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Yash Garg
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2020 – today
- 2024
- [j5]Aman Mishra, Yash Garg, Om Jee Pandey, Mahendra Kumar Shukla, Athanasios V. Vasilakos, Rajesh M. Hegde:
A Novel Resource Management Framework for Blockchain-Based Federated Learning in IoT Networks. IEEE Trans. Sustain. Comput. 9(4): 648-660 (2024) - [i4]Arindam Dutta, Rohit Lal, Yash Garg, Calvin-Khang Ta, Dripta S. Raychaudhuri, Hannah Dela Cruz, Amit K. Roy-Chowdhury:
POSTURE: Pose Guided Unsupervised Domain Adaptation for Human Body Part Segmentation. CoRR abs/2407.03549 (2024) - 2023
- [i3]Haoxiang Zhang, Juliana Freire, Yash Garg:
eTOP: Early Termination of Pipelines for Faster Training of AutoML Systems. CoRR abs/2304.08597 (2023) - [i2]Yash Garg, Nebiyou Yismaw, Rakib Hyder, Ashley Prater-Bennette, M. Salman Asif:
Factorized Tensor Networks for Multi-Task and Multi-Domain Learning. CoRR abs/2310.06124 (2023) - [i1]Rohit Lal, Yash Garg, Arindam Dutta, Calvin-Khang Ta, Dripta S. Raychaudhuri, M. Salman Asif, Amit K. Roy-Chowdhury:
TEMP3D: Temporally Continuous 3D Human Pose Estimation Under Occlusions. CoRR abs/2312.16221 (2023) - 2022
- [j4]Shruti Patil, Varadarajan Vijayakumar, Supriya V. Mahadevkar, Rohan Athawade, Lakhan Maheshwari, Shrushti Kumbhare, Yash Garg, Deepak S. Dharrao, Pooja Kamat, Ketan Kotecha:
Enhancing Optical Character Recognition on Images with Mixed Text Using Semantic Segmentation. J. Sens. Actuator Networks 11(4): 63 (2022) - [c10]Md Abdur Rahaman, Yash Garg, Armin Iraji, Zening Fu, Jiayu Chen, Vince D. Calhoun:
Two-Dimensional Attentive Fusion for Multi-Modal Learning of Neuroimaging and Genomics Data. MLSP 2022: 1-6 - 2021
- [j3]Manoj Tiwaskar, Yash Garg, Xinsheng Li, K. Selçuk Candan, Maria Luisa Sapino:
Selego: robust variate selection for accurate time series forecasting. Data Min. Knowl. Discov. 35(5): 2141-2167 (2021) - [j2]Hans Walter Behrens, K. Selçuk Candan, Xilun Chen, Yash Garg, Mao-Lin Li, Xinsheng Li, Sicong Liu, Maria Luisa Sapino, Md Shadab, Dalton Turner, Magesh Vijayakumaren:
DataStorm: Coupled, Continuous Simulations for Complex Urban Environments. Trans. Data Sci. 2(3): 19:1-19:37 (2021) - [c9]Yash Garg:
ReTriM: Reconstructive Triplet Loss for Learning Reduced Embeddings for Multi-Variate Time Series. ICDM (Workshops) 2021: 460-465 - [c8]Yash Garg, K. Selçuk Candan:
XM2A: Multi-Scale Multi-Head Attention with Cross-Talk for Multi-Variate Time Series Analysis. MIPR 2021: 151-157 - 2020
- [b1]Yash Garg:
On Feature Saliency and Deep Neural Networks. Arizona State University, Tempe, USA, 2020 - [c7]Yash Garg, K. Selçuk Candan, Maria Luisa Sapino:
SAN : Scale-Space Attention Networks. ICDE 2020: 853-864 - [c6]Yash Garg, K. Selçuk Candan:
SDMA: Saliency-Driven Mutual Cross Attention for Multi-Variate Time Series. ICPR 2020: 7242-7249 - [c5]Yash Garg, K. Selçuk Candan:
iSparse: Output Informed Sparsification of Neural Network. ICMR 2020: 180-188
2010 – 2019
- 2019
- [c4]Yash Garg, K. Selçuk Candan:
RACKNet: Robust Allocation of Convolutional Kernels in Neural Networks for Image Classification. ICMR 2019: 315-323 - 2018
- [j1]Hans Behrens, K. Selçuk Candan, Xilun Chen, Ashish Gadkari, Yash Garg, Mao-Lin Li:
DataStorm-FE: A Data- and Decision-Flow and Coordination Engine for Coupled Simulation Ensembles. Proc. VLDB Endow. 11(12): 1906-1909 (2018) - 2017
- [c3]Silvestro Roberto Poccia, Maria Luisa Sapino, Sicong Liu, Xilun Chen, Yash Garg, Shengyu Huang, Jung Hyun Kim, Xinsheng Li, Parth Nagarkar, K. Selçuk Candan:
SIMDMS: Data Management and Analysis to Support Decision Making through Large Simulation Ensembles. EDBT 2017: 582-585 - [c2]Yash Garg, Silvestro Roberto Poccia:
On the Effectiveness of Distance Measures for Similarity Search in Multi-Variate Sensory Data: Effectiveness of Distance Measures for Similarity Search. ICMR 2017: 489-493 - 2015
- [c1]Sicong Liu, Yash Garg, K. Selçuk Candan, Maria Luisa Sapino, Gerardo Chowell-Puente:
NOTES2: Networks-of-Traces for Epidemic Spread Simulations. AAAI Workshop: Computational Sustainability 2015
Coauthor Index
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last updated on 2024-09-10 02:11 CEST by the dblp team
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