Search Results for author: Yue Zhao

Found 68 papers, 33 papers with code

ELODI: Ensemble Logit Difference Inhibition for Positive-Congruent Training

no code implementations12 May 2022 Yue Zhao, Yantao Shen, Yuanjun Xiong, Shuo Yang, Wei Xia, Zhuowen Tu, Bernt Schiele, Stefano Soatto

We present a method to train a classification system that achieves paragon performance in both error rate and NFR, at the inference cost of a single model.

A Deep Reinforcement Learning Framework for Rapid Diagnosis of Whole Slide Pathological Images

no code implementations5 May 2022 Tingting Zheng, Weixing Chen, Shuqin Li, Hao Quan, Qun Bai, Tianhang Nan, Song Zheng, Xinghua Gao, Yue Zhao, Xiaoyu Cui

Inspired by the pathologist's clinical diagnosis process, we propose a weakly supervised deep reinforcement learning framework, which can greatly reduce the time required for network inference.

Knowledge Distillation reinforcement-learning +1

Gaussian Kernel Variance For an Adaptive Learning Method on Signals Over Graphs

no code implementations26 Apr 2022 Yue Zhao, Ender Ayanoglu

To be more specific, we focus on SKG with a Gaussian kernel and specify how to find a suitable variance for the kernel.

Two-Stream Graph Convolutional Network for Intra-oral Scanner Image Segmentation

1 code implementation19 Apr 2022 Yue Zhao, Lingming Zhang, Yang Liu, Deyu Meng, Zhiming Cui, Chenqiang Gao, Xinbo Gao, Chunfeng Lian, Dinggang Shen

The state-of-the-art deep learning-based methods often simply concatenate the raw geometric attributes (i. e., coordinates and normal vectors) of mesh cells to train a single-stream network for automatic intra-oral scanner image segmentation.

Graph Learning Semantic Segmentation

Combining Individual and Joint Networking Behavior for Intelligent IoT Analytics

no code implementations7 Mar 2022 Jeya Vikranth Jeyakumar, Ludmila Cherkasova, Saina Lajevardi, Moray Allan, Yue Zhao, John Fry, Mani Srivastava

In this work, we design a novel, scalable approach, where a general demand forecasting model is built using the combined data of all the companies with a normalization factor.

Learning Robust Representation through Graph Adversarial Contrastive Learning

no code implementations31 Jan 2022 Jiayan Guo, Shangyang Li, Yue Zhao, Yan Zhang

Existing studies show that node representations generated by graph neural networks (GNNs) are vulnerable to adversarial attacks, such as unnoticeable perturbations of adjacent matrix and node features.

Contrastive Learning Graph Representation Learning +2

ECOD: Unsupervised Outlier Detection Using Empirical Cumulative Distribution Functions

1 code implementation2 Jan 2022 Zheng Li, Yue Zhao, Xiyang Hu, Nicola Botta, Cezar Ionescu, George H. Chen

To address these issues, we present a simple yet effective algorithm called ECOD (Empirical-Cumulative-distribution-based Outlier Detection), which is inspired by the fact that outliers are often the "rare events" that appear in the tails of a distribution.

Outlier Detection

BA-Net: Bridge Attention for Deep Convolutional Neural Networks

1 code implementation8 Dec 2021 Yue Zhao, Junzhou Chen, Zirui Zhang, Ronghui Zhang

The core idea of this design is to bridge the outputs of the previous convolution layers through skip connections for channel weights generation.

Automatic Unsupervised Outlier Model Selection

no code implementations NeurIPS 2021 Yue Zhao, Ryan Rossi, Leman Akoglu

Given an unsupervised outlier detection task on a new dataset, how can we automatically select a good outlier detection algorithm and its hyperparameter(s) (collectively called a model)?

Meta-Learning Model Selection +1

Federated Learning Based on Dynamic Regularization

1 code implementation ICLR 2021 Durmus Alp Emre Acar, Yue Zhao, Ramon Matas Navarro, Matthew Mattina, Paul N. Whatmough, Venkatesh Saligrama

We propose a novel federated learning method for distributively training neural network models, where the server orchestrates cooperation between a subset of randomly chosen devices in each round.

Federated Learning

TOD: Tensor-based Outlier Detection

1 code implementation26 Oct 2021 Yue Zhao, George H. Chen, Zhihao Jia

Second, to exploit the aggregated compute resources and memory capacity of multiple GPUs, we introduce automatic batching, which decomposes OD computations into small batches that can be executed on multiple GPUs in parallel.

Outlier Detection Quantization

3D Dental model segmentation with graph attentional convolution network

no code implementations Pattern Recognition Letters 2021 Yue Zhao, Lingming Zhang, Chongshi Yang, Yingyun Tan, Yang Liu, Pengcheng Li, Tianhao Huang, Chenqiang Gao

We have evaluated our network on a real-patient dataset of dental models acquired through 3D intraoral scanners, and experimental results show that our method outperforms state-of-the-art deep learning methods for 3D shape segmentation.

Local Patch Network with Global Attention for Infrared Small Target Detection

no code implementations13 Aug 2021 Fang Chen, Chenqiang Gao, Fangcen Liu, Yue Zhao, Yuxi Zhou, Deyu Meng, WangMeng Zuo

A local patch network (LPNet) with global attention is proposed in this paper to detect small targets by jointly considering the global and local properties of infrared small target images.

Semantic Segmentation

Intrinsically Motivated Self-supervised Learning in Reinforcement Learning

no code implementations26 Jun 2021 Yue Zhao, Chenzhuang Du, Hang Zhao, Tiejun Li

In vision-based reinforcement learning (RL) tasks, it is prevalent to assign auxiliary tasks with a surrogate self-supervised loss so as to obtain more semantic representations and improve sample efficiency.

Decision Making reinforcement-learning +2

TSGCNet: Discriminative Geometric Feature Learning With Two-Stream Graph Convolutional Network for 3D Dental Model Segmentation

no code implementations CVPR 2021 Lingming Zhang, Yue Zhao, Deyu Meng, Zhiming Cui, Chenqiang Gao, Xinbo Gao, Chunfeng Lian, Dinggang Shen

State-of-the-art methods directly concatenate the raw attributes of 3D inputs, namely coordinates and normal vectors of mesh cells, to train a single-stream network for fully-automated tooth segmentation.

Graph Learning

GCN-MIF: Graph Convolutional Network with Multi-Information Fusion for Low-dose CT Denoising

2 code implementations15 May 2021 Kecheng Chen, Jiayu Sun, Jiang Shen, Jixiang Luo, Xinyu Zhang, Xuelin Pan, Dongsheng Wu, Yue Zhao, Miguel Bento, Yazhou Ren, Xiaorong Pu

To address this issue, we propose a novel graph convolutional network-based LDCT denoising model, namely GCN-MIF, to explicitly perform multi-information fusion for denoising purpose.

