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Interpreting and Boosting Dropout from a Game-Theoretic View [article]

Hao Zhang, Sen Li, Yinchao Ma, Mingjie Li, Yichen Xie, Quanshi Zhang
2021 arXiv   pre-print
Based on this understanding, we propose an interaction loss to further improve the utility of dropout.  ...  This paper aims to understand and improve the utility of the dropout operation from the perspective of game-theoretic interactions.  ...  Hinton et al. (2012) ; Srivastava et al. (2014) thought that dropout could encourage each unit in an intermediate-layer feature to model useful information without much dependence on other units.  ... 
arXiv:2009.11729v4 fatcat:wjr4rqe6ezec5fdsrzdjzmokwi

SI-VDNAS: Semi-Implicit Variational Dropout for Hierarchical One-shot Neural Architecture Search

Yaoming Wang, Wenrui Dai, Chenglin Li, Junni Zou, Hongkai Xiong
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
In this paper, we propose a novel probabilistic approach, namely Semi-Implicit Variational Dropout one-shot Neural Architecture Search (SI-VDNAS), that leverages semi-implicit variational dropout to support  ...  CSALR in Deep Metric Learning The proposed CSALR module can be easily applied to the existing backbones to capture long-range contextual dependencies efficiently, providing a general framework for deep  ...  ., 2017] , which can capture long-range contextual dependencies adaptively.  ... 
doi:10.24963/ijcai.2020/285 dblp:conf/ijcai/ChenGGD20 fatcat:3ca6iti3crbpxar246i5lkrcpy

Dropout of adult learners returning to university: interactions of motivational and environmental factors

Frenay, M., Jacot, A., Cazan, A.-M.
2010 Bulletin of the Transilvania University of Braşov: Series VII: Social Sciences, Law  
The purpose of this paper is to highlight how motivational and contextual factors interact together to explain the dropout process of adult learners returning to university.  ...  The findings from this study indicated that studying dropout of adult learners with motivational factors enables a deeper understanding taking into account the different commitments of this population  ...  In the context of adult learners and according to the identity dynamic theory, their engagement depends on the relevance and efficiency of the educational program to reach their identity goals.  ... 
doaj:770db3d6385d44ada4c72f825f86f729 fatcat:eetg4oigoravxirqvx7zogypja

Contextual RNN-T For Open Domain ASR [article]

Mahaveer Jain, Gil Keren, Jay Mahadeokar, Geoffrey Zweig, Florian Metze, Yatharth Saraf
2020 arXiv   pre-print
We evaluate our approach on an in-house dataset sampled from de-identified public social media videos, which represent an open domain ASR task.  ...  By using an attention model and a biasing model to leverage the contextual metadata that accompanies a video, we observe a relative improvement of about 16% in Word Error Rate on Named Entities (WER-NE  ...  (EE), an Attention Module (AttModule) and a Biasing Module (BiasingModule) as shown in Figure 2 .  ... 
arXiv:2006.03411v2 fatcat:cwjn4eeiyrc4lcraeeqx6bg2qa

Maps Search Misspelling Detection Leveraging Domain-Augmented Contextual Representations [article]

Yutong Li
2021 arXiv   pre-print
Building an independent misspelling detector and serve it before correction can bring multiple benefits to speller and other search components, which is particularly true for the most commonly deployed  ...  With rapid development of deep learning and substantial advancement in contextual representation learning such as BERTology, building a decent misspelling detector without having to rely on hand-crafted  ...  Algorithm The central mission for such an algorithm is to generate high quality pairs, Q(misspelt query) -> C(ground-truth correction), freely, accurately and at large scale, no dependency on human judgement  ... 
arXiv:2108.06842v1 fatcat:4crfyqzlvbhirebragmeoekgbu

Contextual RNN-T for Open Domain ASR

Mahaveer Jain, Gil Keren, Jay Mahadeokar, Geoffrey Zweig, Florian Metze, Yatharth Saraf
2020 Interspeech 2020  
We evaluate our approach on an in-house dataset sampled from deidentified public social media videos, which represent an open domain ASR task.  ...  By using an attention model to leverage the contextual metadata that accompanies a video, we observe a relative improvement of about 16% in Word Error Rate on Named Entities (WER-NE) for videos with related  ...  Contextual RNN-T We modify the base RNN-T model described in Section 3 and add three additional components: an Embedding Extractor (EE), an Attention Module (AttModule) and (optionally) a Biasing Module  ... 
doi:10.21437/interspeech.2020-2986 dblp:conf/interspeech/JainKMZMS20 fatcat:pluyzzp47ngfhgh4ws4277ofzy

Dissecting Contextual Word Embeddings: Architecture and Representation [article]

Matthew E. Peters, Mark Neumann, Luke Zettlemoyer, Wen-tau Yih
2018 arXiv   pre-print
Contextual word representations derived from pre-trained bidirectional language models (biLMs) have recently been shown to provide significant improvements to the state of the art for a wide range of NLP  ...  We show there is a tradeoff between speed and accuracy, but all architectures learn high quality contextual representations that outperform word embeddings for four challenging NLP tasks.  ...  Billion Word Benchmark (Chelba et al., 2014) using a sampled softmax with 8192 negative samples per batch.  ... 
arXiv:1808.08949v2 fatcat:ogd5bpuwmjfd7j57lnrq6fxfxq

Time-Series Representation Learning via Temporal and Contextual Contrasting [article]

