Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Alykhan Tejani"'
Autor:
Bruce Ferwerda, Luca Belli, Ben Chamberlain, Alexandre Lung-Yut-Fong, Yuanpu Xie, Wenzhe Shi, Saikishore Kalloori, Frank Portman, Michael M. Bronstein, Alykhan Tejani, Jonathan Hunt, Vito Walter Anelli
Publikováno v:
RecSys
The workshop features presentations of accepted contributions to the RecSys Challenge 2021, organized by Politecnico di Bari, ETH Zurich, Jonkoping University, and the data set is provided by Twitter. The challenge focuses on a real-world task of twe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::92545fe85fbd196cc5c79f293b786618
https://doi.org/10.1145/3460231.3478515
https://doi.org/10.1145/3460231.3478515
Autor:
Kristian Lum, Frank Portman, Saikishore Kalloori, Wenzhe Shi, Michael M. Bronstein, Alykhan Tejani, Vito Walter Anelli, Jonathan Hunt, Luca Belli, Yuanpu Xie, Alexandre Lung-Yut-Fong, Bruce Ferwerda, Ben Chamberlain
After the success the RecSys 2020 Challenge, we are describing a novel and bigger dataset that was released in conjunction with the ACM RecSys Challenge 2021. This year's dataset is not only bigger (~ 1B data points, a 5 fold increase), but for the f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c735528f4e22d8efd67a74bb588aca8f
Autor:
Jessie Smith, Wenzhe Shi, Xiao Zhu, Sofia Ira Ktena, Akshay Gupta, Frank Portman, Nazareno Andrade, Luca Belli, Michael M. Bronstein, Vito Walter Anelli, Yuanpu Xie, Alexandre Lung-Yut-Fong, Amra Delic, Gabriele Sottocornola, Alykhan Tejani
Publikováno v:
RecSys
The workshop features presentations of accepted contributions to the RecSys Challenge 2020, organized by Politecnico di Bari, Free University of Bozen-Bolzano, TU Wien, University of Colorado, Boulder, and Universidade Federal de Campina Grande, and
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::baf729f4e0f6adfe1d4cf33d57f42cbc
https://doi.org/10.1145/3383313.3411532
https://doi.org/10.1145/3383313.3411532
Autor:
Ferenc Huszar, Sofia Ira Ktena, Akshay Gupta, Alykhan Tejani, Pranay Kumar Myana, Yuanpu Xie, Suvadip Paul, Prasang Upadhyaya, Wenzhe Shi, Caojin Zhang, Deepak Dilipkumar, Yicun Liu, Ikuhiro Ihara
Publikováno v:
RecSys
Deep Neural Networks (DNNs) with sparse input features have been widely used in recommender systems in industry. These models have large memory requirements and need a huge amount of training data. The large model size usually entails a cost, in the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::857ea526014f8f0bce5717caa13120c3
Publikováno v:
IEEE Transactions on Pattern Analysis and Machine Intelligence. 39:1374-1387
In this paper we present the latent regression forest (LRF), a novel framework for real-time, 3D hand pose estimation from a single depth image. Prior discriminative methods often fall into two categories: holistic and patch-based. Holistic methods a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::288b597ed44cd0d13f76261aac4f2a04
https://doi.org/10.1109/tpami.2016.2599170
https://doi.org/10.1109/tpami.2016.2599170
Autor:
Wenzhe Shi, Pranay Kumar Myana, Lucas Theis, Ferenc Huszar, Deepak Dilipkumar, Sofia Ira Ktena, Steven Yoo, Alykhan Tejani
Publikováno v:
RecSys
One of the challenges in display advertising is that the distribution of features and click through rate (CTR) can exhibit large shifts over time due to seasonality, changes to ad campaigns and other factors. The predominant strategy to keep up with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ee39e89b70ec1d3dfa166b4ba4c94068
https://doi.org/10.1145/3298689.3347002
https://doi.org/10.1145/3298689.3347002
Autor:
Johannes Totz, Zehan Wang, Ferenc Huszar, Alejandro Acosta, Christian Ledig, Andrew Peter Aitken, Lucas Theis, Wenzhe Shi, Andrew Cunningham, Jose Caballero, Alykhan Tejani
Publikováno v:
CVPR
Despite the breakthroughs in accuracy and speed of single image super-resolution using faster and deeper convolutional neural networks, one central problem remains largely unsolved: how do we recover the finer texture details when we super-resolve at
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2e8a9c645e1a6302df46826adc03e245
http://arxiv.org/abs/1609.04802
http://arxiv.org/abs/1609.04802
Publikováno v:
Computer Vision – ECCV 2014 ISBN: 9783319105987
ECCV (6)
ECCV (6)
In this paper we propose a novel framework, Latent-Class Hough Forests, for 3D object detection and pose estimation in heavily cluttered and occluded scenes. Firstly, we adapt the state-of-the-art template matching feature, LINEMOD [14], into a scale
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::42ac30e0983499d1de076e14eb29655e
https://doi.org/10.1007/978-3-319-10599-4_30
https://doi.org/10.1007/978-3-319-10599-4_30