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Online supervised incremental learning of link quality estimates in wireless networks

Gianni A. Di Caro, Michal Kudelski, Eduardo Feo Flushing, Jawad Nagi, Imran Ahmed, Luca M. Gambardella
2013 2013 12th Annual Mediterranean Ad Hoc Networking Workshop (MED-HOC-NET)  
We address the problem of link quality estimation in wireless networks and propose a distributed online protocol based on supervised incremental learning.  ...  A node uses these measurements as labeled training samples for the incremental and supervised learning of the regression mapping from a local network configuration to a link quality estimate.  ...  CONCLUSIONS AND FUTURE WORK We proposed LQL, a protocol for the on-line supervised incremental learning of link quality estimates in wireless networks, both static and mobile.  ... 
doi:10.1109/medhocnet.2013.6767422 dblp:conf/medhocnet/CaroKFNAG13 fatcat:le57dt7zb5h5ln6jvfmgg3bu4q

Fast Incremental Link Insertion in Clock Networks for Skew Variability Reduction

A. Rajaram, D.Z. Pan
7th International Symposium on Quality Electronic Design (ISQED'06)  
Our method also incrementally considers the effect of previously inserted links before choosing the next link.  ...  With the advent of sub-100nm VLSI technologies, variation effects greatly increase the unwanted skew in Clock Distribution Networks (CDNs), thereby reducing the performance of the chip.  ...  Figure 1 . 1 A simple link-based clock network. Figure 2 . 2 A simple nontree where incremental approach might help.  ... 
doi:10.1109/isqed.2006.66 dblp:conf/isqed/RajaramP06 fatcat:zerpeqys7bhgzplcks4kwsowga

Mugshot database acquisition in video surveillance networks using incremental auto-clustering quality measures

Quanren Xiong, C. Jaynes
Proceedings of the IEEE Conference on Advanced Video and Signal Based Surveillance, 2003.  
• Quanren Xiong and Christopher Jaynes, Mugshot Database Acquisition in Video Surveillance Networks using Incremental Auto-Clustering Quality Measures, IEEE Conference on Advanced Video and Signal Based  ...  Track skin regions and assign an faceness score measuring quality of tracked face for recognition: vertical symmetry, deviation from skin tone, overall resolution and focus -quality mugshots are added  ... 
doi:10.1109/avss.2003.1217921 dblp:conf/avss/XiongJ03 fatcat:h45xh5ij3zhlnpfonqztzm62ha

Incremental Learning of Multi-tasking Networks for Aesthetic Radar Map Prediction

Xin Jin, Xinghui Zhou, Xiaodong Li, Xiaokun Zhang, Hongbo Sun, Xiqiao Li, Ruijun Liu
2019 IEEE Access  
This allows the network model to fit different attributes in various datasets better. INDEX TERMS Neural network, multitasking, computer vision, incremental learning.  ...  In this paper, we propose a multi-task convolution neural network with more incremental features. We show the results in the way of a hexagon map, which is called aesthetic radar map.  ...  FIGURE 5 . 5 Predicted results of extra aesthetic quality attributes of testing photos with incremental learning. 20] Lu et al. used deep convolutional networks for marine organism classification, and  ... 
doi:10.1109/access.2019.2958119 fatcat:vrqmh577ivhinimnebcflctqf4

Network structure of innovation: can brokerage or closure predict patent quality?

Jyun-Cheng Wang, Cheng-hsin Chiang, Shu-Wei Lin
2010 Scientometrics  
Social network analysis was applied to analyze two complementary network positions occupied by a patent brokerage and closure to determine whether either position predicts patent quality.  ...  This paper examines whether patent quality can be predicted a priori, i.e., at an early stage after a patent is granted by analyzing information embedded in a network of patent citations.  ...  Patent quality was defined in terms of increments citation counts and maintenance year.  ... 
doi:10.1007/s11192-010-0211-y fatcat:2m3nkjfninalxn6guwuppf6jnm

Low-Latency Incremental Text-to-Speech Synthesis with Distilled Context Prediction Network [article]

Takaaki Saeki, Shinnosuke Takamichi, Hiroshi Saruwatari
2021 arXiv   pre-print
Experimental results show that the proposed method requires about ten times less inference time to achieve comparable synthetic speech quality to that of our previous method, and it can perform incremental  ...  We perform knowledge distillation from a GPT2-based context prediction network into a simple recurrent model by minimizing a teacher-student loss defined between the context embedding vectors of those  ...  Fig. 1 . 1 Proposed incremental TTS method with distilled context prediction network.  ... 
arXiv:2109.10724v1 fatcat:aps77vtzwbgh3a4pcgh7yo3qee

Local search algorithms for reserved delivery subnetwork configuration problems with cycle and bicycle reduction

Ruibiao Qiu, J.S. Turner
2005 GLOBECOM '05. IEEE Global Telecommunications Conference, 2005.  
Our simulation results show that the local search algorithms improve the quality of LDF solutions, but with added computational complexity.  ...  In this paper, we apply local search algorithms based on negative cost cycle and bicycle reduction to further improve the quality of the results obtained from LDF.  ...  To study the solution quality improvements by these two local search algorithms, we evaluated both local search algorithms on a number of network topologies.  ... 
doi:10.1109/glocom.2005.1577733 dblp:conf/globecom/QiuT05 fatcat:g5pslmbfoffallhp3mumdec734