Emadeldeen Eldele, Mohamed Ragab, Zhenghua Chen, Min Wu, Chee Keong Kwoh, Xiaoli Li, Cuntai Guan
2021 arXiv   pre-print
Last, to further learn discriminative representations, we propose a contextual contrasting module built upon the contexts from the temporal contrasting module.  ...  In this paper, we propose an unsupervised Time-Series representation learning framework via Temporal and Contextual Contrasting (TS-TCC), to learn time-series representation from unlabeled data.  ...  In this contextual contrasting module, we aim to maximize the similarity among different contexts of the same sample while minimizing similarity among contexts of different samples.  ... 
arXiv:2106.14112v1 fatcat:b45ts7bwungevd5jn375jnbmba

Exploiting Contextual Information with Deep Neural Networks [article]

Ismail Elezi
2020 arXiv   pre-print
To the best of our knowledge, we are the first to integrate graph-theoretical modules, carefully crafted for the problem of similarity learning and that are designed to consider contextual information,  ...  Nevertheless, there has not been much research in exploiting contextual information in deep neural networks.  ...  Another widely used deep learning-specific form of regularization is dropout [173] . Dropout in forward pass simply drops units with probability p, making every unit less dependent in its neighbors.  ... 
arXiv:2006.11706v2 fatcat:bzaghxubbzcftdsvv4ogk3tfxe

What Predicts Clinician Dropout from State-Sponsored Managing and Adapting Practice Training

S. Serene Olin, Erum Nadeem, Alissa Gleacher, James Weaver, Dara Weiss, Kimberly E. Hoagwood, Sarah McCue Horwitz
2015 Administration and Policy in Mental Health  
Dropouts from system-wide evidence-based practice trainings are high; yet there are few studies on what predicts dropouts.  ...  In 2006, NYS Office of Mental Health (OMH) established an evidence-based treatment (EBT) training center for mental health providers statewide.  ...  Clinicians' affiliation was also significantly different depending on region (Fishers exact <.001).  ... 
doi:10.1007/s10488-015-0709-y pmid:26699136 pmcid:PMC5545802 fatcat:f3vvpbvcnvdfvg77ybg3aphu6a

Patterns, Consequences, and Possible Causes of Dropout in Upper Secondary Education in Mexico

Raja Bentaouet Kattan, Miguel Székely
2015 Education Research International  
The present study provides a detailed analysis of upper secondary education dropout patterns in Mexico, exploring its consequences and possible causes.  ...  The main value added is the simultaneous analysis of the influence of individual-family, community, and macroaggregate factors, on school dropout in the country.  ...  Acknowledgments The authors thank the helpful comments and suggestions by an anonymous referee, which helped improve the paper substantially.  ... 
doi:10.1155/2015/676472 fatcat:ktmisnorlbhrbmc7chf22tky4m

Understanding in-video dropouts and interaction peaks inonline lecture videos

Juho Kim, Philip J. Guo, Daniel T. Seaton, Piotr Mitros, Krzysztof Z. Gajos, Robert C. Miller
2014 Proceedings of the first ACM conference on Learning @ scale conference - L@S '14  
We find higher dropout rates in longer videos, re-watching sessions (vs first-time), and tutorials (vs lectures).  ...  In attempting to reason why peaks occur by sampling 80 videos, we observe that 61% of the peaks accompany visual transitions in the video, e.g., a slide view to a classroom view.  ...  While our categorization is not conclusive, it provides an explanation of which semantic and contextual aspects of video might be responsible for a peak.  ... 
doi:10.1145/2556325.2566237 dblp:conf/lats/KimGSMGM14 fatcat:ys2zi3my65he5gjq6qzsufipgy

Pragmatic inference and visual abstraction enable contextual flexibility during visual communication [article]

Judith Fan, Robert Hawkins, Mike Wu, Noah Goodman
2019 arXiv   pre-print
Together, this work provides the first algorithmically explicit theory of how visual perception and social cognition jointly support contextual flexibility in visual communication.  ...  We found that people exploited shared information to efficiently communicate about the target object: on far trials, sketchers achieved high recognition accuracy while applying fewer strokes, using less  ...  We use MCMC to draw 1000 samples from the joint posterior with a lag of 0, discarding 3000 burn-in samples.  ... 
arXiv:1903.04448v2 fatcat:dk2npj6j6jcb7clhgesjv73vdu

Sato: Contextual Semantic Type Detection in Tables [article]

Dan Zhang and Yoshihiko Suhara and Jinfeng Li and Madelon Hulsebos and Çağatay Demiralp and Wang-Chiew Tan
2020 arXiv   pre-print
However, existing detection approaches either perform poorly with dirty data, support only a limited number of semantic types, fail to incorporate the table context of columns or rely on large sample sizes  ...  Additionally, we believe that high-order dependency between predictions is not always necessary if we incorporate contextual features into the model.  ...  Since table topic features provide table-wise contextual information, we consider the original CRF model with pairwise potential functions as the right choice for improving the model accuracy efficiently  ... 
arXiv:1911.06311v3 fatcat:q763z33jnvbyhjqojpuqhl3uge

Developing a model for dropout prevention and intervention in primary and secondary schools in Serbia: Assessing the model's effectiveness

Jasminka Markovic-Cekic, Jelena Radisic, Vitomir Jovanovic, Tanja Rankovic
2017 Psihološka Istraživanja  
Understanding dropout as a multidimensional and system-level phenomenon, we offer a model for dropout prevention and intervention.  ...  The paper focuses on investigating the dropout phenomena and the need for its prevention and reduction within Serbian pre-university education.  ...  students at dropout risk, drafts an individual plan for dropout prevention (IPDP).  ... 
doi:10.5937/psistra1701145m fatcat:cae2yo7pgvg7lpniem52atnemy
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