Denoising

Revisiting Skeleton-based Action Recognition

2 code implementations28 Apr 2021 Haodong Duan, Yue Zhao, Kai Chen, Dahua Lin, Bo Dai

In this work, we propose PoseC3D, a new approach to skeleton-based action recognition, which relies on a 3D heatmap stack instead of a graph sequence as the base representation of human skeletons.

Action Recognition Group Activity Recognition +2

A Large-scale Study on Unsupervised Outlier Model Selection: Do Internal Strategies Suffice?

1 code implementation3 Apr 2021 Martin Q. Ma, Yue Zhao, Xiaorong Zhang, Leman Akoglu

These so-called internal strategies solely rely on the input data (without labels) and the output (outlier scores) of the candidate models.

Model Selection Outlier Detection

PointBA: Towards Backdoor Attacks in 3D Point Cloud

no code implementations ICCV 2021 Xinke Li, Zhirui Chen, Yue Zhao, Zekun Tong, Yabang Zhao, Andrew Lim, Joey Tianyi Zhou

We present the backdoor attacks in 3D point cloud with a unified framework that exploits the unique properties of 3D data and networks.

Backdoor Attack Disentanglement

HufuNet: Embedding the Left Piece as Watermark and Keeping the Right Piece for Ownership Verification in Deep Neural Networks

1 code implementation25 Mar 2021 Peizhuo Lv, Pan Li, Shengzhi Zhang, Kai Chen, Ruigang Liang, Yue Zhao, Yingjiu Li

Most existing solutions embed backdoors in DNN model training such that DNN ownership can be verified by triggering distinguishable model behaviors with a set of secret inputs.

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development

2 code implementations18 Feb 2021 Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik

Here, we introduce Therapeutics Data Commons (TDC), the first unifying platform to systematically access and evaluate machine learning across the entire range of therapeutics.

Drug Discovery

Upper Limits on the Isotropic Gravitational-Wave Background from Advanced LIGO's and Advanced Virgo's Third Observing Run

