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Hierarchical Elastic Graph Matching for Hand Gesture Recognition [chapter]

Yu-Ting Li, Juan P. Wachs
2012 Lecture Notes in Computer Science  
The weights in graph's nodes are adapted according to their relative ability to enhance the recognition, and determined using adaptive boosting.  ...  A dictionary representing the variability of each gesture class is proposed, in the form of a collection of graphs (a bunch graph).  ...  The rest of the paper is organized as follows: in Section 2 the EBGM and Adaptive Boosting algorithm are described.  ... 
doi:10.1007/978-3-642-33275-3_38 fatcat:oryxoawtwjaj5gdrysrij6p5sa

Contents all nrs. if necessary

2003 Discrete Applied Mathematics  
Woeginger Recognizing DNA graphs is difficult 85 B. Schwikowski and M. Vingron Weighted sequence graphs: boosting iterated dynamic programming using locally suboptimal solutions 95 V.  ...  Miklós Algorithm for statistical alignment of two sequences derived from a Poisson sequence length distribution 79 R. Pendavingh, P. Schuurman and G.J.  ... 
doi:10.1016/s0166-218x(03)00218-x fatcat:ijjy6nwkifa77cilir2p7mf5qa

Multimodal kernel learning for image retrieval

Yen-Yu Lin, Chiou-Shann Fuh
2010 2010 International Conference on System Science and Engineering  
for each modality; 3) The adopted optimization criterion in boosting is to align with a target kernel matrix accounting for relevance feedback, and the learned multimodal kernel matrix can be used for  ...  ; 2) The base kernel matrices are derived from eigendecomposing the graph Laplacian, and further refined to satisfy a pivotal monotone property that ensures intrinsic structure will be reasonably maintained  ...  As we have described, through boosting the proposed algorithm can simultaneously address intrinsic structure preserving, kernel alignment, and multimodal fusion.  ... 
doi:10.1109/icsse.2010.5551790 fatcat:mxoes5xy75fulnt6mh77dqgus4

Tree in Tree: from Decision Trees to Decision Graphs [article]

Bingzhao Zhu, Mahsa Shoaran
2021 arXiv   pre-print
The time complexity of TnT is linear to the number of nodes in the graph, and it can construct decision graphs on large datasets.  ...  This paper introduces Tree in Tree decision graph (TnT), a framework that extends the conventional decision tree to a more generic and powerful directed acyclic graph.  ...  The proposed Tree in Tree (TnT) algorithm outperforms axis-aligned decision trees such as TAO [6, 29] and CART [15] , as well as NDG which is also based on axis-aligned decision graphs [16] .  ... 
arXiv:2110.00392v3 fatcat:lojzytrafbbtjibkqx3uivk7x4

SPECTRE: Seedless Network Alignment via Spectral Centralities [article]

Mikhail Hayhoe, Francisco Barreras, Hamed Hassani, Victor M. Preciado
2019 arXiv   pre-print
Unlike most network alignment algorithms, SPECTRE requires no seeds (i.e., pairs of nodes identified beforehand), which in many cases are expensive, or impossible, to obtain.  ...  In this work we introduce SPECTRE, a scalable algorithm that uses spectral centrality measures and percolation techniques.  ...  Our proposed algorithm leverages this idea, in conjunction with a boosting strategy, to overcome the dependance on a seed set, allowing us to obtain high-quality alignments even in moderately correlated  ... 
arXiv:1811.01056v2 fatcat:gvry7uvmzbhslpifaermeatq7u

JigsawNet: Shredded Image Reassembly using Convolutional Neural Network and Loop-based Composition [article]

Canyu Le, Xin Li
2018 arXiv   pre-print
To improve the network efficiency and accuracy, we transfer the calculation of CNN to the stitching region and apply a boost training strategy.  ...  This paper proposes a novel algorithm to reassemble an arbitrarily shredded image to its original status.  ...  Based on the above derivations, we can design the boosting algorithm for CNN training. CNN boost training.  ... 
arXiv:1809.04137v1 fatcat:ljfx4hyjwvbbbfprfxjltsdw4y

Video parsing based on head tracking and face recognition

Pengxu Li, Haizhou Ai, Yuan Li, Chang Huang
2007 Proceedings of the 6th ACM international conference on Image and video retrieval - CIVR '07  
The system is based on face vision techniques including face detection and tracking, face alignment and recognition.  ...  extracted in video by head tracking that decompose the video into segments corresponding to certain identity, then frames containing faces of higher quality are selected and normalized according to face alignment  ...  It integrates the state-of-the-art head tracking, face alignment and face recognition algorithms.  ... 
doi:10.1145/1282280.1282288 dblp:conf/civr/LiALH07 fatcat:i36tzoradzd4rc2m7ulf46rab4


Sorin Istrail, Pavel Pevzner, Ron Shamir
2003 Discrete Applied Mathematics  
They show that optimal alignment is hard in this context, but provide a polynomial approximation algorithm.  ...  In "Weighted sequence graphs: Boosting iterated dynamic programming using locally suboptimal solutions", Schwikowski and Vingron contribute to this ÿeld by developing a framework for iterated dynamic programming  ... 
doi:10.1016/s0166-218x(02)00281-0 fatcat:jcjjjakle5alzl75eiy7i2lvb4

