Models? [article]

Jingzhao Zhang, Sai Praneeth Karimireddy, Andreas Veit, Seungyeon Kim, Sashank J Reddi, Sanjiv Kumar, Suvrit Sra
2020 arXiv   pre-print
The settings under which SGD performs poorly in comparison to adaptive methods are not well understood yet.  ...  We provide the first tight upper and lower convergence bounds for adaptive gradient methods under heavy-tailed noise.  ...  training attention models.  ... 
arXiv:1912.03194v2 fatcat:eyzh4eiswbhybjahjbvktu47he

An evolutionary model of premenstrual syndrome

Chris Reiber
2008 Medical Hypotheses  
cycle for some women.  ...  PMS is not evolutionarily adaptive in and of itself.  ...  Funding for this work was provided by an Andrew W.  ... 
doi:10.1016/j.mehy.2007.08.031 pmid:18053655 fatcat:hajgceo6t5depfj4ziibcjsaoi

Open-Domain Dialogue Generation Based on Pre-trained Language Models [article]

Yan Zeng, Jian-Yun Nie
2020 arXiv   pre-print
We then propose two correction methods to reduce the discrepancies, and both improve the model performance.  ...  Pre-trained language models have been successfully used in response generation for open-domain dialogue.  ...  The choice of a pre-trained language model and the way to adapt it are still an art.  ... 
arXiv:2010.12780v1 fatcat:66lxzni7zjctrpl35mcfd3vdyy

Visualizing and Explaining Language Models [article]

Adrian M.P. Braşoveanu, Răzvan Andonie
2022 arXiv   pre-print
Due to their black-box nature, such models are difficult to interpret and explain to third parties.  ...  the underlying models.  ...  This dynamic nature of the explainability is rarely explained, but it is one of the reason why visualizations in particular are a good fit for creating explanations in the first place.  ... 
arXiv:2205.10238v1 fatcat:z5vtlhx62fe25mmdxytpi3k2o4

Symbolic Models and Emergent Models: A Review

Juyang Weng
2012 IEEE Transactions on Autonomous Mental Development  
There exists a large conceptual gap between symbolic models and emergent models for the mind.  ...  A fundamental challenge for emergent models is abstraction, which symbolic models enjoy through human handcrafting. The term abstract refers to properties disassociated with any particular form.  ...  Adapted from Horn & Schunck [59]. 3-D shape of the object being modeled are of primary interest.  ... 
doi:10.1109/tamd.2011.2159113 fatcat:op2i6qg2frc6fcflzg7g5lv4uy

User-centric Integration of Contexts for A Unified Context-aware Application Model

Yoosoo Oh, Sangho Lee, Woontack Woo
2005 Internaltional Workshop on Personalized Context Modeling and Management for UbiComp Applications  
In this paper, we propose a unified method of user-centric integration of contexts for context-aware applications.  ...  However, the existing research activities don't consider much how contexts are integrated in a unified way.  ...  ACKNOWLEDGMENT We'd like to thank to Dahee Kim (Virtual Simulator Design) and Wonwoo Lee (Technical support for MRWindow).  ... 
dblp:conf/ubipcmm/OhLW05 fatcat:53ltowb3tjhg5aps2fyww7u3da

Beware the Rationalization Trap! When Language Model Explainability Diverges from our Mental Models of Language [article]

Rita Sevastjanova, Mennatallah El-Assady
2022 arXiv   pre-print
We further emphasize the need for human-centered design to explain the model from multiple perspectives, progressively adapting explanations to changing user expectations.  ...  We introduce a decision tree model to showcase potential reasons why current explanations fail to reach their objectives.  ...  It is assumed that users can easily understand why models make their decisions or when models pay attention to the wrong words [Fleisher, 2021] by examining the most salient part(s) in the text.  ... 
arXiv:2207.06897v1 fatcat:g6ezni2d3ncwhjnfpp764c2dqi

Reasoning Through Models [chapter]

Bernhard Thalheim
2022 Frontiers in Artificial Intelligence and Applications  
They are universal instruments. Reasoning through and by models is, however, different from those that we use in 'exact' sciences and is far less understood.  ...  Models are used everywhere, in daily life, sciences, engineering, and thoughts. They represent, support, and enable our thinking, acting, reflecting, communication, and understanding.  ...  , context-enhancement, assumptionslicing with attention restriction, why-it-must-be, why-this-question-and-notother, why-not-rephrasing, observation-in-context dependencies, immersioninto-context, why-finish  ... 
doi:10.3233/faia210479 fatcat:vkdei3p36vcmjpzn6ynr6hs6eq

Building an Automated Modeling System to Explore a Universe of Spatial Interaction Models

Stan Openshaw
2010 Geographical Analysis  
A number of automatic methods for identifying “goodmodels exist, for instance, step-wise regression and the automatic inter- action detector.  ...  model-building methods.  ... 
doi:10.1111/j.1538-4632.1988.tb00161.x fatcat:4ljlyayjjvb5jjs3nmdtlxm7zu

The ground state of the two-dimensional Hubbard model

Yoshihiro Asai
2000 Physica. B, Condensed matter  
We have studied the ground state of the two-dimensional Hubbard model by using the adaptive sampling quantum monte carlo method.  ...  mixed estimator method for measurements and its variants which are indispensable to the CP method.  ...  This should be one of the main reasons why our ASQMC method gives more accurate results than the CP method.  ... 
doi:10.1016/s0921-4526(99)00875-3 fatcat:boxycfhtanbdtgwjnuiqqj7s2a

Models for Understanding

Richard E. Mayer
1989 Review of Educational Research  
One promising instructional technique for improving students' understanding of scientific explanations is the use of conceptual models.  ...  What can be done to empower students to be creative when they are faced with problems?  ...  Good models are presented at a level of detail that is appropriate for the learner.  ... 
doi:10.3102/00346543059001043 fatcat:lwwcpzp2nzf4lm2b46du5tyyqi

Models for Understanding

Richard E. Mayer
1989 Review of Educational Research  
One promising instructional technique for improving students' understanding of scientific explanations is the use of conceptual models.  ...  What can be done to empower students to be creative when they are faced with problems?  ...  Good models are presented at a level of detail that is appropriate for the learner.  ... 
doi:10.2307/1170446 fatcat:5xnawo3borczhcmhy3op3jqpfu

Identifying models of environmental systems' behaviour

M.B. Beck
1982 Mathematical Modelling  
This paper addresses the question of how theories are developed about the behaviour of large, complex systems such as those typically encountered in managing environmental quality.  ...  The specific problem considered is that of model structure identification by reference to experimental, in situ field data.  ...  Department of the Environment for permission to use the field data from the Bedford Ouse Study.  ... 
doi:10.1016/0270-0255(82)90043-4 fatcat:pfe2u4lngjbwjmejsxhxhi5gxm

Improved Attention Models for Memory Augmented Neural Network Adaptive Controllers [article]

Deepan Muthirayan, Scott Nivison, Pramod P. Khargonekar
2020 arXiv   pre-print
In the above work, we used a soft-attention mechanism for the adaptive controller.  ...  Controllers that use soft attention or hard attention mechanisms are limited either because they can forget the information or fail to shift attention when the information they are reading becomes less  ...  The natural question to ask is what is a good attention mechanism for such an application?  ... 
arXiv:1910.01189v7 fatcat:6xjsmsxbbjfgbmygkebccozu6y
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