no code implementations28 Jan 2021 The LIGO Scientific Collaboration, The Virgo Collaboration, the KAGRA Collaboration, R. Abbott, T. D. Abbott, S. Abraham, F. Acernese, K. Ackley, A. Adams, C. Adams, R. X. Adhikari, V. B. Adya, C. Affeldt, D. Agarwal, M. Agathos, K. Agatsuma, N. Aggarwal, O. D. Aguiar, L. Aiello, A. Ain, T. Akutsu, K. M. Aleman, G. Allen, A. Allocca, P. A. Altin, A. Amato, S. Anand, A. Ananyeva, S. B. Anderson, W. G. Anderson, M. Ando, S. V. Angelova, S. Ansoldi, J. M. Antelis, S. Antier, S. Appert, Koya Arai, Koji Arai, Y. Arai, S. Araki, A. Araya, M. C. Araya, J. S. Areeda, M. Arène, N. Aritomi, N. Arnaud, S. M. Aronson, H. Asada, Y. Asali, G. Ashton, Y. Aso, S. M. Aston, P. Astone, F. Aubin, P. Aufmuth, K. AultONeal, C. Austin, S. Babak, F. Badaracco, M. K. M. Bader, S. Bae, Y. Bae, A. M. Baer, S. Bagnasco, Y. Bai, L. Baiotti, J. Baird, R. Bajpai, M. Ball, G. Ballardin, S. W. Ballmer, M. Bals, A. Balsamo, G. Baltus, S. Banagiri, D. Bankar, R. S. Bankar, J. C. Barayoga, C. Barbieri, B. C. Barish, D. Barker, P. Barneo, S. Barnum, F. Barone, B. Barr, L. Barsotti, M. Barsuglia, D. Barta, J. Bartlett, M. A. Barton, I. Bartos, R. Bassiri, A. Basti, M. Bawaj, J. C. Bayley, A. C. Baylor, M. Bazzan, B. Bécsy, V. M. Bedakihale, M. Bejger, I. Belahcene, V. Benedetto, D. Beniwal, M. G. Benjamin, T. F. Bennett, J. D. Bentley, M. BenYaala, F. Bergamin, B. K. Berger, S. Bernuzzi, D. Bersanetti, A. Bertolini, J. Betzwieser, R. Bhandare, A. V. Bhandari, D. Bhattacharjee, S. Bhaumik, J. Bidler, I. A. Bilenko, G. Billingsley, R. Birney, O. Birnholtz, S. Biscans, M. Bischi, S. Biscoveanu, A. Bisht, B. Biswas, M. Bitossi, M. -A. Bizouard, J. K. Blackburn, J. Blackman, C. D. Blair, D. G. Blair, R. M. Blair, F. Bobba, N. Bode, M. Boer, G. Bogaert, M. Boldrini, F. Bondu, E. Bonilla, R. Bonnand, P. Booker, B. A. Boom, R. Bork, V. Boschi, N. Bose, S. Bose, V. Bossilkov, V. Boudart, Y. Bouffanais, A. Bozzi, C. Bradaschia, P. R. Brady, A. Bramley, A. Branch, M. Branchesi, J. E. Brau, M. Breschi, T. Briant, J. H. Briggs, A. Brillet, M. Brinkmann, P. Brockill, A. F. Brooks, J. Brooks, D. D. Brown, S. Brunett, G. Bruno, R. Bruntz, J. Bryant, A. Buikema, T. Bulik, H. J. Bulten, A. Buonanno, R. Buscicchio, D. Buskulic, R. L. Byer, L. Cadonati, M. Caesar, G. Cagnoli, C. Cahillane, H. W. Cain III, J. Calderón Bustillo, J. D. Callaghan, T. A. Callister, E. Calloni, J. B. Camp, M. Canepa, M. Cannavacciuolo, K. C. Cannon, H. Cao, J. Cao, Z. Cao, E. Capocasa, E. Capote, G. Carapella, F. Carbognani, J. B. Carlin, M. F. Carney, M. Carpinelli, G. Carullo, T. L. Carver, J. Casanueva Diaz, C. Casentini, G. Castaldi, S. Caudill, M. Cavaglià, F. Cavalier, R. Cavalieri, G. Cella, P. Cerdá-Durán, E. Cesarini, W. Chaibi, K. Chakravarti, B. Champion, C. -H. Chan, C. Chan, C. L. Chan, M. Chan, K. Chandra, P. Chanial, S. Chao, P. Charlton, E. A. Chase, E. Chassande-Mottin, D. Chatterjee, M. Chaturvedi, A. Chen, C. Chen, H. Y. Chen, J. Chen, K. Chen, X. Chen, Y. -B. Chen, Y. -R. Chen, Z. Chen, H. Cheng, C. K. Cheong, H. Y. Cheung, H. Y. Chia, F. Chiadini, C-Y. Chiang, R. Chierici, A. Chincarini, M. L. Chiofalo, A. Chiummo, G. Cho, H. S. Cho, S. Choate, R. K. Choudhary, S. Choudhary, N. Christensen, H. Chu, Q. Chu, Y-K. Chu, S. Chua, K. W. Chung, G. Ciani, P. Ciecielag, M. Cieślar, M. Cifaldi, A. A. Ciobanu, R. Ciolfi, F. Cipriano, A. Cirone, F. Clara, E. N. Clark, J. A. Clark, L. Clarke, P. Clearwater, S. Clesse, F. Cleva, E. Coccia, P. -F. Cohadon, D. E. Cohen, L. Cohen, M. Colleoni, C. G. Collette, M. Colpi, C. M. Compton, M. Constancio Jr., L. Conti, S. J. Cooper, P. Corban, T. R. Corbitt, I. Cordero-Carrión, S. Corezzi, K. R. Corley, N. Cornish, D. Corre, A. Corsi, S. Cortese, C. A. Costa, R. Cotesta, M. W. Coughlin, S. B. Coughlin, J. -P. Coulon, S. T. Countryman, B. Cousins, P. Couvares, P. B. Covas, D. M. Coward, M. J. Cowart, D. C. Coyne, R. Coyne, J. D. E. Creighton, T. D. Creighton, A. W. Criswell, M. Croquette, S. G. Crowder, J. R. Cudell, T. J. Cullen, A. Cumming, R. Cummings, E. Cuoco, M. Curyło, T. Dal Canton, G. Dálya, A. Dana, L. M. DaneshgaranBajastani, B. D'Angelo, S. L. Danilishin, S. D'Antonio, K. Danzmann, C. Darsow-Fromm, A. Dasgupta, L. E. H. Datrier, V. Dattilo, I. Dave, M. Davier, G. S. Davies, D. Davis, E. J. Daw, R. Dean, D. DeBra, M. Deenadayalan, J. Degallaix, M. De Laurentis, S. Deléglise, V. Del Favero, F. De Lillo, N. De Lillo, W. Del Pozzo, L. M. DeMarchi, F. De Matteis, V. D'Emilio, N. Demos, T. Dent, A. Depasse, R. De Pietri, R. De Rosa, C. De Rossi, R. DeSalvo, R. De Simone, S. Dhurandhar, M. C. Díaz, M. Diaz-Ortiz Jr., N. A. Didio, T. Dietrich, L. Di Fiore, C. Di Fronzo, C. Di Giorgio, F. Di Giovanni, T. Di Girolamo, A. Di Lieto, B. Ding, S. Di Pace, I. Di Palma, F. Di