Review of General Algorithmic Features for Genome Assemblers for Next Generation Sequencers

Bilal Wajid, Erchin Serpedin
2012 Genomics, Proteomics & Bioinformatics  
Concepts like string graphs, bidirected graphs and de Bruijn graphs have had a deep impact on assembly algorithms [28] [29] [30] [31] [32] [33] [34] [35] .  ...  (C) The multiple alignment algorithms take a collection of unique k-mers.  ... 
doi:10.1016/j.gpb.2012.05.006 pmid:22768980 pmcid:PMC5054208 fatcat:ole4f3n5crdzzpczrqqmkettsa

Boosting Relational Sequence Alignments

Andreas Karwath, Kristian Kersting, Niels Landwehr
2008 2008 Eighth IEEE International Conference on Data Mining  
Relational sequence alignment aims at exploiting symbolic structure to avoid the full enumeration.  ...  As our experimental results show, this boosting approach can significantly improve upon established results in challenging applications.  ...  We call the resulting algorithm "boosted relational alignment" or short BOOSTEDREAL.  ... 
doi:10.1109/icdm.2008.127 dblp:conf/icdm/KarwathKL08 fatcat:tbjfhji22vggxl6yn3cyk55qi4

Learning Heat Diffusion for Network Alignment [article]

Sisi Qu, Mengmeng Xu, Bernard Ghanem, Jesper Tegner
2020 arXiv   pre-print
Yet, network alignment remains a core algorithmic problem. Here, we present a novel learning algorithm called evolutionary heat diffusion-based network alignment (EDNA) to address this challenge.  ...  The EDNA algorithm is versatile in that other available network alignments/embeddings can be used as an initial baseline alignment, and then EDNA works as a wrapper around them by running the evolutionary  ...  After applying heat diffusion using the signals of anchor alignment nodes to the whole graph T times, the evolutionary algorithm can be harnessed to fine-tune the diffusion parameter Θ to further improve  ... 
arXiv:2007.05401v1 fatcat:psh4n53chnb3lmast6jegikbsa

Compositional Boosting for Computing Hierarchical Image Structures

Tian-Fu Wu, Gui-Song Xia, Song-Chun Zhu
2007 2007 IEEE Conference on Computer Vision and Pattern Recognition  
The algorithm runs recursively for each node A in the And-Or graph and iterates between two steps -bottom-up proposal and top-down validation.  ...  Then we present a compositional boosting algorithm for computing the 17 graphlets categories collectively in the Bayesian framework.  ...  The algorithm runs recursively for each node A in the And-Or graph and iterate two steps -bottom-up proposal and top-down validation. The bottom-up step includes two types of boosting methods. 1.  ... 
doi:10.1109/cvpr.2007.383034 dblp:conf/cvpr/WuXZ07 fatcat:qa6ykvt7und53bpqebljq3gibi

Joint Real-time Object Detection and Pose Estimation Using Probabilistic Boosting Network

Jingdan Zhang, Shaohua Kevin Zhou, Leonard McMillan, Dorin Comaniciu
2007 2007 IEEE Conference on Computer Vision and Pattern Recognition  
Grounded on the law of total probability, PBN integrates evidence from two building blocks, namely a multiclass boosting classifier for pose estimation and a boosted detection cascade for object detection  ...  We implement PBN using a graph-structured network that alternates the two tasks of foreground/background discrimination and pose estimation for rejecting negatives as quickly as possible.  ...  This algorithm is grounded on the multiclass version of the influential boosting algorithm proposed by Friedman et al.  ... 
doi:10.1109/cvpr.2007.383275 dblp:conf/cvpr/ZhangZMC07 fatcat:j3ahhvx46ngc5feyiy2ipzrqgq

Author index (last vol./issue)

2003 Discrete Applied Mathematics  
Quint, Sphere of influence graphs and the L N -metric (3) 447-460 Miklo´s, I., Algorithm for statistical alignment of two sequences derived from a Poisson sequence length distribution (1) 79-84 Miller,  ...  Vingron, Weighted sequence graphs: boosting iterated dynamic programming using locally suboptimal solutions (1) 95-117 Semple, C., Reconstructing minimal rooted trees (3) 489-503 Author Index / Discrete  ... 
doi:10.1016/s0166-218x(03)00253-1 fatcat:sgubg2yg6zbzled43mz5troizy

The IBM Attila speech recognition toolkit

Hagen Soltau, George Saon, Brian Kingsbury
2010 2010 IEEE Spoken Language Technology Workshop  
The uniform alignments initialize context-independent (CI) models, which are refined using the Baum-Welch algorithm.  ...  An alignment can be populated using several different methods: Viterbi, Baum-Welch, modified forwardbackward routines over lattices for minimum phone error (MPE) or boosted MMI training, uniform segmentation  ... 
doi:10.1109/slt.2010.5700829 dblp:conf/slt/SoltauSK10 fatcat:iovd5e6abnbvrfpnvm6iml7euq
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