Incremental Text-to-Speech Synthesis Using Pseudo Lookahead with Large Pretrained Language Model [article]

Takaaki Saeki, Shinnosuke Takamichi, Hiroshi Saruwatari
2021 arXiv   pre-print
Incremental TTS is generally subject to a trade-off between latency and synthetic speech quality.  ...  Evaluation results show that our method 1) achieves higher speech quality than the method taking only observed information into account and 2) achieves a speech quality equivalent to waiting for the future  ...  Incremental TTS is generally subject to a trade-off between latency and synthetic speech quality.  ... 
arXiv:2012.12612v2 fatcat:rhpy4jho6rd2bc665sm6zircui

The Incremental Deployability of Core–Stateless Fair Queuing [chapter]

Yannick Blanpain, Hung-Yun Hsieh, Raghupathy Sivakumar
2001 Lecture Notes in Computer Science  
We define incremental deployability as the ability of the approach to gracefully provide increasingly better quality of service with each additional QoS-aware router deployed in the network.  ...  We use the ns2 network simulator for the simulations. We conclude that CSFQ does not exhibit good incremental deployability.  ...  In the context of quality of service architectures, we define incrementally deployability as the ability to provide increasingly better quality of service with increasing number of QoS-aware routers.  ... 
doi:10.1007/3-540-47734-9_26 fatcat:caj7ktdrobdvndh5unamjvtuq4

Incremental local community identification in dynamic social networks

Mansoureh Takaffoli, Reihaneh Rabbany, Osmar R. Zaïane
2013 Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining - ASONAM '13  
Compared to previous independent approaches, this incremental approach is more effective at detecting stable communities over time.  ...  In this paper, we introduce a new incremental community mining approach, in which communities in the current time are obtained based on the communities from the past time frame.  ...  The FacetNet communities are different than those found by the Independent and Incremental L-metric methods. And at the same time, have lower quality index of DQ.  ... 
doi:10.1145/2492517.2492633 dblp:conf/asunam/TakaffoliRZ13 fatcat:jpti6h2dwfdynipanilk7dyaie

Incremental Community Mining in Location-based Social Network

Loubna Boujlaleb, Ali Idarrou, Driss Mammass
2018 International Journal of Advanced engineering Management and Science  
In this respect, we extend the static Louvain method to incrementally detect communities in a dynamic scenario following the direct method and considering both overlapping and non-overlapping setting.  ...  of these networks.  ...  We can evidently observe that incremental approach is constantly discovering communities with important quality regarding both recent and temporal information.  ... 
doi:10.22161/ijaems.4.8.8 fatcat:aorzhp7nfrfg3ik6hgads5putu

Incremental Text-to-Speech Synthesis Using Pseudo Lookahead with Large Pretrained Language Model

Takaaki Saeki, Shinnosuke Takamichi, Hiroshi Saruwatari
2021 IEEE Signal Processing Letters  
Incremental TTS is generally subject to a trade-off between latency and synthetic speech quality.  ...  The first attempt at end-to-end neural incremental TTS [12] uses a Tacotron [10] based model to achieve high-quality synthesis.  ... 
doi:10.1109/lsp.2021.3073869 fatcat:6n476znndnff5p6t3yj5uxjvwa

RBF-Based QP Estimation Model for VBR Control in H.264/SVC

Sergio Sanz-Rodriguez, Fernando Diaz-de-Maria
2011 IEEE transactions on circuits and systems for video technology (Print)  
In particular, the QP increment estimation at each layer is computed by means of a radial basis function (RBF) network that is specially designed for this purpose.  ...  Furthermore, the RBF network design process was conceived to provide an effective solution for a wide range of practical real-time VBR applications for scalable video content delivery.  ...  Both QP increment models are named key-picture and nonkey-picture RBF networks to emphasize that dependence on the frame type.  ... 
doi:10.1109/tcsvt.2011.2143330 fatcat:krzpyn7k5nhhfmxiwdodkgrrrm

Continual learning of neural networks for quality prediction in production using memory aware synapses and weight transfer

Hasan Tercan, Philipp Deibert, Tobias Meisen
2021 Journal of Intelligent Manufacturing  
AbstractDeep learning-based predictive quality enables manufacturing companies to make data-driven predictions of the quality of a produced product based on process data.  ...  In this paper, we address this problem and propose a method for continual learning in such predictive quality scenarios.  ...  Thereby, all increments are conducted in a sequential way. The learning of the first (base) task involves an untrained network and is regarded as the zeroth increment.  ... 
doi:10.1007/s10845-021-01793-0 fatcat:en257nxqefgbdfpkmrc35nu25i

Memory-Efficient Incremental Learning Through Feature Adaptation [article]

Ahmet Iscen, Jeffrey Zhang, Svetlana Lazebnik, Cordelia Schmid
2020 arXiv   pre-print
Feature adaptation is learned with a multi-layer perceptron, which is trained on feature pairs corresponding to the outputs of the original and updated network on a training image.  ...  We introduce an approach for incremental learning that preserves feature descriptors of training images from previously learned classes, instead of the images themselves, unlike most existing work.  ...  We preserve and adapt feature descriptors to new feature spaces as the network is trained incrementally.  ... 
arXiv:2004.00713v2 fatcat:o6dc534jdbgojpmp4wcmezrkoq
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