Renzo, A. K. Divakarla, A. Dmitriev, Z. Doctor, L. D'Onofrio, F. Donovan, K. L. Dooley, S. Doravari, I. Dorrington, M. Drago, J. C. Driggers, Y. Drori, Z. Du, J. -G. Ducoin, P. Dupej, O. Durante, D. D'Urso, P. -A. Duverne, I. Dvorkin, S. E. Dwyer, P. J. Easter, M. Ebersold, G. Eddolls, B. Edelman, T. B. Edo, O. Edy, A. Effler, S. Eguchi, J. Eichholz, S. S. Eikenberry, M. Eisenmann, R. A. Eisenstein, A. Ejlli, Y. Enomoto, L. Errico, R. C. Essick, H. Estellés, D. Estevez, Z. Etienne, T. Etzel, M. Evans, T. M. Evans, B. E. Ewing, V. Fafone, H. Fair, S. Fairhurst, X. Fan, A. M. Farah, S. Farinon, B. Farr, W. M. Farr, N. W. Farrow, E. J. Fauchon-Jones, M. Favata, M. Fays, M. Fazio, J. Feicht, M. M. Fejer, F. Feng, E. Fenyvesi, D. L. Ferguson, A. Fernandez-Galiana, I. Ferrante, T. A. Ferreira, F. Fidecaro, P. Figura, I. Fiori, M. Fishbach, R. P. Fisher, J. M. Fishner, R. Fittipaldi, V. Fiumara, R. Flaminio, E. Floden, E. Flynn, H. Fong, J. A. Font, B. Fornal, P. W. F. Forsyth, A. Franke, S. Frasca, F. Frasconi, C. Frederick, Z. Frei, A. Freise, R. Frey, P. Fritschel, V. V. Frolov, G. G. Fronzé, Y. Fujii, Y. Fujikawa, M. Fukunaga, M. Fukushima, P. Fulda, M. Fyffe, H. A. Gabbard, B. U. Gadre, S. M. Gaebel, J. R. Gair, J. Gais, S. Galaudage, R. Gamba, D. Ganapathy, A. Ganguly, D. Gao, S. G. Gaonkar, B. Garaventa, C. García-Núñez, C. García-Quirós, F. Garufi, B. Gateley, S. Gaudio, V. Gayathri, G. Ge, G. Gemme, A. Gennai, J. George, L. Gergely, P. Gewecke, S. Ghonge, Abhirup. Ghosh, Archisman Ghosh, Shaon Ghosh, Shrobana Ghosh, Sourath Ghosh, B. Giacomazzo, L. Giacoppo, J. A. Giaime, K. D. Giardina, D. R. Gibson, C. Gier, M. Giesler, P. Giri, F. Gissi, J. Glanzer, A. E. Gleckl, P. Godwin, E. Goetz, R. Goetz, N. Gohlke, B. Goncharov, G. González, A. Gopakumar, M. Gosselin, R. Gouaty, B. Grace, A. Grado, M. Granata, V. Granata, A. Grant, S. Gras, P. Grassia, C. Gray, R. Gray, G. Greco, A. C. Green, R. Green, A. M. Gretarsson, E. M. Gretarsson, D. Griffith, W. Griffiths, H. L. Griggs, G. Grignani, A. Grimaldi, E. Grimes, S. J. Grimm, H. Grote, S. Grunewald, P. Gruning, J. G. Guerrero, G. M. Guidi, A. R. Guimaraes, G. Guixé, H. K. Gulati, H. -K. Guo, Y. Guo, Anchal Gupta, Anuradha Gupta, P. Gupta, E. K. Gustafson, R. Gustafson, F. Guzman, S. Ha, L. Haegel, A. Hagiwara, S. Haino, O. Halim, E. D. Hall, E. Z. Hamilton, G. Hammond, W. -B. Han, M. Haney, J. Hanks, C. Hanna, M. D. Hannam, O. A. Hannuksela, H. Hansen, T. J. Hansen, J. Hanson, T. Harder, T. Hardwick, K. Haris, J. Harms, G. M. Harry, I. W. Harry, D. Hartwig, K. Hasegawa, B. Haskell, R. K. Hasskew, C. -J. Haster, K. Hattori, K. Haughian, H. Hayakawa, K. Hayama, F. J. Hayes, J. Healy, A. Heidmann, M. C. Heintze, J. Heinze, J. Heinzel, H. Heitmann, F. Hellman, P. Hello, A. F. Helmling-Cornell, G. Hemming, M. Hendry, I. S. Heng, E. Hennes, J. Hennig, M. H. Hennig, F. Hernandez Vivanco, M. Heurs, S. Hild, P. Hill, Y. Himemoto, A. S. Hines, Y. Hiranuma, N. Hirata, E. Hirose, S. Hochheim, D. Hofman, J. N. Hohmann, A. M. Holgado, N. A. Holland, I. J. Hollows, Z. J. Holmes, K. Holt, D. E. Holz, Z. Hong, P. Hopkins, J. Hough, E. J. Howell, C. G. Hoy, D. Hoyland, A. Hreibi, B-H. Hsieh, Y. Hsu, G-Z. Huang, H-Y. Huang, P. Huang, Y-C. Huang, Y. -J. Huang, Y. -W. Huang, M. T. Hübner, A. D. Huddart, E. A. Huerta, B. Hughey, D. C. Y. Hui, V. Hui, S. Husa, S. H. Huttner, R. Huxford, T. Huynh-Dinh, S. Ide, B. Idzkowski, A. Iess, B. Ikenoue, S. Imam, K. Inayoshi, H. Inchauspe, C. Ingram, Y. Inoue, G. Intini, K. Ioka, M. Isi, K. Isleif, K. Ito, Y. Itoh, B. R. Iyer, K. Izumi, V. JaberianHamedan, T. Jacqmin, S. J. Jadhav, S. P. Jadhav, A. L. James, A. Z. Jan, K. Jani, K. Janssens, N. N. Janthalur, P. Jaranowski, D. Jariwala, R. Jaume, A. C. Jenkins, C. Jeon, M. Jeunon, W. Jia, J. Jiang, H. -B. Jin, G. R. Johns, A. W. Jones, D. I. Jones, J. D. Jones, P. Jones, R. Jones, R. J. G. Jonker, L. Ju, K. Jung, P. Jung, J. Junker, K. Kaihotsu, T. Kajita, M. Kakizaki, C. V. Kalaghatgi, V. Kalogera, B. Kamai, M. Kamiizumi, N. Kanda, S. Kandhasamy, G. Kang, J. B. Kanner, Y. Kao, S. J. Kapadia, D. P. Kapasi, C. Karathanasis, S. Karki, R. Kashyap, M. Kasprzack, W. Kastaun, S. Katsanevas, E. Katsavounidis, W. Katzman, T. Kaur, K. Kawabe, K. Kawaguchi, N. Kawai, T. Kawasaki, F. Kéfélian, D. Keitel, J. S. Key, S. Khadka, F. Y. Khalili, I. Khan, S. Khan, E. A. Khazanov, N. Khetan, M. Khursheed, N. Kijbunchoo, C. Kim, J. C. Kim, J. Kim, K. Kim, W. S. Kim, Y. -M. Kim, C. Kimball, N. Kimura, P. J. King, M. Kinley-Hanlon, R. Kirchhoff, J. S. Kissel, N. Kita, H. Kitazawa, L. Kleybolte, S. Klimenko, A. M. Knee, T. D. Knowles, E. Knyazev, P. Koch, G. Koekoek, Y. Kojima, K. Kokeyama, S. Koley, P. Kolitsidou, M. Kolstein, K. Komori, V. Kondrashov, A. K. H. Kong, A. Kontos, N. Koper, M. Korobko, K. Kotake, M. Kovalam, D. B. Kozak, C. Kozakai, R. Kozu, V. Kringel, N. V. Krishnendu, A. Królak, G. Kuehn, F. Kuei, A. Kumar, P. Kumar, Rahul Kumar, Rakesh Kumar, J. Kume, K. Kuns, C. Kuo, H-S. Kuo, Y. Kuromiya, S. Kuroyanagi, K. Kusayanagi, K. Kwak, S. Kwang, D. Laghi, E. Lalande, T. L. Lam, A. Lamberts, M. Landry, B. B. Lane, R. N. Lang, J. Lange, B. Lantz, I. La