My main research interest lies at the intersection of machine learning and deep learning for multi-variate time series analytics. My focus is on developing novel algorithms that extracts insights from the data using machine learning techniques which [insights] are then used to train highly-accurate deep learning models.

Publications

 Scholar |  First Author |  Co-Author |  Equal Contribution |  ACM Grant | Reverse Chronological Order
[C] Conference [D] Demo [J] Journal [T] Thesis and [W] Workshop

[17-C] Haoxiang Zhang, Juliana Freire, Yash Garg, “eTOP: Early Termination of Pipelines for Faster Training of AutoML Systems”, arXiv:2304.08597 2023.
[16-C] M. Abdur Rahaman, Yash Garg, Armin Iraj, Zening Fu, Jiayu Chen, Vince Calhoun, “Two-Dimensional Attentive Fusion for Multi-Modal Learning of Neuroimaging and Genomics Data”, IEEE International Workshop on Machine Learning for Signal Processing (MLSP) 2022.
[15-W] Yash Garg, “ReTriM: Reconstructive Triplet Loss for Learning Reduced Embeddings for Multi-Variate Time Series”, Workshop on High Dimensional Data Mining, International Conference on Data Mining (ICDMW) 2021.
[14-J] Manoj Tiwaskar, Yash Garg, Xinsheng Li, K. Selcuk Candan, Maria Luisa Sapino, “Selego: Robust Variate Selection for Accurate Time Series Forecasting”, Special Issue of European Conference on Machine Learning (ECML), Data Mining and Knowledge Discovery (DMKD), 2021 -
[13-J] Hans Behrens, K. Selcuk Candan, Xilun Chen, Yash Garg, “DataStorm: Coupled, Continuous Simulations for Complex Urban Environment”, ACM Transactions of Data Science (TDS), 2021.
[12-C] Yash Garg, K. Selcuk Candan, “XM2A: Multi-Scale Multi-Head Attention with Cross-Talk”, Internation Conference on Multimedia Information Processing and Retrieval (MIPR), 2021
[11-C] Yash Garg, K. Selcuk Candan, “SDMA: Saliency-Driven Mutual Cross Attention”, International Conference on Pattern Recognition (ICPR), 2021
[10-C] Yash Garg, K. Selcuk Candan, Maria Luisa Sapino, “SAN: Scale-Space Attention Network”, International Conference on Data Engineering (ICDE), 2020
[09-C] Yash Garg, K. Selcuk Candan, “iSparse: Output Informed Sparsification of Neural Networks”, International Conference on Multimedia Retrieval (ICMR), 2020
[08-T] Yash Garg, “On Feature Saliency and Deep Neural Networks”, Ph.D. Dissertation, Arizona State University, 2020
[07-C] Yash Garg, K. Selcuk Candan, “RACKNet: Robust Allocation of Convolutional Kernels in Neural Networks”, International Conference on Multimedia Retrieval (ICMR), 2019
[06-W] Hans Behrens, Mao-Lin Li, Ashish Gadkari, Yash Garg, “Load-Adaptive Continuous Coupled-Simulation Ensembles with DataStorm and Chameleon”, Chameleon Cloud (CC), 2019
[05-J] Hans Behrens, K. Selcuk Candan, Xilun Chen, Ashish Gadkari, Yash Garg, et al., “DataStorm-FE: A Data and Devision-Flow and coordination Engine for Coupled Simulation Ensembles”, Proceedings of Very Large Database (VLDB), 2018
[04-D] Silvestro Poccia, Maria Luisa Sapino, Xilun Chen, Yash Garg, “SIMDMS: Data Management and Analysis to Support Decision Making Through Large Simulation Ensembles”, Extended Database Technology (EDBT), 2017
[03-C] Yash Garg, Silvestro Roberto Poccia, “On the Effectiveness of Distance Measures for for Similarity Search in Mutli-Variate Sensory Data”, International Conference on Multimedia Retrieval (ICMR), 2017
[02-T] Yash Garg, “Multi-Variate Time Series Similarity Measures and their Robustness Against Temporal Asynchrony”, MS Thesis, Arizona State University (ASU), 2015
[01-W] Sicong Liu, Yash Garg, K. Selcuk Candan, Maria Luisa Sapino, Gerardo Chowel-Punette, “NOTES2: Network-of-Traces for Epidemic Spread Simulations”, Association for Advances in Artificial Intelligence (AAAI) Workshop, 2015

Services

2022
Journal Reviewer, Transactions on Knowledge Discovery and Data Engineering (TKDE)
Program Committee, ACM International Conference on Multimedia Retrival (ICMR)
Program Committee, International Conference on Time Series and Forecasting (ITISE)
Program Committee, ACM Multimedia (ACMMM)
2021
Journal Reviewer, Transactions on Knowledge Discovery and Data Engineering (TKDE)
Program Committee, International Conference on Multimedia Retrieval (ICMR)
2020
Journal Reviewer, Transactions on Knowledge Discovery and Data Engineering (TKDE)
Conference External Reviewer, Very Large Databases (VLDB)
Program Committee, International Conference on Multimedia Retrieval (ICMR)
Journal Reviewer, Transactions on Database Systems (TODS)
Conference Reviewer, Database Systems for Advanced Applications (DASFAA)
2019
Journal Reviewer, Transactions on Knowledge Discovery and Data Engineering (TKDE)
Conference External Reviewer, Extended Database Technology (EDBT)
Conference Reviewer, Conference on Knowledge Management (CIKM)
Program Committee, International Conference on Multimedia Retrieval (ICMR)
2018
External Reviewer, International Conference on Data Engineering (ICDE)
Journal Reviewer, Transactions on Knowledge Discovery and Data Engineering (TKDE)
External Reviewer, EuroPar
Journal Reviewer, Transaction on Database Systems
External Reviewer, SIG on Knowledge Discovery and Data Mining (SIGKDD)
Conference External Reviewer, Pacific Asia Knowledge Discovery and Data Engineering (PAKDD)
2017
Conference Reviewer, Database Systems for Advanced Applications (DASFAA)
Conference External Reviewer, Database Systems for Advanced Applications (DASFAA)
Journal Reviewer, Transactions on Knowledge Discovery and Data Engineering (TKDE)
Conference External Reviewer, Extended Database Technology (EDBT)
Journal Reviewer, Transactions on Multimedia (TMM)
Journal Reviewer, Transactions on Cloud Computing (TCC)
2016
Journal Reviewer, Transactions on CLoud Computing (TCC)
Conference Reviewer, ASONAM Conference Reviewer, Database Systems for Advanced Applications (DASFAA)
Journal Reviewer, Transactions of Knowledge Discovery and Data Engineering (TKDE)
Journal Reviewer, Transactions on Multimedia (TMM)
Conference External Reviewer, Association for Advances in Artifical Intelligence (AAAI)
External Reviewer, SIG on Knowledge Discovery and Data Mining (SIGKDD)
External Reviewer, SIG on Management of Data (SIGMOD)