Rosa, A. Lartaux-Vollard, P. D. Lasky, M. Laxen, A. Lazzarini, C. Lazzaro, P. Leaci, S. Leavey, Y. K. Lecoeuche, H. K. Lee, H. M. Lee, H. W. Lee, J. Lee, K. Lee, R. Lee, J. Lehmann, A. Lemaître, E. Leon, M. Leonardi, N. Leroy, N. Letendre, Y. Levin, J. N. Leviton, A. K. Y. Li, B. Li, J. Li, K. L. Li, T. G. F. Li, X. Li, C-Y. Lin, F-K. Lin, F-L. Lin, H. L. Lin, L. C. -C. Lin, F. Linde, S. D. Linker, J. N. Linley, T. B. Littenberg, G. C. Liu, J. Liu, K. Liu, X. Liu, M. Llorens-Monteagudo, R. K. L. Lo, A. Lockwood, M. L. Lollie, L. T. London, A. Longo, D. Lopez, M. Lorenzini, V. Loriette, M. Lormand, G. Losurdo, J. D. Lough, C. O. Lousto, G. Lovelace, H. Lück, D. Lumaca, A. P. Lundgren, L. -W. Luo, R. Macas, M. MacInnis, D. M. Macleod, I. A. O. MacMillan, A. Macquet, I. Magaña Hernandez, F. Magaña-Sandoval, C. Magazzù, R. M. Magee, R. Maggiore, E. Majorana, I. Maksimovic, S. Maliakal, A. Malik, N. Man, V. Mandic, V. Mangano, J. L. Mango, G. L. Mansell, M. Manske, M. Mantovani, M. Mapelli, F. Marchesoni, M. Marchio, F. Marion, Z. Mark, S. Márka, Z. Márka, C. Markakis, A. S. Markosyan, A. Markowitz, E. Maros, A. Marquina, S. Marsat, F. Martelli, I. W. Martin, R. M. Martin, M. Martinez, V. Martinez, K. Martinovic, D. V. Martynov, E. J. Marx, H. Masalehdan, K. Mason, E. Massera, A. Masserot, T. J. Massinger, M. Masso-Reid, S. Mastrogiovanni, A. Matas, M. Mateu-Lucena, F. Matichard, M. Matiushechkina, N. Mavalvala, J. J. McCann, R. McCarthy, D. E. McClelland, P. McClincy, S. McCormick, L. McCuller, G. I. McGhee, S. C. McGuire, C. McIsaac, J. McIver, D. J. McManus, T. McRae, S. T. McWilliams, D. Meacher, M. Mehmet, A. K. Mehta, A. Melatos, D. A. Melchor, G. Mendell, A. Menendez-Vazquez, C. S. Menoni, R. A. Mercer, L. Mereni, K. Merfeld, E. L. Merilh, J. D. Merritt, M. Merzougui, S. Meshkov, C. Messenger, C. Messick, P. M. Meyers, F. Meylahn, A. Mhaske, A. Miani, H. Miao, I. Michaloliakos, C. Michel, Y. Michimura, H. Middleton, L. Milano, A. L. Miller, M. Millhouse, J. C. Mills, E. Milotti, M. C. Milovich-Goff, O. Minazzoli, Y. Minenkov, N. Mio, Ll. M. Mir, A. Mishkin, C. Mishra, T. Mishra, T. Mistry, S. Mitra, V. P. Mitrofanov, G. Mitselmakher, R. Mittleman, O. Miyakawa, A. Miyamoto, Y. Miyazaki, K. Miyo, S. Miyoki, Geoffrey Mo, K. Mogushi, S. R. P. Mohapatra, S. R. Mohite, I. Molina, M. Molina-Ruiz, M. Mondin, M. Montani, C. J. Moore, D. Moraru, F. Morawski, A. More, C. Moreno, G. Moreno, Y. Mori, S. Morisaki, Y. Moriwaki, B. Mours, C. M. Mow-Lowry, S. Mozzon, F. Muciaccia, Arunava Mukherjee, D. Mukherjee, Soma Mukherjee, Subroto Mukherjee, N. Mukund, A. Mullavey, J. Munch, E. A. Muñiz, P. G. Murray, R. Musenich, S. L. Nadji, K. Nagano, S. Nagano, A. Nagar, K. Nakamura, H. Nakano, M. Nakano, R. Nakashima, Y. Nakayama, I. Nardecchia, T. Narikawa, L. Naticchioni, B. Nayak, R. K. Nayak, R. Negishi, B. F. Neil, J. Neilson, G. Nelemans, T. J. N. Nelson, M. Nery, A. Neunzert, K. Y. Ng, S. W. S. Ng, C. Nguyen, P. Nguyen, T. Nguyen, L. Nguyen Quynh, W. -T. Ni, S. A. Nichols, A. Nishizawa, S. Nissanke, F. Nocera, M. Noh, M. Norman, C. North, S. Nozaki, L. K. Nuttall, J. Oberling, B. D. O'Brien, Y. Obuchi, J. O'Dell, W. Ogaki, G. Oganesyan, J. J. Oh, K. Oh, S. H. Oh, M. Ohashi, N. Ohishi, M. Ohkawa, F. Ohme, H. Ohta, M. A. Okada, Y. Okutani, K. Okutomi, C. Olivetto, K. Oohara, C. Ooi, R. Oram, B. O'Reilly, R. G. Ormiston, N. D. Ormsby, L. F. Ortega, R. O'Shaughnessy, E. O'Shea, S. Oshino, S. Ossokine, C. Osthelder, S. Otabe, D. J. Ottaway, H. Overmier, A. E. Pace, G. Pagano, M. A. Page, G. Pagliaroli, A. Pai, S. A. Pai, J. R. Palamos, O. Palashov, C. Palomba, K. Pan, P. K. Panda, H. Pang, P. T. H. Pang, C. Pankow, F. Pannarale, B. C. Pant, F. Paoletti, A. Paoli, A. Paolone, A. Parisi, J. Park, W. Parker, D. Pascucci, A. Pasqualetti, R. Passaquieti, D. Passuello, M. Patel, B. Patricelli, E. Payne, T. C. Pechsiri, M. Pedraza, M. Pegoraro, A. Pele, F. E. Peña Arellano, S. Penn, A. Perego, A. Pereira, T. Pereira, C. J. Perez, C. Périgois, A. Perreca, S. Perriès, J. Petermann, D. Petterson, H. P. Pfeiffer, K. A. Pham, K. S. Phukon, O. J. Piccinni, M. Pichot, M. Piendibene, F. Piergiovanni, L. Pierini, V. Pierro, G. Pillant, F. Pilo, L. Pinard, I. M. Pinto, B. J. Piotrzkowski, K. Piotrzkowski, M. Pirello, M. Pitkin, E. Placidi, W. Plastino, C. Pluchar, R. Poggiani, E. Polini, D. Y. T. Pong, S. Ponrathnam, P. Popolizio, E. K. Porter, J. Powell, M. Pracchia, T. Pradier, A. K. Prajapati, K. Prasai, R. Prasanna, G. Pratten, T. Prestegard, M. Principe, G. A. Prodi, L. Prokhorov, P. Prosposito, L. Prudenzi, A. Puecher, M. Punturo, F. Puosi, P. Puppo, M. Pürrer, H. Qi, V. Quetschke, P. J. Quinonez, R. Quitzow-James, F. J. Raab, G. Raaijmakers, H. Radkins, N. Radulesco, P. Raffai, S. X. Rail, S. Raja, C. Rajan, K. E. Ramirez, T. D. Ramirez, A. Ramos-Buades, J. Rana, P. Rapagnani, U. D. Rapol, B. Ratto, V. Raymond, N. Raza, M. Razzano, J. Read, L. A. Rees, T. Regimbau, L. Rei, S. Reid, D. H. Reitze, P. Relton, P. Rettegno, F. Ricci, C. J. Richardson, J. W. Richardson, L. Richardson, P. M. Ricker, G. Riemenschneider, K. Riles, M. Rizzo, N. A. Robertson, R. Robie, F. Robinet, A. Rocchi, J. A. Rocha, S. Rodriguez, R. D. Rodriguez-Soto, L. Rolland, J. G. Rollins, V. J. Roma, M. Romanelli, J. D. Romano, R. Romano, C. L. Romel, A. Romero, I. M. Romero-Shaw, J. H. Romie, C. A. Rose, D. Rosińska, S. G. Rosofsky, M. P. Ross, S. Rowan, S. J. Rowlinson, Santosh Roy, Soumen Roy, D. Rozza, P. Ruggi, K. Ryan, S. Sachdev, T. Sadecki, J. Sadiq, N. Sago, S. Saito, Y. Saito, K. Sakai, Y. Sakai, M. Sakellariadou, Y. Sakuno, O. S. Salafia, L. Salconi, M. Saleem, F. Salemi, A. Samajdar, E. J. Sanchez, J. H. Sanchez, L. E. Sanchez, N. Sanchis-Gual, J. R. Sanders, A. Sanuy, T. R. Saravanan, N. Sarin, B. Sassolas, H. Satari, S. Sato, T. Sato, O. Sauter, R. L. Savage, V. Savant, T. Sawada, D. Sawant, H. L. Sawant, S. Sayah, D. Schaetzl, M. Scheel, J. Scheuer, A. Schindler-Tyka, P. Schmidt, R. Schnabel, M. Schneewind, R. M. S. Schofield, A. Schönbeck, B. W. Schulte, B. F. Schutz, E. Schwartz, J. Scott, S. M. Scott, M. Seglar-Arroyo, E. Seidel, T. Sekiguchi, Y. Sekiguchi, D. Sellers, A. Sergeev, A. S. Sengupta, N. Sennett, D. Sentenac, E. G. Seo, V. Sequino, Y. Setyawati, T. Shaffer, M. S. Shahriar, B. Shams, L. Shao, S. Sharifi, A. Sharma, P. Sharma, P. Shawhan, N. S. Shcheblanov, H. Shen, S. Shibagaki, M. Shikauchi, R. Shimizu, T. Shimoda, K. Shimode, R. Shink, H. Shinkai, T. Shishido, A. Shoda, D. H. Shoemaker, D. M. Shoemaker, K. Shukla, S. ShyamSundar, M. Sieniawska, D. Sigg, L. P. Singer, D. Singh, N. Singh, A. Singha, A. M. Sintes, V. Sipala, V. Skliris, B. J. J. Slagmolen, T. J. Slaven-Blair, J. Smetana, J. R. Smith, R. J. E. Smith, S. N. Somala, K. Somiya, E. J. Son, K. Soni, S. Soni, B. Sorazu, V. Sordini, F. Sorrentino, N. Sorrentino, H. Sotani, R. Soulard, T. Souradeep, E. Sowell, V. Spagnuolo, A. P. Spencer, M. Spera, A. K. Srivastava, V. Srivastava, K. Staats, C. Stachie, D. A. Steer, J. Steinlechner, S. Steinlechner, D. J. Stops, M. Stover, K. A. Strain, L. C. Strang, G. Stratta, A. Strunk, R. Sturani, A. L. Stuver, J. Südbeck, S. Sudhagar, V. Sudhir, R. Sugimoto, H. G. Suh, T. Z. Summerscales, H. Sun, L. Sun, S. Sunil, A. Sur, J. Suresh, P. J. Sutton, Takamasa Suzuki, Toshikazu Suzuki, B. L. Swinkels, M. J. Szczepańczyk, P. Szewczyk, M. Tacca, H. Tagoshi, S. C. Tait, H. Takahashi, R. Takahashi, A. Takamori, S. Takano, H. Takeda, M. Takeda, C. Talbot, H. Tanaka, Kazuyuki Tanaka, Kenta Tanaka, Taiki Tanaka, Takahiro Tanaka, A. J. Tanasijczuk, S. Tanioka, D. B. Tanner, D. Tao, A. Tapia, E. N. Tapia San Martin, J. D. Tasson, S. Telada, R. Tenorio, L. Terkowski, M. Test, M. P. Thirugnanasambandam, M. Thomas, P. Thomas, J. E. Thompson, S. R. Thondapu, K. A. Thorne, E. Thrane, Shubhanshu Tiwari, Srishti Tiwari, V. Tiwari, K. Toland, A. E. Tolley, T. Tomaru, Y. Tomigami, T. Tomura, M. Tonelli, A. Torres-Forné, C. I. Torrie, I. Tosta e Melo, D. Töyrä, A. Trapananti, F. Travasso, G. Traylor, M. C. Tringali, A. Tripathee, L. Troiano, A. Trovato, L. Trozzo, R. J. Trudeau, D. S. Tsai, D. Tsai, K. W. Tsang, T. Tsang, J-S. Tsao, M. Tse, R. Tso, K. Tsubono, S. Tsuchida, L. Tsukada, D. Tsuna, T. Tsutsui, T. Tsuzuki, M. Turconi, D. Tuyenbayev, A. S. Ubhi, N. Uchikata, T. Uchiyama, R. P. Udall, A. Ueda, T. Uehara, K. Ueno, G. Ueshima, D. Ugolini, C. S. Unnikrishnan, F. Uraguchi, A. L. Urban, T. Ushiba, S. A. Usman, A. C. Utina, H. Vahlbruch, G. Vajente, A. Vajpeyi, G. Valdes, M. Valentini, V. Valsan, N. van Bakel, M. van Beuzekom, J. F. J. van den Brand, C. Van Den Broeck, N. Van Remortel, D. C. Vander-Hyde, L. van der Schaaf, J. V. van Heijningen, M. H. P. M. van Putten, M. Vardaro, A. F. Vargas, V. Varma, M. Vasúth, A. Vecchio, G. Vedovato, J. Veitch, P. J. Veitch, K. Venkateswara, J. Venneberg, G. Venugopalan, D. Verkindt, Y. Verma, D. Veske, F. Vetrano, A. Viceré, A. D. Viets, V. Villa-Ortega, J. -Y. Vinet, S. Vitale, T. Vo, H. Vocca, E. R. G. von Reis, J. von Wrangel, C. Vorvick, S. P. Vyatchanin, L. E. Wade, M. Wade, K. J. Wagner, R. C. Walet, M. Walker, G. S. Wallace, L. Wallace, S. Walsh, J. Wang, J. Z. Wang, W. H. Wang, R. L. Ward, J. Warner, M. Was, T. Washimi, N. Y. Washington, J. Watchi, B. Weaver, L. Wei, M. Weinert, A. J. Weinstein, R. Weiss, C. M. Weller, F. Wellmann, L. Wen, P. Weßels, J. W. Westhouse, K. Wette, J. T. Whelan, D. D. White, B. F. Whiting, C. Whittle, D. Wilken, D. Williams, M. J. Williams, A. R. Williamson, J. L. Willis, B. Willke, D. J. Wilson, W. Winkler, C. C. Wipf, T. Wlodarczyk, G. Woan, J. Woehler, J. K. Wofford, I. C. F. Wong, C. Wu, D. S. Wu, H. Wu, S. Wu, D. M. Wysocki, L. Xiao, W-R. Xu, T. Yamada, H. Yamamoto, Kazuhiro Yamamoto, Kohei Yamamoto, T. Yamamoto, K. Yamashita, R. Yamazaki, F. W. Yang, L. Yang, Yang Yang, Yi Yang, Z. Yang, M. J. Yap, D. W. Yeeles, A. B. Yelikar, M. Ying, K. Yokogawa, J. Yokoyama, T. Yokozawa, A. Yoon, T. Yoshioka, Hang Yu, Haocun Yu, H. Yuzurihara, A. Zadrożny, M. Zanolin, S. Zeidler, T. Zelenova, J. -P. Zendri, M. Zevin, M. Zhan, H. Zhang, J. Zhang, L. Zhang, R. Zhang, T. Zhang, C. Zhao, G. Zhao, Yue Zhao, Yuhang Zhao, Z. Zhou, X. J. Zhu, Z. -H. Zhu, M. E. Zucker, J. Zweizig

Unlike in previous observing runs in the advanced detector era, we include Virgo in the search for the GWB.

General Relativity and Quantum Cosmology Cosmology and Nongalactic Astrophysics

Inorganic component imaging of aggregate glue droplets on spider orb webs by TOF-SIMS

no code implementations27 Jan 2021 Yue Zhao, Masato Morita, Tetsuo Sakamoto

A uniform element distribution is seen for suspended pristine aggregate glue droplets, and a differential spreading of aggregate glue components is seen for attached aggregate glue droplets.

Atomic and Molecular Clusters Applied Physics Instrumentation and Detectors

PyHealth: A Python Library for Health Predictive Models

2 code implementations11 Jan 2021 Yue Zhao, Zhi Qiao, Cao Xiao, Lucas Glass, Jimeng Sun

PyHealth consists of data preprocessing module, predictive modeling module, and evaluation module.

Cross-Attention Guided Network for Visual Tracking

no code implementations1 Jan 2021 Yue Zhao, Zhibin Yu

Here, the channel attention of target template is introduced to guide the feature learning for search branch, and then the self-spatial attention is used to localize the informative part location after the correlation processing.

Visual Tracking

TSGCNet: Discriminative Geometric Feature Learning with Two-Stream GraphConvolutional Network for 3D Dental Model Segmentation

no code implementations26 Dec 2020 Lingming Zhang, Yue Zhao, Deyu Meng, Zhiming Cui, Chenqiang Gao, Xinbo Gao, Chunfeng Lian, Dinggang Shen

State-of-the-art methods directly concatenate the raw attributes of 3D inputs, namely coordinates and normal vectors of mesh cells, to train a single-stream network for fully-automated tooth segmentation.

Graph Learning

AutoAudit: Mining Accounting and Time-Evolving Graphs

1 code implementation1 Nov 2020 Meng-Chieh Lee, Yue Zhao, Aluna Wang, Pierre Jinghong Liang, Leman Akoglu, Vincent S. Tseng, Christos Faloutsos

How can we spot money laundering in large-scale graph-like accounting datasets?

Social and Information Networks

A random batch Ewald method for particle systems with Coulomb interactions

no code implementations4 Oct 2020 Shi Jin, Lei LI, Zhenli Xu, Yue Zhao

We develop a random batch Ewald (RBE) method for molecular dynamics simulations of particle systems with long-range Coulomb interactions, which achieves an $O(N)$ complexity in each step of simulating the $N$-body systems.

Computational Physics 65C35, 82M37, 65T50

Automating Outlier Detection via Meta-Learning

1 code implementation22 Sep 2020 Yue Zhao, Ryan A. Rossi, Leman Akoglu

Given an unsupervised outlier detection (OD) task on a new dataset, how can we automatically select a good outlier detection method and its hyperparameter(s) (collectively called a model)?

Anomaly Detection AutoML +3

SYNC: A Copula based Framework for Generating Synthetic Data from Aggregated Sources

1 code implementation20 Sep 2020 Zheng Li, Yue Zhao, Jialin Fu

A synthetic dataset is a data object that is generated programmatically, and it may be valuable to creating a single dataset from multiple sources when direct collection is difficult or costly.

Feature Engineering Synthetic Data Generation

COPOD: Copula-Based Outlier Detection

1 code implementation20 Sep 2020 Zheng Li, Yue Zhao, Nicola Botta, Cezar Ionescu, Xiyang Hu

In this work, we make three key contributions, 1) propose a novel, parameter-free outlier detection algorithm with both great performance and interpretability, 2) perform extensive experiments on 30 benchmark datasets to show that COPOD outperforms in most cases and is also one of the fastest algorithms, and 3) release an easy-to-use Python implementation for reproducibility.

Outlier Detection

Intra- and Inter-Action Understanding via Temporal Action Parsing

no code implementations CVPR 2020 Dian Shao, Yue Zhao, Bo Dai, Dahua Lin

Current methods for action recognition primarily rely on deep convolutional networks to derive feature embeddings of visual and motion features.

Action Parsing Action Recognition +1

Omni-sourced Webly-supervised Learning for Video Recognition

3 code implementations ECCV 2020 Haodong Duan, Yue Zhao, Yuanjun Xiong, Wentao Liu, Dahua Lin

Then a joint-training strategy is proposed to deal with the domain gaps between multiple data sources and formats in webly-supervised learning.

Ranked #3 on Action Recognition on UCF101 (using extra training data)

Action Classification Action Recognition +1

A random-batch Monte Carlo method for many-body systems with singular kernels

no code implementations14 Mar 2020 Lei Li, Zhenli Xu, Yue Zhao

The cost of the rejection step is $O(1)$ since the interaction used is of short range.

Computational Physics Numerical Analysis Numerical Analysis 82B80, 60H35, 65C05

SUOD: Accelerating Large-Scale Unsupervised Heterogeneous Outlier Detection

1 code implementation11 Mar 2020 Yue Zhao, Xiyang Hu, Cheng Cheng, Cong Wang, Changlin Wan, Wen Wang, Jianing Yang, Haoping Bai, Zheng Li, Cao Xiao, Yunlong Wang, Zhi Qiao, Jimeng Sun, Leman Akoglu

Outlier detection (OD) is a key machine learning (ML) task for identifying abnormal objects from general samples with numerous high-stake applications including fraud detection and intrusion detection.

Dimensionality Reduction Fraud Detection +2

On Isometry Robustness of Deep 3D Point Cloud Models under Adversarial Attacks

1 code implementation CVPR 2020 Yue Zhao, Yuwei Wu, Caihua Chen, Andrew Lim

Armed with the Thompson Sampling, we develop a black-box attack with success rate over 95% on ModelNet40 data set.

SUOD: Toward Scalable Unsupervised Outlier Detection

1 code implementation8 Feb 2020 Yue Zhao, Xueying Ding, Jianing Yang, Haoping Bai

In this study, we propose a three-module acceleration framework called SUOD to expedite the training and prediction with a large number of unsupervised detection models.

Knowledge Distillation Outlier Detection

Extracting clinical concepts from user queries

no code implementations12 Dec 2019 Yue Zhao, John Handley

Often trained on annotated clinical notes, clinical NER models tend to struggle with tagging clinical entities in user queries because of the structural differences between clinical notes and user queries.

Clinical Concept Extraction Named Entity Recognition +1

XGBOD: Improving Supervised Outlier Detection with Unsupervised Representation Learning

1 code implementation1 Dec 2019 Yue Zhao, Maciej K. Hryniewicki

A new semi-supervised ensemble algorithm called XGBOD (Extreme Gradient Boosting Outlier Detection) is proposed, described and demonstrated for the enhanced detection of outliers from normal observations in various practical datasets.

Outlier Detection Representation Learning

DCSO: Dynamic Combination of Detector Scores for Outlier Ensembles

1 code implementation23 Nov 2019 Yue Zhao, Maciej K. Hryniewicki

Selecting and combining the outlier scores of different base detectors used within outlier ensembles can be quite challenging in the absence of ground truth.

outlier ensembles

RNN-Test: Towards Adversarial Testing for Recurrent Neural Network Systems

no code implementations11 Nov 2019 Jianmin Guo, Yue Zhao, Quan Zhang, Yu Jiang

Compared with the neuron coverage, the proposed state coverage metrics as guidance excel with 4. 17% to 97. 22% higher success (or generation) rate.

Language Modelling

ADA+: A GENERIC FRAMEWORK WITH MORE ADAPTIVE EXPLICIT ADJUSTMENT FOR LEARNING RATE

no code implementations25 Sep 2019 Yue Zhao, Xiangsheng Huang, Ludan Kou

Although adaptive algorithms have achieved significant success in training deep neural networks with faster training speed, they tend to have poor generalization performance compared to SGD with Momentum(SGDM).

Combining Machine Learning Models using combo Library

1 code implementation21 Sep 2019 Yue Zhao, Xuejian Wang, Cheng Cheng, Xueying Ding

Model combination, often regarded as a key sub-field of ensemble learning, has been widely used in both academic research and industry applications.

Anomaly Detection Ensemble Learning

Learning to Recover Sparse Signals

no code implementations NeurIPS Workshop Deep_Invers 2019 Sichen Zhong, Yue Zhao, Jianshu Chen

In compressed sensing, a primary problem to solve is to reconstruct a high dimensional sparse signal from a small number of observations.

reinforcement-learning

SynC: A Unified Framework for Generating Synthetic Population with Gaussian Copula

2 code implementations16 Apr 2019 Colin Wan, Zheng Li, Alicia Guo, Yue Zhao

Synthetic population generation is the process of combining multiple socioeconomic and demographic datasets from different sources and/or granularity levels, and downscaling them to an individual level.

Feature Engineering

Music Artist Classification with Convolutional Recurrent Neural Networks

4 code implementations14 Jan 2019 Zain Nasrullah, Yue Zhao

To this end, an established classification architecture, a Convolutional Recurrent Neural Network (CRNN), is applied to the artist20 music artist identification dataset under a comprehensive set of conditions.

Artist classification Classification +4

PyOD: A Python Toolbox for Scalable Outlier Detection

4 code implementations6 Jan 2019 Yue Zhao, Zain Nasrullah, Zheng Li

PyOD is an open-source Python toolbox for performing scalable outlier detection on multivariate data.

Anomaly Detection outlier ensembles

Seeing isn't Believing: Practical Adversarial Attack Against Object Detectors

no code implementations26 Dec 2018 Yue Zhao, Hong Zhu, Ruigang Liang, Qintao Shen, Shengzhi Zhang, Kai Chen

In this paper, we presented systematic solutions to build robust and practical AEs against real world object detectors.

Adversarial Attack Autonomous Driving

LSCP: Locally Selective Combination in Parallel Outlier Ensembles

1 code implementation4 Dec 2018 Yue Zhao, Zain Nasrullah, Maciej K. Hryniewicki, Zheng Li

The top-performing base detectors in this local region are selected and combined as the model's final output.

Anomaly Detection outlier ensembles

Find and Focus: Retrieve and Localize Video Events with Natural Language Queries

no code implementations ECCV 2018 Dian Shao, Yu Xiong, Yue Zhao, Qingqiu Huang, Yu Qiao, Dahua Lin

The thriving of video sharing services brings new challenges to video retrieval, e. g. the rapid growth in video duration and content diversity.

Video Retrieval

DLFuzz: Differential Fuzzing Testing of Deep Learning Systems

1 code implementation28 Aug 2018 Jianmin Guo, Yu Jiang, Yue Zhao, Quan Chen, Jiaguang Sun

Deep learning (DL) systems are increasingly applied to safety-critical domains such as autonomous driving cars.

Software Engineering

Federated Learning with Non-IID Data

1 code implementation2 Jun 2018 Yue Zhao, Meng Li, Liangzhen Lai, Naveen Suda, Damon Civin, Vikas Chandra

Experiments show that accuracy can be increased by 30% for the CIFAR-10 dataset with only 5% globally shared data.

Federated Learning

Recognize Actions by Disentangling Components of Dynamics

no code implementations CVPR 2018 Yue Zhao, Yuanjun Xiong, Dahua Lin

Despite the remarkable progress in action recognition over the past several years, existing methods remain limited in efficiency and effectiveness.

Action Recognition Frame +2

CommanderSong: A Systematic Approach for Practical Adversarial Voice Recognition

no code implementations24 Jan 2018 Xuejing Yuan, Yuxuan Chen, Yue Zhao, Yunhui Long, Xiaokang Liu, Kai Chen, Shengzhi Zhang, Heqing Huang, Xiao-Feng Wang, Carl A. Gunter

For this purpose, we developed novel techniques that address a key technical challenge: integrating the commands into a song in a way that can be effectively recognized by ASR through the air, in the presence of background noise, while not being detected by a human listener.

Automatic Speech Recognition

A Learning-to-Infer Method for Real-Time Power Grid Multi-Line Outage Identification

no code implementations21 Oct 2017 Yue Zhao, Jianshu Chen, H. Vincent Poor

Identifying a potentially large number of simultaneous line outages in power transmission networks in real time is a computationally hard problem.

Adaptive estimation of the copula correlation matrix for semiparametric elliptical copulas

no code implementations28 May 2013 Marten Wegkamp, Yue Zhao

Then we study a factor model of $\Sigma$, for which we propose a refined estimator $\widetilde{\Sigma}$ by fitting a low-rank matrix plus a diagonal matrix to $\hat{\Sigma}$ using least squares with a nuclear norm penalty on the low-rank matrix.

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